Exploration of the antiviral efficacy of thiophene derivatives targeting human papillomavirus (HPV) and prevention of cancer: A comprehensive computational approach

Exploration of the antiviral efficacy of thiophene derivatives targeting human papillomavirus (HPV) and prevention of cancer: A comprehensive computational approach | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Exploration of the antiviral efficacy of thiophene derivatives targeting human papillomavirus (HPV) and prevention of cancer: A comprehensive computational approach Michael O. Odey, Alpha O. Gulack, Rose O. Ogar, Stanley J. Oduma, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4247398/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Owing to the public health concern of human papillomavirus infection, which is capable of progressing into cancer among the population today, desperation to mitigate the cause of this infection is needed; hence, in this research, we unveiled the antiviral effects of four thiophene derivatives, 2B, 2C, 2D and 2E, against human papillomavirus (HPV) via computational DFT and molecular docking approaches along with ADMET prediction. Interestingly, the compounds showed great stability according to conformational assessment, spectroscopic studies (FT-IR and UV‒Vis), NBO studies, and quantum descriptor analysis. These compounds mostly exhibit LP→ LP, σ*→ σ*, and σ*→ σ transitions, as 2B shows a dominant π*→ π* orbital transition. Their reactivity was observed in different studies; for example, the HOMO-LUMO and DOS results highlighted 2B as the most reactive, among others. The energy gaps were 3.758 eV, 3.750 eV, 3.743 eV, and 3.724 eV for 2B, 2C, 2D, and 2E, respectively. During the docking process, the compounds displayed a high binding affinity and number of amino acids after interacting with the 1R8H and 4GIZ proteins of HPV, especially when they interacted with the 4GIZ protein, as the 2E-4GIZ complex displayed a robust affinity of -6.4 kcal/mol. Hence, these compounds show great antiviral potential against HPV and are promising candidates for novel HPV infection therapies. Human papillomavirus (HPV) thiophene derivative drug design molecular docking DFT study Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Human papillomavirus (HPV) is a widespread viral infection, often transmitted through sexual contact, affecting millions of individuals globally [ 1 ]. This diverse group of viruses comprises over 200 distinct types, with some posing minimal health risks, while others have been linked to a range of cancers and genital warts [ 2 – 4 ]. HPV is transmitted through skin-to-skin contact, primarily during sexual activity [ 5 ]. However, it can also be transmitted through other forms of close contact, such as kissing or touching infected surfaces [ 6 , 7 ]. Engaging in early sexual activity, having multiple sexual partners, or having a weakened immune system significantly increases the likelihood of contracting the virus [ 8 ]. HPV infections are categorized into two main groups based on their potential to cause cancer (low-risk and high-risk types) [ 9 ]. Low-risk HPV strains such as types six and eleven are responsible for the development of genital warts, which are benign growths that appear on the genital and anal areas. While they can be unsightly and uncomfortable, genital warts do not lead to cancer [ 9 , 10 ]. HPV strains of low-risk are not associated with cancer and tend to cause genital warts instead. On the other hand, high-risk HPV strains, especially types 16 and 18, are strongly linked to the development of cancers in the cervix, anus, penis, vulva, vagina, and oropharynx [ 11 , 12 ]. Persistent infection with these high-risk types is the primary risk factor for the development of HPV-related cancers. Prevention of HPV infections primarily revolves around vaccination and practicing safe sex [ 13 ]. Human Papillomavirus (HPV) vaccines, such as Gardasil and Cervarix, are highly effective preventive measures against infection with the most prevalent cancer-causing strains of the virus [ 14 ]. Raising awareness about HPV-promoting vaccination and encouraging safe sexual practices are crucial steps in combating the spread of this widespread and potentially serious infection. However, as a leading cause of preventable cancers, particularly cervical cancer, the significance of HPV extends beyond its association with sexual health to broader public health concerns [ 15 , 16 ]. Due to the diverse health risks of human papillomavirus (HPV), researchers have recently been interested in unraveling the complexity of HPV and exploring its molecular biology, transmission, associated health risks, preventive measures, and broader societal impact. In recent years, the incorporation of computational approaches in drug design and discovery has significantly enhanced the development of drug formulations. The research conducted by Akash et al. (2023) [ 17 ] on novel computational and drug design strategies to inhibit human papillomavirus (HPV)-associated cervical cancer and the DNA polymerase theta receptor using apigenin derivatives is a significant contribution to the field. Their research results emphasized the increased effectiveness of apigenin 4'-O-rhamnoside and apigenin-4'-alpha-L-rhamnoside against the HPV45 oncoprotein E7 (PDB ID 2EWL). Apigenin and apigenin 5-O-beta-D-glucopyranoside also demonstrated significant binding energy against the L1 protein in humans. Besides, the researchers observed a binding affinity range of -7.5 kcal/mol to -8.8 kcal/mol for DNA polymerase theta, indicating the likelihood of apigenin derivatives to inhibit this enzyme (PDB ID 8E23). Aarthi et al. (2020) [ 18 ] explored structural dynamic studies to identify EGCG analogs for inhibiting human papillomavirus E7. They identified small molecules and EGCG as potent inhibitors against the HPV 16 E7 oncoprotein. Furthermore, Aarthy and Singh [ 19 ] utilized a computational approach to explore the relationship between protein tyrosine phosphatase and E7 oncoproteins of high- and low-risk HPV. The findings revealed that the LXCXE domain of HPV E7 at both high and low risk adheres to a tumor suppressor protein, and that certain compounds can interfere with the interaction between the oncoprotein and tumor suppressor at the E7–PTPN14 interface. Akash et al. (2023) conducted an extensive study on natural apigenin derivatives for inhibiting human papillomavirus-associated cervical cancer and DNA polymerase theta receptor through a mechanistic approach. According to their findings, apigenin 4'-O-rhamnoside and apigenin-4'-alpha-L-rhamnoside demonstrated significant efficacy against the HPV45 oncoprotein E7 (PDB ID 2EWL), while apigenin and apigenin 5-O-beta-D-glucopyranoside exhibited notable binding energy against the L1 protein of humans. The study revealed that the inhibitory potential of apigenin derivatives against DNA polymerase theta was significant, with binding affinities ranging from − 7.5 kcal/mol to -8.8 kcal/mol (PDB ID 8E23). In a related study, Salaria et al. (2022) also investigated the effects of apigenin derivatives on HPV-associated cervical cancer. However, through an in-silico approach, [ 21 ] investigated the potential of traditional Himalayan herbs' phytoconstituents to inhibit human papillomavirus (HPV-18) for the treatment of cervical cancer. The research revealed that among the selected phytoconstituents, eriodictyol-7-glucuronide, stigmasterol, clicoemodin, and thalirugidine demonstrated the most favorable interactions and docking scores of -9.1, -8.7, -8.4, and − 8.4 kJ/mol, respectively. Notably, these phytoconstituents exhibit binding affinities that are similar to, or even greater than, those of standard anticancer drugs like imiquimod (-6.1 kJ/mol) and podofilox (-6.9 kJ/mol). To date, the quest for effective drug molecules to combat HPV infection has remained elusive. The anticipation of innovative anti-HPV chemotherapies featuring unique modes of action and the identification of potential drugs are of utmost importance. In our research study, we utilized an in-silico approach to evaluate the effectiveness of the study compounds against HPV, with the goal of exploring their anti-HPV potential. Method 2.1 Experimental methods 2.2 DFT method Theoretical analysis of the study compounds was performed using density functional theory (DFT) calculations. These calculations were carried out at the B3LYP/6-311G ++ (d, p) level of theory to evaluate the properties and behavior of the compounds under investigation. The DFT method, which is widely used in the field of quantum chemistry, employs a mathematical framework to predict the electronic properties and behavior of molecules. The study aimed to provide insights into the molecular structure and properties of the compounds, which would aid in the development of new materials and drugs. This optimization was run by Gaussian 09 software [ 23 ]. The method and basis set of choice were selected based on the atoms of the compounds and aimed to improve the energy minimization calculations. The electronic properties were calculated, and the natural bond orbital (NBO) was automatically calculated by Gaussian software. Likewise, the HOMO-LUMO energies were further converted from atomic units (a.u.) to electron volts (eV), and a graphical illustration of the isosurface, which depicts the electron density, was obtained by Chemcraft v1.8 [ 24 ]. Density of state (DOS) analysis was employed to elucidate the electronic behavior graphically, which was carried out utilizing Multiwfn v3.7 and Origin 2018 software [ 25 , 26 ]. Furthermore, theoretical spectral analysis was performed with the method and basis set to gain more insight into the behavior of the compounds. The results were virtualized and recorded with the aid of Gaussview v6.0 software [ 27 ]. Conversely, the virtual studies that revealed various natures of interactions and localized regions of electrons were possibly plots with the aid of Multiwfn packages. NCI was obtained through the VMD v1.9.3 application [ 28 ]. Emphatically, the outlined objectives aides in understanding the electronic behavior and possible drug nature of the studied ligands. 2.3 Molecular docking protocol Molecular docking, an important computational methodology in drug design, facilitates the identification of interactions between ligands and proteins and their binding regions [ 29 ]. This investigation explored the potential therapeutic effects of compounds 2B, 2C, 2D, and 2E against human papillomavirus (HPV). The tagged protein structures coded as 1R8H and 4GIZ were acquired in PDB format from the Research Collaboratory for Structural Bioinformatics (RCSB), an online database ( www.rcsb.org ). The selection of the target protein, specifically 1R8H, was based on research conducted by Dell et al. (2003) [ 30 ], who found that the E2 DBDs of both HPV16 and HPV6 identified a longer version of the consensus E2 binding site, which was determined through research on the BPV1 E2 protein. Conversely, the 4GIZ protein code was reported by Zanier et al. (2013) [ 31 ], who investigated the structural basis of LxxLL motifs in HPV E6 oncoproteins. Their study underscores the structural basis of both the multifunctionality and oncogenicity of E6 proteins. To explore the biological potential of our compound against HBV, the protein of choice above was used. After the proteins were downloaded, they were further prepared using Biovia Discovery Studio 21 software [ 32 ]. The process included the removal of water molecules and native ligands from the protein structure. The active site within the protein was highlighted with a sphere shape where the xyz coordinates were obtained. Polar hydrogen was added to the protein structure to facilitate the docking process. Additionally, the docking process was carried out using PyRx v0.8 [ 33 ], revealing the binding mode and affinity of the ligand‒protein interaction and graphically illustrating the 2D interaction. In addition, 3D demonstrations of the ligand‒protein interactions were captured using PyMOL v2.4 software [ 34 ]. Results and Discussion 3.1 Geometry optimization The process of geometry optimization is essential in the study of innovative pharmaceutical compounds because it explains their stable behavior and refines and perfects the spatial arrangement of atoms within a molecular structure, which are basic tools in novel drug design [ 35 ]. Thiophene derivatives characteristically adopt a planar structure due to resonance stabilization within their aromatic ring. Thus, this planar structure is facilitated by the overlap of p-orbitals in the carbon and sulfur atoms, akin to benzene [ 36 ]. However, substitution patterns and steric interference can lead to deviations from perfect planarity, inducing slight distortions or twists in the ring system [ 37 , 38 ]. These deviations are often influenced by factors such as substitution patterns, electronic effects, and intermolecular interactions. Hence, this study was applied to 2B, 2C, 2D, and 2E compounds to identify the most stable configuration of a molecule, directly impacting its behavior and interactions within the compound. The bond lengths and angles of the compounds, including Br 25 -C 17 , S 20 -C 19 , and S 29 -C 10, which are similar to all the other compounds, and F 31 ˗C 2 , Cl 32 ˗C 2 , H 32 ˗C 2 , and O 32 ˗C 4, which differ among the compounds, were carefully analyzed ( Table 1 ) . Most of the bonds around the methanethioamide scaffold, hydrazineylmethanide scaffold, and 4-bromo-5-(methylthio)-2,3-dihydrothiophen-3-ide scaffold of the studied compounds exhibited similar lengths—1.904 Å, 1.761 Å, and 1.677 Å, respectively—across all the studied compounds. Moreover, a clear variation at the specific position within the benzene ring of the compounds was recorded. The length of the fluorobenzene of 2B was 1.354 Å at the F 31 ˗C 2 label, the length of the chlorobenzene of 2C was 1.756 Å at the Cl 32 ˗C 2 label, and the length of the benzene of 2D was 1.083 Å at the H 32 ˗C 2 label; the length of the anisoles of 2E was 1.373 Å at the O 32 ˗C 4 label. The integration of Cl, F, and OCH 3 greatly influenced the bond length of the compounds, thereby affecting their conformation and stability. Comparatively, the 2D compound with no attachment of foreign atoms to its benzene ring shows slightly greater stability than the other systems. Compound 2C, which contains chlorine, has a longer bond length, implying that it is less stable than other studied thiophene derivatives. Table 1 Structural analysis of the studied thiophene derivatives, revealing bond lengths and angles at various selected labels Compound Bond label Bond length (Å) Bond label Bond angle ( o ) 2B Br 25 C 17 1.904 B 25 C 17 C 15 121.70 S 20 C 19 1.761 S 20 C 19 S 16 120.23 S 29 C 10 1.677 S 29 C 10 N 9 125.72 F 31 ˗C 2 1.354 F 31 C 2 C 3 118.90 2C Br 25 C 17 1.904 Br 25 C 17 C 15 121.70 S 20 C 19 1.761 S 20 C 19 S 16 120.23 S 29 C 10 1.677 S 29 C 10 N 9 126.03 Cl 32 C 2 1.756 Cl 32 C 2 C 3 119.60 2D Br 25 C 17 1.904 Br 25 C 17 C 15 121.69 S 20 C 19 1.761 S 20 C 19 S 16 120.26 S 29 C 10 1.677 S 29 C 10 N 9 126.22 H 32 ˗C 2 1.083 H 32 C 2 C 3 120.25 2E Br 25 C 17 1.904 Br 25 C 17 C 15 121.66 S 20 C 19 1.761 S 20 C 19 S 16 120.28 S 29 C 10 1.680 S 29 C 10 N 9 127.92 O 32 ˗C 2 1.373 C 4 O 32 C 33 118.95 3.2 Spectroscopy 3.2.1 FT-IR analysis Fourier transform infrared spectroscopy (FT-IR) analysis involves the measurement of the absorption or emission of infrared light by molecular bonds within a sample, providing detailed information about its chemical composition and structure [ 39 ]. When applied to biological compounds, it enables the identification of functional groups and secondary structures, including α-helices, β-sheets, and random coils. Hence, analyzing the characteristic absorption peaks in the infrared spectrum can infer the presence of specific chemical bonds and provide insights into the conformational changes or structural rearrangements induced by light absorption. We employed this technique theoretically in our investigated compounds to offer valuable information about the compounds' stability, hydration dynamics, and structural alterations. The reported literature states that each type of bond within a molecule absorbs infrared radiation at characteristic wavelengths, resulting in unique spectral features that can be used for identification and structural analysis [ 40 – 42 ]. From our results, as shown in Table 2 , diverse vibrational modes were observed at the respective wavelengths due to light absorption by the compounds. Respective functional groups were identified in the 2B, 2C, 2D, and 2E compounds, and these groups included NH (amine group), CH and CH3 (methyl group), and C = C (alkane group). Strong absorption bands in the fingerprint region of the spectrum were observed for the amine group, with notable symmetric stretching across all the studied compounds; thus, low absorption was observed upon rocking vibration. This is suggested to contribute to the stability characteristics of the compounds. Similarly, at high frequencies, symmetric and asymmetric vibrations of methyl groups at the benzene and thiophene rings were observed across all the compounds, indicating an additional stable conformation. Likewise, a strong absorption of light by the C = C group situated at the benzene ring was recorded along with symmetric vibrations. The presence of these groups with symmetric and asymmetric vibrations indicates the strong stability of the compounds despite the rocking and scissoring stretching observed at other frequencies. However, the frequencies of the identified groups range from 3576 cm − 1 to 1404 cm − 1, which agrees with the reported literature [ 43 ]. Therefore, this technique facilitates the elucidation of molecular structures, dynamics, and interactions, thereby advancing our understanding of biological systems and informing the development of novel therapeutic interventions and biomaterials. Table 2 FT-IR analysis results for the studied complexes Compound Experimental value (CM − 1 ) Theoretical value (CM − 1 ) Assignment 2B Symmetric stretching 3324, 3220, 3117, 1640, 1262 3576, 3564, 3283 Symmetric stretching NH 3220, 3204 Symmetric stretching CH 3200, 3172 Asymmetric stretching CH 3172, 3135 Asymmetric stretching CH3 3047 symmetric stretching CH3 1648, 1642, 1515, symmetric stretching C = C 1585, 1551, 1473, 1371 Rocking stretching NH 1551, Rocking stretching CH 1481, 1464 Scissoring stretching CH3 2C Symmetric stretching 3330, 3224, 3109, 1647, 1255 3576, 3285, Symmetric stretching NH 3564, Asymmetric stretching NH 3223, 3204, 3203 Symmetric stretching CH 3199, 3167 Asymmetric stretching CH 3144, 3135 Asymmetric stretching CH3 3047 Symmetric stretching CH3 1635, 1515 Symmetric stretching C = C 1627, 1584, 1550, 1472 Rocking stretching NH 1523 Rocking stretching CH 1481 Scissoring stretching CH3 2D Symmetric stretching 3328, 3225, 3111, 1641, 1257 3574, 3280 Symmetric stretching NH 3564 Asymmetric stretching NH 3221, 3180, 3171, 3159, 3144, 3135 Asymmetric stretching CH 3204, 3193, 3047 Symmetric stretching CH 1641, 1635, 1515 Symmetric stretching C = C 1585, 1557 Rocking stretching NH 1527, 1478 Rocking stretching CH 1481 Scissoring stretching CH3 2E Symmetric stretching 3330, 3224, 3119, 1651, 1264 3559, 3280 Symmetric stretching NH 3537, Asymmetric stretching NH 3239, 3207, 3206 Symmetric stretching CH 3190, 3174 Asymmetric stretching CH 3143, 3139, 3135, 3080 Asymmetric stretching CH3 3047, 3016 Symmetric stretching CH3 1649, 1590, 1585, 1475, 1385, 1368, 1360 Rocking stretching NH 1637, 1515, 1404 Symmetric stretching C = C 1521, 1515, 1491, 1481, 1469, 1464 Scissoring stretching CH3 1493 Rocking stretching CH 3.2.3 UV‒vis analysis UV‒Vis spectroscopy analysis exploits the absorption of light in the ultraviolet and visible regions of the electromagnetic spectrum by molecules containing conjugated π-electron systems. The absorption of light occurs due to the excitation of electrons from ground-state molecular orbitals to higher energy excited states [ 44 ]. The absorption spectrum obtained provides information about the electronic transitions within the molecule, including π-π* transitions in aromatic rings and n-π* transitions in conjugated compounds, as more of these characteristics were observed in our investigation through natural bond orbital studies [ 45 ]. This technique is also useful for studying the structure and function of biological molecules because it can offer insight into their secondary structure, folding, and stability. Our analysis results ( Table 3 ) of the studied compounds suggest that electronic transitions occur in the molecules upon absorption of light. The ground state refers to the lowest energy state of the molecule, while the excited states represent higher energy states attained upon absorption of photons. The excitation energies of the different compounds were compared: compound 2B: ground state (2.8601 eV), first excited state (3.5718 eV), and second excited state (3.7185 eV); compound 2C: ground state (2.8532 eV), first excited state (3.5514 eV), and second excited state (3.6887 eV); compound 2D: ground state (2.8489 eV), first excited state (3.5688 eV), and second excited state (3.6989 eV); and compound 2E: ground state (2.8551 eV), first excited state (3.5574 eV), and second excited state (3.6893 eV). From these results, it can be observed that all compounds undergo electronic transitions to higher energy states upon absorption of light. The differences in excitation energies between the ground and excited states reflect the energy required to promote electrons to higher orbitals. To assess the stability and reactivity of compounds based on these results, several factors need to be considered. Therefore, compounds with lower excitation energies may exhibit greater stability because less energy is required for excitation. Conversely, compounds with higher excitation energies may be more reactive, as they have higher energy levels available for participating in chemical reactions. This knowledge is supported by the higher wavelengths observed across each energy level of our studied compounds. Additionally, reports suggest that compounds with low energy levels tend to exhibit higher wavelengths [ 45 ]. Thus, comparing the provided data, compound 2C has the lowest excitation energies among the compounds, potentially indicating greater stability. Conversely, compound 2B has the highest excitation energy, suggesting that it might be more reactive. This finding supported the results revealed in the structural studies and frontier molecular orbital analysis, thereby providing more evidence of the reactivity and stability characteristics of the study compounds. Table 3 UV‒Vis results for all the studied thiophene derivatives optimized at the B3LYP/6-311G ++ (d, p) level of theory System Transition Type Energy (eV) Wavelength (nm) Oscillator strength ( f ) Percentage contribution (%) Transition 2B S 0 -S 1 (101 \(\to\) 102) 2.8601 433.49 0.0521 0.66466 H \(\to\) L S 0 -S 2 (100 \(\to\) 102) 3.5718 347.12 0.3951 0.65256 H \(\to\) L + 1 S 0 -S 3 (98 \(\to\) 102) 3.7185 333.43 0.0022 0.55956 H \(\to\) L + 3 2C S 0 -S 1 (105 \(\to\) 106) 2.8532 434.54 0.0548 0.66258 H \(\to\) L S 0 -S 2 (104 \(\to\) 106) 3.5514 349.11 0.4486 0.64502 H \(\to\) L + 1 S 0 -S 3 (102 \(\to\) 106) 3.6887 336.12 0.0007 0.50153 H \(\to\) L + 3 2D S 0 -S 1 (97 \(\to\) 98) 2.8489 435.20 0.0532 0.66797 H \(\to\) L S 0 -S 2 (96 \(\to\) 98) 3.5688 347.41 0.4078 0.65138 H \(\to\) L + 1 S 0 -S 3 (94 \(\to\) 98) 3.6989 335.19 0.0046 0.54718 H \(\to\) L + 3 2E S 0 -S 1 (105 \(\to\) 106) 2.8551 434.26 0.0691 0.65726 H \(\to\) L S 0 -S 2 (104 \(\to\) 106) 3.5574 348.53 0.6108 0.58147 H \(\to\) L + 1 S 0 -S 3 (103 \(\to\) 106) 3.6893 336.07 0.0089 0.57503 H \(\to\) L + 2 3.3 Electronic properties 3.3.1 Frontier molecular orbital analysis Frontier molecular orbital analysis elucidates the mechanisms involved in the transfer of charges from the filled orbital to the unfilled orbital. The application of the highest occupied molecular orbital and lowest unoccupied molecular orbital (HOMO-LUMO) analysis has provided valuable insights into the electronic structure and reactivity of molecules and provided insight into their potential interactions with other compounds [ 46 ]. The analyzed HOMO and LUMO energies, as presented in Table 4 , were further used to calculate parameters such as the energy gap, ionization potential (IP), electron affinity (EA), chemical softness and hardness (σ and η), chemical potential (µ), electrophilicity index (ω) and Fermi energy level (EFL) [ 47 ]. The energy gap ( E g ), defined as the range within a solid where no electron states are present [ 48 ], was calculated using the following equation: E g = E LUMO - E HOMO where E g represents the energy gap, E LUMO represents the energy of the LUMO and E HOMO represents the energy of the HOMO. The obtained results exhibit varying energy gaps in the following trend: 3.758 eV > 3.750 eV > 3.743 eV > 3.724 eV for 2B, 2C, 2D, and 2E ( Fig. 2 ) . This result signifies that the 2B compound possesses a higher energy gap of 3.758 eV, indicating that a greater amount of energy is required to move an electron from the occupied orbital to the uncopied orbital, thus making it less reactive than the other compounds. Conversely, the 2E compound exhibits the lowest energy gap, suggesting that less energy is needed to move an electron from the occupied orbital to the uncopied orbital, thereby indicating that it is the most reactive compound among those under study [ 49 ]. The ionization potential reflects the ability of a compound to undergo chemical reactions involving ion formation or electron donation. The calculated values presented in Table 4 suggest that the 2C compound demonstrates a higher ionization potential (IP) at 6.120 eV because of its stability, and a high ionization potential indicates low susceptibility to certain chemical reactions involving electron transfer. In the context of drug design, this characteristic may contribute to the stability of drug atoms, ensuring their structural integrity during storage and transportation. Conversely, the 2E compound exhibits a lower ionization potential of 5.926 eV, signifying the ease of electron loss. Additionally, the investigation of chemical potential, chemical hardness, and chemical softness provided insights into the polarity of these compounds. Chemical hardness indicates how molecules are polarizable and the distortion of the electron cloud in an electric field. The chemical hardness was found to be higher in 2B, with a hardness value of 1.879 eV, and lower in the 2E compound. Higher chemical softness indicates a lower degree of polarizability and low distortion of the electron cloud in response to an electric field. Hence, the chemical softness aligns with the trend in chemical hardness. However, it is clear that 2E is likely to be a highly reactive thiophene, while 2E is less reactive than the other studied thiophene derivatives. This finding is comprehensively supported by the results highlighted in the geometry optimization study. Table 4 HOMO-LUMO and quantum descriptor results for all the studied compounds Compound HOMO-eV LUMO-eV Energy gap (eV) IP EA σ η µ ω EFL 2B -6.089 -2.331 3.758 6.089 -2.331 0.266 1.879 -4.210 4.716 4.210 2C -6.120 -2.370 3.750 6.120 2.370 0.267 1.875 -4.245 4.804 4.245 2D -6.021 -2.278 3.743 6.021 2.278 0.267 1.872 -4.149 4.600 4.149 2E -5.926 -2.201 3.724 5.926 2.201 0.268 1.862 -4.064 4.434 4.064 3.3.2 Natural Bond Orbital (NBO) Analysis The utilization of natural bond orbital (NBO) analysis can allow for the examination of both intermolecular and intramolecular interactions between donor and acceptor orbitals [ 50 ]. This study provides insights into the extent of charge transfer from the valence band to the conduction band. Regarding the Schrödinger equation, the NBO method enhances our understanding of chemical bonding concepts [ 51 ]. Therefore, to ascertain the degree of conjugation within our studied compounds, second-order perturbation theory analysis was employed, as documented in the literature [ 52 ]. This knowledge is critical in the novelty of the drug; hence, the magnitude of the perturbation energy E 2 correlates with the strength of interaction between the donor and acceptor, thereby enabling us to predict the stability of these compounds [ 53 ]. However, E 2, also known as the stabilization energy, signifies electron delocalization between occupied and unoccupied orbitals, illustrating a stable donor-acceptor relationship. The calculation of the perturbation energy E 2 involves the use of Eq. 1 . E 2 \(=qi\frac{\left(Fij\right){)}^{2}}{E\left(i\right)-E\left(j\right)}\) (1) where E 2 represents the perturbation energy of the second order, Fij signifies the off-diagonal elements on the folk matrix, and E(j) - E(i) denotes the diagonal elements. Table 5 displays the computed values of the donor-acceptor interactions derived from the higher perturbation energy among the examined compounds. The identified Interactions include double anti-bonding to double anti-bonding (π*→ π*), lone pair to single anti-bonding (LP→ σ*), single anti-bonding to single anti-bonding (σ*→ σ*), and lone pair to lone pair (LP→ LP) interactions, with a predominant occurrence of σ*→ σ* on 2C, 2D, and 2E compounds. These interactions were chosen based on their significant contributions to the charge transfer process observed for various charge transitions from the donor to acceptor orbital. The NBO results revealed a 2B compound with electron delocalization between πC5→ πC6 and πC4→ π*C5 and the highest perturbation energy of 121.13 kcal/mol, suggesting a strong interaction that underlines the robust stability of the compound, as described earlier in frontier molecular studies and other quantum descriptor analyses. Hence, 2B was more stable than the other thiophene compounds because of its large perturbation energy and double bond transition between the donor and acceptor (π*→ π*). In contrast, the 2E compound displayed lower perturbation energy (E2) at most of its door-acceptor orbitals and a simple transition of charges within a bonding from LP→ LP, σ*→ σ*, and σ*→ σ transition, contributing to the easy flow of electrons from the donor to acceptor. Table 5 Second-Order Perturbation Theory Analysis of the Fock Matrix in the NBO Basis Compound Transition Donor NBO (i) Acceptor (j) E(2) (Kcal/mol) E(j)-E(i) (a.u) F(ij) (a.u) 2B π*→ π* π*C 5 → π*C 6 π*C 4 → π*C 5 121.13 0.01 0.065 π*→ π* π*C 17 → π*C 19 π*C 14 → π*C 15 60.67 0.02 0.058 LP→ σ* LP S 29 σ*C 4 →LP H 30 76.41 0.72 0.169 2C σ*→ σ* σ*C 5 → σ*C 6 σ*C 3 → σ*C 4 93.78 0.01 0.065 σ*→ σ* σ*C 1 → σ*C 2 σ*C 3 → σ*C 4 75.61 0.02 0.063 σ*→ σ* σ*C 17 → σ*C 19 σ*C 14 → σ*C 15 60.87 0.02 0.058 2D σ*→ σ* σ*C 5 → σ*C 6 σ*C 1 → π*C 2 96.96 0.01 0.063 σ*→ σ* σ*C 5 → σ*C 6 σ*C 3 → π*C 4 85.92 0.01 0.065 σ*→ σ σ*C 17 → σ*C 19 σC 14 →σC 15 59.79 0.02 0.058 2E LP→ LP LP S 29 LP C 10 79.42 0.10 0.116 σ*→ σ* σ*C 3 → σ*C 4 σ*C 5 → π*C 6 50.33 0.03 0.063 σ*→ σ σ*C 17 → σ*C 19 σC 14 → σ*C 15 48.37 0.03 0.058 3.3.3 Density of state analysis The study of density of states involves analyzing the complete density of states (TDOS), partial density of states (PDOS), and overlap partial density of states (OPDOS). This study is illustrated in plots to make predictions about the contributions of molecular orbitals. In the field of drug design, DOS analysis was conducted to gain significant insights into the fragments responsible for the redistribution of electrons in a compound, thereby pioneering the compounds’ reactivity and stability characteristics [ 54 ]. The electron occurrence patterns of the highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) were clarified by this analysis. It also provided an accurate count of the state available for the study compounds to occupy at different energy intervals [ 55 ]. From the results plotted, the left side, as divided by the dotted line, represents the bonding molecular orbitals, whereas the antibonding molecular orbitals are illustrated on the right side. In the graphical representation of the compounds, the energy of the bonded atoms is considered based on their contributions to the molecular orbitals [ 56 ]. Figure 3 reveals that the four different compounds (2B, 2C, 2D, and 2E) exhibit similar distributions of electrons due to their similar properties. In all the compounds, the carbon atom exhibits the highest peak, suggesting its significant contribution to the compound's reactivity. Hence, the trends are observed in the following order: carbon > hydrogen > nitrogen > bromine for all the compounds except 2D, which replaced Br with sulfur. The fragments with the least distribution of charges are the atoms that provided the unique variations in the compound (fluorine in 2C, chlorine in 2B, bromine in 2D, and oxygen in 2E). Additionally, the 2E compound exhibited a slightly low Fermi energy level (0.149 a.u.), indicating the easy distribution of charges of atoms from the conduction band into the valence band, resulting in increased reactivity. Conversely, the 2C and 2D compounds had the highest Fermi energy levels (0.156 a.u.), indicating that they were slightly less reactive than the 2B and 2E compounds. 3.4 Visual studies 3.4.1 Noncovalent interaction (NCI) analysis Noncovalent interactions characterized by their weak nature and absence of chemical reactions are often referred to as nonbonded interactions [ 57 ]. There are three distinct types of noncovalent interactions (hydrogen bonds, van der Waals interactions, and electrostatic interactions), with van der Waals interactions being the most prevalent and known to involve close-distance interactions [ 58 ]. These short-range interactions occur whenever atoms or molecules closely approach each other, thereby involving atoms within distances comparable to their sizes [ 59 ]. Hydrogen bonds, situated at the interface between chemical bonds and noncovalent interactions, form between pairs of atoms when one acts as a proton donor and the other acts as a proton acceptor. In contrast, electrostatic interactions represent the third category of noncovalent interactions, distinguished by their long-range nature. The electrostatic interactions extend beyond the confines of the closest atoms, making their description more complex. This study is vital in drug design because it provides a comprehensive understanding of the various natures of the interactions of compounds. However, the various interactions are represented by different colors; van der Waals interactions are denoted by green, hydrogen interactions are denoted by blue, and electrostatic interactions, also known as steric repulsion, are denoted by red [ 60 ], as shown in Fig. 4 . This result illustrates the dominance of the green iso-surfaces in all the studied compounds. Close observation revealed that the green color was dominant at the outside regions of the methanethioamide scaffold, hydrazineylmethanide scaffold, and 4-bromo-5-(methylthio)-2,3-dihydrothiophen-3-ide scaffold, indicating good characteristics of the drug. Additionally, steric repulsion forces were highlighted at the intramolecular region of the methane-thioamide scaffold and benzene ring of the compounds, whereas no hydrogen bonds were present across the compounds. The nature of the interactions observed suggested that the studied compounds could be promising candidates for the development of novel drugs. 3.4.2 Electron Localization Function (ELF) Analysis An electron localization function (ELF) investigation quantifies the probability of locating an electron within the locality of a position electron situated at a specific point with the same spin [ 61 ]. The ELF revealed the degree of spatial confinement of the reference electron, offering a means to map the probability distribution of electron pairs in a biological compound. One of the crucial aspects of developing a novel drug is gaining wide knowledge of the compound; hence, this study revealed important regions that are electron-rich, providing an advantage for interference with another biological system [ 61 ]. Interestingly, the results of this analysis illustrate the spatial distribution of electrons within the molecule through distinct colorations in various regions. The red areas signify high electron localization values, which indicate electron density, thus highlighting the active site and likely binding with another compound. The yellow areas denote moderate ELF values, representing less pronounced electron localization. In contrast, the blue regions indicate extremely low ELF regions, suggesting weak electron localization and extensive electron delocalization. Figure 5 shows that all the studied compounds exhibit electron localization at most of the scaffolds. However, the 2E compound displayed more electron localization at the 4-bromo-5-(methylthio)-2,3-dihydrothiophen-3-ide scaffold and benzene ring regions even at its unique OCH 3 , which made it exempt from other compounds. This implies that the 2E compound would likely react with another compound, thus supporting its reactivity, as pointed out in the HOMO-LUMO investigation. Additionally, the spatial distributions of the electron density and charge within compounds 2B, 2C, 2D, and 2E predict the potential properties of the compounds, such as their ability to interact with biological targets, indicating their potential as drugs. 3.5 Molecular Docking Analysis This method plays an essential role in evaluating the chemical interactions between a ligand and disease-related proteins or receptors [ 63 ]. However, by predicting the active site of a protein to which the ligand binds, this analysis provides insights into the interaction strength and type, thus providing valuable information on the ligand's activity and mechanism against the disease [ 64 ]. In this context, our investigation investigated the biological activity and compatibility of four distinct compounds, labeled 2B, 2C, 2D, and 2E, against human papillomavirus. We conducted a comparison between the structures and DNA binding properties of E2 proteins obtained from oncogenic and nononcogenic human papillomaviruses (1R8H). Furthermore, we analyzed the crystal structure of the complete human papillomavirus oncoprotein E6 in complex with the LXXLL peptide of the ubiquitin ligase E6AP at a resolution of 2.55 Å (4GIZ). Vital parameters such as binding affinity, bond distance, and hydrogen bond interactions were ascertained and are presented in Table 5 . Furthermore, the docking results are graphically illustrated in Fig. 6 . Upon evaluation of the results, the protein‒ligand interactions between compound 2B and 1R8H and 4GIZ exhibited binding energies of -5.3 kcal/mol and − 5.6 kcal/mol, corresponding to 4 and 3 conventional hydrogen bonds, respectively. The 2C compound demonstrated binding affinities of -5.6 kcal/mol and − 4.8 kcal/mol with 3 and 2 conventional hydrogen bonds, respectively, while the 2D compound displayed binding affinities of -4.8 kcal/mol and − 5.7 kcal/mol with 2 and 3 conventional hydrogen bonds, respectively. Similarly, 2E had binding affinities of -5.2 kcal/mol and − 6.4 kcal/mol, respectively, with 3 hydrogen bonds. Notably, our findings indicate that the ligand‒protein interaction between the 2E compound and 4GIZ has the highest binding affinity of -6.4 kcal/mol, with three hydrogen bond interactions: D: GLN35:OE1, D: GLN35:OE1, and D: GLN35:OE1. This suggests its high efficacy against human papillomavirus. Although the studied thiophene derivative compounds show great binding affinity for 1R8H and 4GIZ, they exhibit strong negative values and short distances, as shown in the table. However, isotretinoin, a conventional drug, showed strong affinities of -8.3 kcal/mol and − 6.6 kcal/mol for 1R8H and 4GIZ, respectively, indicating that it has a greater affinity than the other studied compounds. However, it was notable that the 2E compound also displayed strong interaction behavior following a binding affinity < -5, which is indicative of strong binding. Therefore, it can be deduced that the study compounds show a good ability to inhibit the action of the selected protein, which is vital for the survival of HPV. This finding also implies that the studied compounds possess the potential to be considered novel antiviral agents, especially human papillomavirus. Table 6 The binding affinity and animal residue results for the interaction between the studied compounds, conventional drug, and selected protein of HPV Compound Best pose binding Affinity (kcal/mol) Amino acid residue Bond distance (Å) 2B-1R8H -5.3 A: THR316: O 2.2159 B: THR316: O 2.5773 A: SER315: OG 2.6591 B: THR316: O 3.0308 2B-4GIZ -5.6 C: LYS72:HZ2 2.9798 D: GLN35:OE1 2.2671 D: GLU41:OE2 2.2499 2C-1R8H -5.1 A: THR316: O 2.1944 B: THR316: O 2.1303 A: SER315: OG 2.7491 2C-4GIZ -5.6 D: GLN35: OE1 2.3445 D: GLU41: OE2 2.0839 2D-1R8H -4.8 B: HIS318: HD1 2.9887 B: LYS327: O 2.1144 2D-4GIZ -5.7 D: GLU41: OE2 2.9860 D: GLN35: OE1 2.2542 D: CYS63: SG 2.8373 2E-1R8H -5.2 B: THR316: O 1.9059 A: SER315: OG 2.7654 B: THR316: O 2.9302 2E-4GIZ -6.4 D: GLN35: OE1 2.5940 D: GLN35: OE1 2.3511 D: GLN35: OE1 2.7216 Isotretinoin + 1R8H -8.3 D: PO4501 C: ARG300 C: ASN304 - - - Isotretinoin + 4GIZ -6.6 B: ARG67 - 3.6 Pharmacokinetic Pharmacokinetics entails the action and disposition of a drug on the body system through the determination of absorption, distribution, metabolism, elimination, and toxicity [ 65 ]. Herein, the toxicity and drug likeness of the studied compounds were predicted to further elucidate their adverse effects and drug-like nature. This is crucial in drug development, as drugs with more adverse effects can hinder or damage the human body. However, this analysis was carried out using two online databases, protox II ( https://tox-new.charite.de/ ) and swissADME ( http://www.swissadme.ch/ ). Protox II was used to determine the toxicity of the compounds, while the drug likeness was determined using swissADME. Accurate prediction of toxicity and drug likeness can help save resources and time by ensuring that only compounds with desirable characteristics are used for drug development. 3.6.1 Toxicity Toxicity denotes the extent of harm that a substance can inflict on an organism following administration. The toxic effects of drugs are contingent upon the dosage administered. These effects can range from mild, targeting specific organs, to severe, impacting the entire biological system [ 66 ]. The liver is an important organ in the human body responsible for the elimination and metabolism of drugs, and hepatotoxicity provides information about the ability of a drug to cause damage or impairment to the liver. The results from Table 7 indicate active hepatotoxicity at a probability of 0.69 for all the studied compounds. However, carcinogenicity, which refers to the ability of substances to cause cancer or promote the development of cancerous cells in living organisms, was also predicted. The result shows inactivity at a probability of 0.62 across all the compounds. The tendency of a substance to confer adverse effects on the immune system was determined through immunotoxicity prediction, and the results highlighted that the probability of activity was 0.96 for all the studied compounds. The induction of genetic mutations was observed through mutagenicity prediction; therefore, the result was inactive at a probability of 0.97. Ultimately, the cytotoxicity of the compounds indicated that they were inactive at a probability of 0.93. Table 7 Pharmacotoxicity results for the studied compounds Compound Classification Targets Prediction Probability 2B Organ toxicity Hepatotoxicity Active 0.69 Toxicity endpoint Carcinogenicity Inactive 0.62 Toxicity endpoint Immunotoxicity Active 0.96 Toxicity endpoint Mutagenicity Inactive 0.97 Toxicity endpoint Cytotoxicity Inactive 0.93 2C Organ toxicity Hepatotoxicity Active 0.69 Toxicity endpoint Carcinogenicity Inactive 0.62 Toxicity endpoint Immunotoxicity Active 0.96 Toxicity endpoint Mutagenicity Inactive 0.97 Toxicity endpoint Cytotoxicity Inactive 0.93 2D Organ toxicity Hepatotoxicity Active 0.69 Toxicity endpoint Carcinogenicity Inactive 0.62 Toxicity endpoint Immunotoxicity Active 0.96 Toxicity endpoint Mutagenicity Inactive 0.97 Toxicity endpoint Cytotoxicity Inactive 0.93 2E Organ toxicity Hepatotoxicity Active 0.69 Toxicity endpoint Carcinogenicity Inactive 0.62 Toxicity endpoint Immunotoxicity Active 0.96 Toxicity endpoint Mutagenicity Inactive 0.97 Toxicity endpoint Cytotoxicity Inactive 0.93 3.6.2 Drug Likeness The term drug likeness encompasses the capacity of substances to possess physical properties or functional groups consistent with those found in established pharmaceutical compounds. The concept of drug likeness is instrumental in providing valuable insights into the molecular features that resemble those present in approved medications. However, this evaluation aids in determining the potential suitability of a molecule for drug development and its likelihood of exhibiting favorable pharmacological properties. The drug likeness of a compound can be evaluated using Lipinski's rule of 5 (RO5), Ghose's rule, and bioavailability scoring. Lipinski's rule of 5, formulated by Christopher A. Lipinski in 1997, is based on the observation that the majority of orally active drugs are relatively small molecules with certain physicochemical properties, such as appropriate lipophilicity and molecular size [ 67 ]. Lipinski's rule is a set of guidelines that specifies the ideal characteristics for drugs taken orally, including a molecular mass of less than 500 Daltons, a log P not exceeding 5, no more than 10 hydrogen bond acceptors, and no more than 5 hydrogen bond donors. The compounds in question (2B, 2C, 2D, and 2E) met all of these criteria, following the predictions analyzed in Table 8 . In addition, the Ghose filter assesses drug likeness based on the compound's molecular weight falling between 160 and 480 Daltons, a refractivity value greater than or equal to 40, between 20 and 70 atoms in the molecule, and a partition coefficient (log P) ranging from − 0.4 to 5.6. The results of the study indicate that the compounds (2B, 2C, 2D, and 2E) satisfy all of Ghose's rules [ 68 ]. It is highly desirable to accurately predict the drug-like properties of a drug in the early stages of drug discovery, as this approach can help rationalize the discovery process and save costs and time. Table 8 Drug-likeness prediction results for the studied compounds Compound Molecular weight Lipinski rule Ghose rule Violation 2B 404.34 g/mol MW ≤ 500 MLOGP ≤ 4.15 N or O ≤ 10 NH or OH ≤ 5 160 ≤ MW ≤ 480 -0.4 ≤ WLOGP ≤ 5.6 40 ≤ MR ≤ 130 20 ≤ atom ≤ 70 YES;0 violation 2C 420.80 g/mol MW ≤ 500 MLOGP ≤ 4.15 N or O ≤ 10 NH or OH ≤ 5 160 ≤ MW ≤ 480 -0.4 ≤ WLOGP ≤ 5.6 40 ≤ MR ≤ 130 20 ≤ atom ≤ 70 YES;0 violation 2D 386.35 g/mol MW ≤ 500 MLOGP ≤ 4.15 N or O ≤ 10 NH or OH ≤ 5 160 ≤ MW ≤ 480 -0.4 ≤ WLOGP ≤ 5.6 40 ≤ MR ≤ 130 20 ≤ atom ≤ 70 YES ;0 violation 2E 416.38 g/mol MW ≤ 500 MLOGP ≤ 4.15 N or O ≤ 10 NH or OH ≤ 5 160 ≤ MW ≤ 480 -0.4 ≤ WLOGP ≤ 5.6 40 ≤ MR ≤ 130 20 ≤ atom ≤ 70 YES;0 violation Conclusion The antiviral efficacy of compounds 2B, 2C, 2D and 2E was investigated using DFT at the B3LYP/6-311G ++ (d, p) level of theory. Several objectives were applied to these thiophene derivatives, which aided us in exploring their diverse characteristics. Insight into the nature of the stability of the material was revealed through FMO determination, NBO analysis, and spectral analysis. NBO exhibited great transitions and bonding types at higher perturbation energies, such as LP→ LP, σ*→ σ*, and σ*→ σ transitions, whereby 2B was dominated by π*→ π*. Additionally, the FMO analysis revealed energy gap values of 3.758 eV, 3.750 eV, 3.743 eV, and 3.724 eV for 2B, 2C, 2D, and 2E, respectively. Moreover, UV‒Vis analysis also supported these results by revealing large wavelengths (433.49 nm, 347.12 nm, and 333.43 nm for compound 2B; 434.54 nm, 349.11 nm, and 336.12 nm for compound 2C; 435.20 nm, 347.41 nm, and 335.19 nm for compound 2D; and 434.26 nm, 348.53 nm, and 336.07 nm for compound 2E) at different excitation states. The compounds were observed to have dominant symmetric and asymmetric vibrations at their carbonic, amide, and methylated groups via FT-IR. We further investigated the reactivity and nature of the bonding interactions of the compounds via virtual studies. Thus, the NCI revealed a robust van der Waal and steric repulsion within the regions of the methanethioamide scaffold, hydrazineylmethanide scaffold, and 4-bromo-5-(methylthio)-2,3-dihydrothiophen-3-ide scaffold of all the compounds. Moreover, the ELF study showed high localization of electrons at the respective scaffolds, most specifically at the hydrogens, although 2E was pinpointed with a large density of electrons, providing additional reasons for its reactive nature, as also observed in the energy gap and Fermi energy of density of state analysis. Interestingly, the molecular docking approach shows a great affinity between the compounds and the target proteins of human papillomavirus (HPV). The protein‒ligand interactions between the 2B compound and 1R8H and 4GIZ exhibited binding energies of -5.3 kcal/mol and − 5.6 kcal/mol, respectively; the 2C compound demonstrated binding affinities of -5.6 kcal/mol and − 4.8 kcal/mol, respectively; the 2D compound displayed binding affinities of -4.8 kcal/mol and − 5.7 kcal/mol, respectively; and the 2E compound showed binding affinities of -5.2 kcal/mol and − 6.4 kcal/mol, respectively. All the compounds had a robust affinity for 4GIZ, particularly 2E, which exhibited a affinity of -6.4 kcal/mol. Isotretinoin, a conventional drug, showed strong affinities of -8.3 kcal/mol and − 6.6 kcal/mol for 1R8H and 4GIZ, respectively. Ultimately, our study demonstrated that all the studied compounds possess promising drug characteristics, especially antiviral potential, with 2E showing greater activity against HPV. 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Theoretical investigations on molecular structure, NBO, HOMO-LUMO and MEP analysis of two crystal structures of N-(2-benzoyl-phenyl) oxalyl: A DFT study. Journal of Physical & Theoretical Chemistry , 13 (2), 155-169. Glendening, E. D., Landis, C. R., & Weinhold, F. (2019). NBO 7.0: New vistas in localized and delocalized chemical bonding theory. Journal of computational chemistry , 40 (25), 2234-2241. Weinhold, F. (2012). Natural bond orbital analysis: A critical overview of relationships to alternative bonding perspectives. Journal of computational chemistry , 33 (30), 2363-2379. Reed, A. E., Curtiss, L. A., & Weinhold, F. (1988). Intermolecular interactions from a natural bond orbital, donor-acceptor viewpoint. Chemical Reviews , 88 (6), 899-926. Badenhoop, J. K., & Weinhold, F. (1997). Natural bond orbital analysis of steric interactions. The Journal of chemical physics , 107 (14), 5406-5421. Mishra, A. K., & Waldeck, D. H. (2011). Comparison of the Density of States (dos) and Potential Energy Curve (pec) models for the electrochemical rate constant. The Journal of Physical Chemistry C , 115 (42), 20662-20673. Tomfohr, J. K., & Sankey, O. F. (2002). Complex band structure, decay lengths, and Fermi level alignment in simple molecular electronic systems. Physical Review B , 65 (24), 245105. Toriyama, M. Y., Ganose, A. M., Dylla, M., Anand, S., Park, J., Brod, M. K., ... & Snyder, G. J. (2022). How to analyze a density of states. Materials Today, Electronics , 1 , 100002 Hobza, P., & Müller-Dethlefs, K. (2010). Noncovalent interactions: theory and experiment (Vol. 2). Royal Society of Chemistry. Černý, J., & Hobza, P. (2007). Noncovalent interactions in biomacromolecules. Physical Chemistry Chemical Physics , 9 (39), 5291-5303. Mati, I. K., & Cockroft, S. L. (2010). Molecular balances for quantifying noncovalent interactions. Chemical Society Reviews , 39 (11), 4195-4205. Adindu, E. A., Ekpong, B. O., Runde, M., Atotse, A. M., Ojumola, F. O., Gulack, A. O., ... & Louis, H. (2024). Investigating the anti-filarial efficacy and molecular interactions of thiadiazol derivative: Insight from quantum chemical calculations, pharmacokinetics, and molecular docking studies. Chemical Physics Impact , 100459. Poater, J., Duran, M., Sola, M., & Silvi, B. (2005). Theoretical evaluation of electron delocalization in aromatic molecules by means of atoms in molecules (AIM) and electron localization function (ELF) topological approaches. Chemical reviews , 105 (10), 3911-3947. Wagner, J. P., & Schreiner, P. R. (2015). London dispersion in molecular chemistry—reconsidering steric effects. Angewandte Chemie International Edition , 54 (42), 12274-12296. Jakhar, R., Dangi, M., Khichi, A., & Chhillar, A. K. (2020). Relevance of molecular docking studies in drug designing. Current Bioinformatics , 15 (4), 270-278. Gutiérrez, I. S., Lin, F. Y., Vanommeslaeghe, K., Lemkul, J. A., Armacost, K. A., Brooks III, C. L., & MacKerell Jr, A. D. (2016). Parametrization of halogen bonds in the CHARMM general force field: Improved treatment of ligand–protein interactions. Bioorganic & medicinal chemistry , 24 (20), 4812-4825. Kharkar, P. S. (2010). Two-dimensional (2D) in silico models for absorption, distribution, metabolism, excretion and toxicity (ADME/T) in drug discovery. Current Topics in Medicinal Chemistry , 10 (1), 116-126. Alomar, M. J. (2014). Factors affecting the development of adverse drug reactions. Saudi Pharmaceutical Journal , 22 (2), 83-94. Lipinski, C. A. (2016). Rule of five in 2015 and beyond: Target and ligand structural limitations, ligand chemistry structure and drug discovery project decisions. Advanced Drug Delivery Reviews , 101 , 34-41. McGhie, T. K. & Walton, M. C. (2007). The bioavailability and absorption of anthocyanins: toward a better understanding. Molecular Nutrition & Food Research , 51 (6), 702-713. Scheme 1 Scheme 1 is available in the Supplementary Files section. Additional Declarations No competing interests reported. Supplementary Files Scheme1.png Scheme 1: Synthesisof the studied thiophene derivatives (2B, 2C, 2D, and 2E) Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4247398","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":290358483,"identity":"d06fc704-86fc-4ce8-b7ea-c02af2937297","order_by":0,"name":"Michael O. Odey","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA0UlEQVRIiWNgGAWjYJCCgw0MDIwNDMwHQCRJWtgSiNfCCNHCY0CcFt0Z2YkHZ1TYyPZL5HyT+LnDRo6B/fDRDfi0mN3I3XBww5k045kzcrdJ9gIZDDxpaTcIannYdjhxw43cbRK8QEaDBI8ZEVr+HU7cfyPnmeRforVsbADaIpHDJk2cLWfebjg441ia8Ywzz4ytZdvSjNkI+uV47uaPPTXAEGtPfnjzbZuNHD/74WN4tTAIJMAZLBIgmg2vchDgPwBnMH8gqHoUjIJRMApGJAAAncJaCyB0VjsAAAAASUVORK5CYII=","orcid":"","institution":"University of Calabar","correspondingAuthor":true,"prefix":"","firstName":"Michael","middleName":"O.","lastName":"Odey","suffix":""},{"id":290358485,"identity":"7d0044f9-96ba-4df1-9dce-7f8ad4737f30","order_by":1,"name":"Alpha O. Gulack","email":"","orcid":"","institution":"University of Calabar","correspondingAuthor":false,"prefix":"","firstName":"Alpha","middleName":"O.","lastName":"Gulack","suffix":""},{"id":290358488,"identity":"ab77c324-928e-4afd-9dac-b6d52745760a","order_by":2,"name":"Rose O. Ogar","email":"","orcid":"","institution":"University of Calabar","correspondingAuthor":false,"prefix":"","firstName":"Rose","middleName":"O.","lastName":"Ogar","suffix":""},{"id":290358491,"identity":"60fe8e27-7db3-4382-80af-c46ad01fe47e","order_by":3,"name":"Stanley J. Oduma","email":"","orcid":"","institution":"University of Calabar","correspondingAuthor":false,"prefix":"","firstName":"Stanley","middleName":"J.","lastName":"Oduma","suffix":""},{"id":290358493,"identity":"e0f01a75-cac3-4c71-8c70-e9a83bdb42a1","order_by":4,"name":"Diana O. Odey","email":"","orcid":"","institution":"Cross River University of Technology","correspondingAuthor":false,"prefix":"","firstName":"Diana","middleName":"O.","lastName":"Odey","suffix":""},{"id":290358495,"identity":"bf610ee1-b2d7-435c-962d-ba2a409f395e","order_by":5,"name":"Sandra I. Iyen","email":"","orcid":"","institution":"Federal University Wukari","correspondingAuthor":false,"prefix":"","firstName":"Sandra","middleName":"I.","lastName":"Iyen","suffix":""}],"badges":[],"createdAt":"2024-04-10 12:32:50","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4247398/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4247398/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":54763974,"identity":"0db3281a-3c1b-4edb-a47f-167718d71c2c","added_by":"auto","created_at":"2024-04-16 12:13:44","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1820724,"visible":true,"origin":"","legend":"\u003cp\u003e3D molecular structure of the studied compounds and proteins\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-4247398/v1/e7ed3cd405efdacca154a924.png"},{"id":54763976,"identity":"663b989e-9f8c-4cc0-a7a7-ec6ba24e799a","added_by":"auto","created_at":"2024-04-16 12:13:44","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1776402,"visible":true,"origin":"","legend":"\u003cp\u003eGraphical illustration of the HOMO-LUMO iso-surface (yellow‒purple color) for all the studied compounds\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-4247398/v1/7ea7e08c159bf5a341c662f3.png"},{"id":54764318,"identity":"4a47c56b-e9fe-4714-868a-9325e4d5f455","added_by":"auto","created_at":"2024-04-16 12:21:44","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1436505,"visible":true,"origin":"","legend":"\u003cp\u003eDensity of state plots for all the studied compounds\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-4247398/v1/3fc8663103694315d96cbf8f.png"},{"id":54763972,"identity":"20c51e54-f834-4b4c-82f9-00b8e63af1d8","added_by":"auto","created_at":"2024-04-16 12:13:44","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":507923,"visible":true,"origin":"","legend":"\u003cp\u003ePictural representation of the noncovalent interactions of thefour studied compounds\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-4247398/v1/385a007189f9223070173f6c.png"},{"id":54764319,"identity":"07273bfc-b073-48bd-8c72-e7c832e4e228","added_by":"auto","created_at":"2024-04-16 12:21:44","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":287275,"visible":true,"origin":"","legend":"\u003cp\u003eGraphical illustration of the electron localization functions ofthe four distinct compounds\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-4247398/v1/b8b44f6b1f23b68ab1623a29.png"},{"id":54763978,"identity":"af8bc3c9-7561-47cd-ae0d-2d4d6bf8c964","added_by":"auto","created_at":"2024-04-16 12:13:44","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":1194016,"visible":true,"origin":"","legend":"\u003cp\u003eGraphical illustration of molecular docking between the studied ligand and 4GIZ and 1E8H\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-4247398/v1/adc92d93e6d517b64f13e321.png"},{"id":54918959,"identity":"21e1a7f6-45a2-4433-85db-eb4138f5b187","added_by":"auto","created_at":"2024-04-18 14:50:35","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4368136,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4247398/v1/5a3c288a-f859-4b7d-bca6-04cd8f76b1e5.pdf"},{"id":54764317,"identity":"95f68336-af01-451c-be76-9d14059b1a0d","added_by":"auto","created_at":"2024-04-16 12:21:44","extension":"png","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":61091,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eScheme 1\u003c/strong\u003e: Synthesisof the studied thiophene derivatives (2B, 2C, 2D, and 2E)\u003c/p\u003e","description":"","filename":"Scheme1.png","url":"https://assets-eu.researchsquare.com/files/rs-4247398/v1/3d13653e72c98ea3ddbc331f.png"}],"financialInterests":"No competing interests reported.","formattedTitle":"Exploration of the antiviral efficacy of thiophene derivatives targeting human papillomavirus (HPV) and prevention of cancer: A comprehensive computational approach","fulltext":[{"header":"Introduction","content":"\u003cp\u003eHuman papillomavirus (HPV) is a widespread viral infection, often transmitted through sexual contact, affecting millions of individuals globally [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. This diverse group of viruses comprises over 200 distinct types, with some posing minimal health risks, while others have been linked to a range of cancers and genital warts [\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. HPV is transmitted through skin-to-skin contact, primarily during sexual activity [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. However, it can also be transmitted through other forms of close contact, such as kissing or touching infected surfaces [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Engaging in early sexual activity, having multiple sexual partners, or having a weakened immune system significantly increases the likelihood of contracting the virus [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. HPV infections are categorized into two main groups based on their potential to cause cancer (low-risk and high-risk types) [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Low-risk HPV strains such as types six and eleven are responsible for the development of genital warts, which are benign growths that appear on the genital and anal areas. While they can be unsightly and uncomfortable, genital warts do not lead to cancer [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. HPV strains of low-risk are not associated with cancer and tend to cause genital warts instead. On the other hand, high-risk HPV strains, especially types 16 and 18, are strongly linked to the development of cancers in the cervix, anus, penis, vulva, vagina, and oropharynx [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Persistent infection with these high-risk types is the primary risk factor for the development of HPV-related cancers. Prevention of HPV infections primarily revolves around vaccination and practicing safe sex [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Human Papillomavirus (HPV) vaccines, such as Gardasil and Cervarix, are highly effective preventive measures against infection with the most prevalent cancer-causing strains of the virus [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Raising awareness about HPV-promoting vaccination and encouraging safe sexual practices are crucial steps in combating the spread of this widespread and potentially serious infection. However, as a leading cause of preventable cancers, particularly cervical cancer, the significance of HPV extends beyond its association with sexual health to broader public health concerns [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Due to the diverse health risks of human papillomavirus (HPV), researchers have recently been interested in unraveling the complexity of HPV and exploring its molecular biology, transmission, associated health risks, preventive measures, and broader societal impact.\u003c/p\u003e \u003cp\u003eIn recent years, the incorporation of computational approaches in drug design and discovery has significantly enhanced the development of drug formulations. The research conducted by Akash et al. (2023) [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] on novel computational and drug design strategies to inhibit human papillomavirus (HPV)-associated cervical cancer and the DNA polymerase theta receptor using apigenin derivatives is a significant contribution to the field. Their research results emphasized the increased effectiveness of apigenin 4'-O-rhamnoside and apigenin-4'-alpha-L-rhamnoside against the HPV45 oncoprotein E7 (PDB ID 2EWL). Apigenin and apigenin 5-O-beta-D-glucopyranoside also demonstrated significant binding energy against the L1 protein in humans. Besides, the researchers observed a binding affinity range of -7.5 kcal/mol to -8.8 kcal/mol for DNA polymerase theta, indicating the likelihood of apigenin derivatives to inhibit this enzyme (PDB ID 8E23). Aarthi \u003cem\u003eet al.\u003c/em\u003e (2020) [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] explored structural dynamic studies to identify EGCG analogs for inhibiting human papillomavirus E7. They identified small molecules and EGCG as potent inhibitors against the HPV 16 E7 oncoprotein. Furthermore, Aarthy and Singh [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] utilized a computational approach to explore the relationship between protein tyrosine phosphatase and E7 oncoproteins of high- and low-risk HPV. The findings revealed that the LXCXE domain of HPV E7 at both high and low risk adheres to a tumor suppressor protein, and that certain compounds can interfere with the interaction between the oncoprotein and tumor suppressor at the E7\u0026ndash;PTPN14 interface. Akash et al. (2023) conducted an extensive study on natural apigenin derivatives for inhibiting human papillomavirus-associated cervical cancer and DNA polymerase theta receptor through a mechanistic approach. According to their findings, apigenin 4'-O-rhamnoside and apigenin-4'-alpha-L-rhamnoside demonstrated significant efficacy against the HPV45 oncoprotein E7 (PDB ID 2EWL), while apigenin and apigenin 5-O-beta-D-glucopyranoside exhibited notable binding energy against the L1 protein of humans. The study revealed that the inhibitory potential of apigenin derivatives against DNA polymerase theta was significant, with binding affinities ranging from \u0026minus;\u0026thinsp;7.5 kcal/mol to -8.8 kcal/mol (PDB ID 8E23). In a related study, Salaria et al. (2022) also investigated the effects of apigenin derivatives on HPV-associated cervical cancer. However, through an in-silico approach, [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] investigated the potential of traditional Himalayan herbs' phytoconstituents to inhibit human papillomavirus (HPV-18) for the treatment of cervical cancer. The research revealed that among the selected phytoconstituents, eriodictyol-7-glucuronide, stigmasterol, clicoemodin, and thalirugidine demonstrated the most favorable interactions and docking scores of -9.1, -8.7, -8.4, and \u0026minus;\u0026thinsp;8.4 kJ/mol, respectively. Notably, these phytoconstituents exhibit binding affinities that are similar to, or even greater than, those of standard anticancer drugs like imiquimod (-6.1 kJ/mol) and podofilox (-6.9 kJ/mol).\u003c/p\u003e \u003cp\u003eTo date, the quest for effective drug molecules to combat HPV infection has remained elusive. The anticipation of innovative anti-HPV chemotherapies featuring unique modes of action and the identification of potential drugs are of utmost importance. In our research study, we utilized an in-silico approach to evaluate the effectiveness of the study compounds against HPV, with the goal of exploring their anti-HPV potential.\u003c/p\u003e"},{"header":"Method","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003e2.1 Experimental methods\u003c/h2\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n \u003ch2\u003e2.2 DFT method\u003c/h2\u003e\n \u003cp\u003eTheoretical analysis of the study compounds was performed using density functional theory (DFT) calculations. These calculations were carried out at the B3LYP/6-311G ++ (d, p) level of theory to evaluate the properties and behavior of the compounds under investigation. The DFT method, which is widely used in the field of quantum chemistry, employs a mathematical framework to predict the electronic properties and behavior of molecules. The study aimed to provide insights into the molecular structure and properties of the compounds, which would aid in the development of new materials and drugs. This optimization was run by Gaussian 09 software [\u003cspan class=\"CitationRef\"\u003e23\u003c/span\u003e]. The method and basis set of choice were selected based on the atoms of the compounds and aimed to improve the energy minimization calculations. The electronic properties were calculated, and the natural bond orbital (NBO) was automatically calculated by Gaussian software. Likewise, the HOMO-LUMO energies were further converted from atomic units (a.u.) to electron volts (eV), and a graphical illustration of the isosurface, which depicts the electron density, was obtained by Chemcraft v1.8 [\u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e]. Density of state (DOS) analysis was employed to elucidate the electronic behavior graphically, which was carried out utilizing Multiwfn v3.7 and Origin 2018 software [\u003cspan class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e26\u003c/span\u003e]. Furthermore, theoretical spectral analysis was performed with the method and basis set to gain more insight into the behavior of the compounds. The results were virtualized and recorded with the aid of Gaussview v6.0 software [\u003cspan class=\"CitationRef\"\u003e27\u003c/span\u003e]. Conversely, the virtual studies that revealed various natures of interactions and localized regions of electrons were possibly plots with the aid of Multiwfn packages. NCI was obtained through the VMD v1.9.3 application [\u003cspan class=\"CitationRef\"\u003e28\u003c/span\u003e]. Emphatically, the outlined objectives aides in understanding the electronic behavior and possible drug nature of the studied ligands.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\n \u003ch2\u003e2.3 Molecular docking protocol\u003c/h2\u003e\n \u003cp\u003eMolecular docking, an important computational methodology in drug design, facilitates the identification of interactions between ligands and proteins and their binding regions [\u003cspan class=\"CitationRef\"\u003e29\u003c/span\u003e]. This investigation explored the potential therapeutic effects of compounds 2B, 2C, 2D, and 2E against human papillomavirus (HPV). The tagged protein structures coded as 1R8H and 4GIZ were acquired in PDB format from the Research Collaboratory for Structural Bioinformatics (RCSB), an online database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ewww.rcsb.org\u003c/span\u003e\u003c/span\u003e). The selection of the target protein, specifically 1R8H, was based on research conducted by Dell \u003cem\u003eet al.\u003c/em\u003e (2003) [\u003cspan class=\"CitationRef\"\u003e30\u003c/span\u003e], who found that the E2 DBDs of both HPV16 and HPV6 identified a longer version of the consensus E2 binding site, which was determined through research on the BPV1 E2 protein. Conversely, the 4GIZ protein code was reported by Zanier \u003cem\u003eet al.\u003c/em\u003e (2013) [\u003cspan class=\"CitationRef\"\u003e31\u003c/span\u003e], who investigated the structural basis of LxxLL motifs in HPV E6 oncoproteins. Their study underscores the structural basis of both the multifunctionality and oncogenicity of E6 proteins. To explore the biological potential of our compound against HBV, the protein of choice above was used. After the proteins were downloaded, they were further prepared using Biovia Discovery Studio 21 software [\u003cspan class=\"CitationRef\"\u003e32\u003c/span\u003e]. The process included the removal of water molecules and native ligands from the protein structure. The active site within the protein was highlighted with a sphere shape where the xyz coordinates were obtained. Polar hydrogen was added to the protein structure to facilitate the docking process. Additionally, the docking process was carried out using PyRx v0.8 [\u003cspan class=\"CitationRef\"\u003e33\u003c/span\u003e], revealing the binding mode and affinity of the ligand‒protein interaction and graphically illustrating the 2D interaction. In addition, 3D demonstrations of the ligand‒protein interactions were captured using PyMOL v2.4 software [\u003cspan class=\"CitationRef\"\u003e34\u003c/span\u003e].\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Results and Discussion","content":"\u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Geometry optimization\u003c/h2\u003e \u003cp\u003eThe process of geometry optimization is essential in the study of innovative pharmaceutical compounds because it explains their stable behavior and refines and perfects the spatial arrangement of atoms within a molecular structure, which are basic tools in novel drug design [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Thiophene derivatives characteristically adopt a planar structure due to resonance stabilization within their aromatic ring. Thus, this planar structure is facilitated by the overlap of p-orbitals in the carbon and sulfur atoms, akin to benzene [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. However, substitution patterns and steric interference can lead to deviations from perfect planarity, inducing slight distortions or twists in the ring system [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. These deviations are often influenced by factors such as substitution patterns, electronic effects, and intermolecular interactions. Hence, this study was applied to 2B, 2C, 2D, and 2E compounds to identify the most stable configuration of a molecule, directly impacting its behavior and interactions within the compound. The bond lengths and angles of the compounds, including Br\u003csub\u003e25\u003c/sub\u003e-C\u003csub\u003e17\u003c/sub\u003e, S\u003csub\u003e20\u003c/sub\u003e-C\u003csub\u003e19\u003c/sub\u003e, and S\u003csub\u003e29\u003c/sub\u003e-C\u003csub\u003e10,\u003c/sub\u003e which are similar to all the other compounds, and F\u003csub\u003e31\u003c/sub\u003e˗C\u003csub\u003e2\u003c/sub\u003e, Cl\u003csub\u003e32\u003c/sub\u003e˗C\u003csub\u003e2\u003c/sub\u003e, H\u003csub\u003e32\u003c/sub\u003e˗C\u003csub\u003e2\u003c/sub\u003e, and O\u003csub\u003e32\u003c/sub\u003e˗C\u003csub\u003e4,\u003c/sub\u003e which differ among the compounds, were carefully analyzed \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. Most of the bonds around the methanethioamide scaffold, hydrazineylmethanide scaffold, and 4-bromo-5-(methylthio)-2,3-dihydrothiophen-3-ide scaffold of the studied compounds exhibited similar lengths\u0026mdash;1.904 \u0026Aring;, 1.761 \u0026Aring;, and 1.677 \u0026Aring;, respectively\u0026mdash;across all the studied compounds. Moreover, a clear variation at the specific position within the benzene ring of the compounds was recorded. The length of the fluorobenzene of 2B was 1.354 \u0026Aring; at the F\u003csub\u003e31\u003c/sub\u003e˗C\u003csub\u003e2\u003c/sub\u003e label, the length of the chlorobenzene of \u003cb\u003e2C\u003c/b\u003e was 1.756 \u0026Aring; at the Cl\u003csub\u003e32\u003c/sub\u003e˗C\u003csub\u003e2\u003c/sub\u003e label, and the length of the benzene of 2D was 1.083 \u0026Aring; at the H\u003csub\u003e32\u003c/sub\u003e˗C\u003csub\u003e2\u003c/sub\u003e label; the length of the anisoles of 2E was 1.373 \u0026Aring; at the O\u003csub\u003e32\u003c/sub\u003e˗C\u003csub\u003e4\u003c/sub\u003e label. The integration of Cl, F, and OCH\u003csub\u003e3\u003c/sub\u003e greatly influenced the bond length of the compounds, thereby affecting their conformation and stability. Comparatively, the 2D compound with no attachment of foreign atoms to its benzene ring shows slightly greater stability than the other systems. Compound 2C, which contains chlorine, has a longer bond length, implying that it is less stable than other studied thiophene derivatives.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eStructural analysis of the studied thiophene derivatives, revealing bond lengths and angles at various selected labels\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCompound\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBond label\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBond length (\u0026Aring;)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBond label\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBond angle (\u003csup\u003eo\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBr\u003csub\u003e25\u003c/sub\u003e C\u003csub\u003e17\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.904\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eB\u003csub\u003e25\u003c/sub\u003e C\u003csub\u003e17\u003c/sub\u003e C\u003csub\u003e15\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e121.70\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS\u003csub\u003e20\u003c/sub\u003e C\u003csub\u003e19\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.761\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eS\u003csub\u003e20\u003c/sub\u003e C\u003csub\u003e19\u003c/sub\u003e S\u003csub\u003e16\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e120.23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS\u003csub\u003e29\u003c/sub\u003e C\u003csub\u003e10\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.677\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eS\u003csub\u003e29\u003c/sub\u003e C\u003csub\u003e10\u003c/sub\u003e N\u003csub\u003e9\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e125.72\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eF\u003csub\u003e31\u003c/sub\u003e˗C\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.354\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eF\u003csub\u003e31\u003c/sub\u003e C\u003csub\u003e2\u003c/sub\u003e C\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e118.90\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBr\u003csub\u003e25\u003c/sub\u003e C\u003csub\u003e17\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.904\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBr\u003csub\u003e25\u003c/sub\u003e C\u003csub\u003e17\u003c/sub\u003e C\u003csub\u003e15\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e121.70\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS\u003csub\u003e20\u003c/sub\u003e C\u003csub\u003e19\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.761\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eS\u003csub\u003e20\u003c/sub\u003e C\u003csub\u003e19\u003c/sub\u003e S\u003csub\u003e16\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e120.23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS\u003csub\u003e29\u003c/sub\u003e C\u003csub\u003e10\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.677\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eS\u003csub\u003e29\u003c/sub\u003e C\u003csub\u003e10\u003c/sub\u003e N\u003csub\u003e9\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e126.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCl\u003csub\u003e32\u003c/sub\u003e C\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.756\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCl\u003csub\u003e32\u003c/sub\u003e C\u003csub\u003e2\u003c/sub\u003e C\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e119.60\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2D\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBr\u003csub\u003e25\u003c/sub\u003e C\u003csub\u003e17\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.904\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBr\u003csub\u003e25\u003c/sub\u003e C\u003csub\u003e17\u003c/sub\u003e C\u003csub\u003e15\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e121.69\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS\u003csub\u003e20\u003c/sub\u003e C\u003csub\u003e19\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.761\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eS\u003csub\u003e20\u003c/sub\u003e C\u003csub\u003e19\u003c/sub\u003e S\u003csub\u003e16\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e120.26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS\u003csub\u003e29\u003c/sub\u003e C\u003csub\u003e10\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.677\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eS\u003csub\u003e29\u003c/sub\u003e C\u003csub\u003e10\u003c/sub\u003e N\u003csub\u003e9\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e126.22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eH\u003csub\u003e32\u003c/sub\u003e˗C\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.083\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eH\u003csub\u003e32\u003c/sub\u003e C\u003csub\u003e2\u003c/sub\u003e C\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e120.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2E\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBr\u003csub\u003e25\u003c/sub\u003e C\u003csub\u003e17\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.904\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBr\u003csub\u003e25\u003c/sub\u003e C\u003csub\u003e17\u003c/sub\u003e C\u003csub\u003e15\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e121.66\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS\u003csub\u003e20\u003c/sub\u003e C\u003csub\u003e19\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.761\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eS\u003csub\u003e20\u003c/sub\u003e C\u003csub\u003e19\u003c/sub\u003e S\u003csub\u003e16\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e120.28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS\u003csub\u003e29\u003c/sub\u003e C\u003csub\u003e10\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.680\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eS\u003csub\u003e29\u003c/sub\u003e C\u003csub\u003e10\u003c/sub\u003e N\u003csub\u003e9\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e127.92\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eO\u003csub\u003e32\u003c/sub\u003e˗C\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.373\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eC\u003csub\u003e4\u003c/sub\u003e O\u003csub\u003e32\u003c/sub\u003e C\u003csub\u003e33\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e118.95\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Spectroscopy\u003c/h2\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003e3.2.1 FT-IR analysis\u003c/h2\u003e \u003cp\u003eFourier transform infrared spectroscopy (FT-IR) analysis involves the measurement of the absorption or emission of infrared light by molecular bonds within a sample, providing detailed information about its chemical composition and structure [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. When applied to biological compounds, it enables the identification of functional groups and secondary structures, including α-helices, β-sheets, and random coils. Hence, analyzing the characteristic absorption peaks in the infrared spectrum can infer the presence of specific chemical bonds and provide insights into the conformational changes or structural rearrangements induced by light absorption. We employed this technique theoretically in our investigated compounds to offer valuable information about the compounds' stability, hydration dynamics, and structural alterations. The reported literature states that each type of bond within a molecule absorbs infrared radiation at characteristic wavelengths, resulting in unique spectral features that can be used for identification and structural analysis [\u003cspan additionalcitationids=\"CR41\" citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. From our results, as shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, diverse vibrational modes were observed at the respective wavelengths due to light absorption by the compounds. Respective functional groups were identified in the 2B, 2C, 2D, and 2E compounds, and these groups included NH (amine group), CH and CH3 (methyl group), and C\u0026thinsp;=\u0026thinsp;C (alkane group). Strong absorption bands in the fingerprint region of the spectrum were observed for the amine group, with notable symmetric stretching across all the studied compounds; thus, low absorption was observed upon rocking vibration. This is suggested to contribute to the stability characteristics of the compounds. Similarly, at high frequencies, symmetric and asymmetric vibrations of methyl groups at the benzene and thiophene rings were observed across all the compounds, indicating an additional stable conformation. Likewise, a strong absorption of light by the C\u0026thinsp;=\u0026thinsp;C group situated at the benzene ring was recorded along with symmetric vibrations. The presence of these groups with symmetric and asymmetric vibrations indicates the strong stability of the compounds despite the rocking and scissoring stretching observed at other frequencies. However, the frequencies of the identified groups range from 3576 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e to 1404 cm\u003csup\u003e\u0026minus;\u0026thinsp;1,\u003c/sup\u003e which agrees with the reported literature [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Therefore, this technique facilitates the elucidation of molecular structures, dynamics, and interactions, thereby advancing our understanding of biological systems and informing the development of novel therapeutic interventions and biomaterials.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFT-IR analysis results for the studied complexes\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCompound\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eExperimental value (CM\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTheoretical value (CM\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAssignment\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2B\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSymmetric stretching 3324, 3220, 3117, 1640, 1262\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3576, 3564, 3283\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSymmetric stretching NH\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3220, 3204\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSymmetric stretching CH\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3200, 3172\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAsymmetric stretching CH\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3172, 3135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAsymmetric stretching CH3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3047\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003esymmetric stretching CH3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1648, 1642, 1515,\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003esymmetric stretching C\u0026thinsp;=\u0026thinsp;C\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1585, 1551, 1473, 1371\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRocking stretching NH\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1551,\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRocking stretching CH\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1481, 1464\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eScissoring stretching CH3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2C\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSymmetric stretching 3330, 3224, 3109, 1647, 1255\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3576, 3285,\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSymmetric stretching NH\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3564,\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAsymmetric stretching NH\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3223, 3204, 3203\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSymmetric stretching CH\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3199, 3167\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAsymmetric stretching CH\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3144, 3135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAsymmetric stretching CH3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3047\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSymmetric stretching CH3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1635, 1515\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSymmetric stretching C\u0026thinsp;=\u0026thinsp;C\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1627, 1584, 1550, 1472\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRocking stretching NH\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1523\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRocking stretching CH\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1481\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eScissoring stretching CH3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2D\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSymmetric stretching 3328, 3225, 3111, 1641, 1257\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3574, 3280\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSymmetric stretching NH\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3564\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAsymmetric stretching NH\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3221, 3180, 3171, 3159, 3144, 3135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAsymmetric stretching CH\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3204, 3193, 3047\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSymmetric stretching CH\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1641, 1635, 1515\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSymmetric stretching C\u0026thinsp;=\u0026thinsp;C\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1585, 1557\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRocking stretching NH\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1527, 1478\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRocking stretching CH\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1481\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eScissoring stretching CH3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2E\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSymmetric stretching 3330, 3224, 3119, 1651, 1264\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3559, 3280\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSymmetric stretching NH\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3537,\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAsymmetric stretching NH\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3239, 3207, 3206\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSymmetric stretching CH\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3190, 3174\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAsymmetric stretching CH\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3143, 3139, 3135, 3080\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAsymmetric stretching CH3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3047, 3016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSymmetric stretching CH3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1649, 1590, 1585, 1475, 1385, 1368, 1360\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRocking stretching NH\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1637, 1515, 1404\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSymmetric stretching C\u0026thinsp;=\u0026thinsp;C\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1521, 1515, 1491, 1481, 1469, 1464\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eScissoring stretching CH3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1493\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRocking stretching CH\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003e3.2.3 UV‒vis analysis\u003c/h2\u003e \u003cp\u003eUV‒Vis spectroscopy analysis exploits the absorption of light in the ultraviolet and visible regions of the electromagnetic spectrum by molecules containing conjugated π-electron systems. The absorption of light occurs due to the excitation of electrons from ground-state molecular orbitals to higher energy excited states [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. The absorption spectrum obtained provides information about the electronic transitions within the molecule, including π-π* transitions in aromatic rings and n-π* transitions in conjugated compounds, as more of these characteristics were observed in our investigation through natural bond orbital studies [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. This technique is also useful for studying the structure and function of biological molecules because it can offer insight into their secondary structure, folding, and stability. Our analysis results \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e of the studied compounds suggest that electronic transitions occur in the molecules upon absorption of light. The ground state refers to the lowest energy state of the molecule, while the excited states represent higher energy states attained upon absorption of photons. The excitation energies of the different compounds were compared: compound 2B: ground state (2.8601 eV), first excited state (3.5718 eV), and second excited state (3.7185 eV); compound 2C: ground state (2.8532 eV), first excited state (3.5514 eV), and second excited state (3.6887 eV); compound 2D: ground state (2.8489 eV), first excited state (3.5688 eV), and second excited state (3.6989 eV); and compound 2E: ground state (2.8551 eV), first excited state (3.5574 eV), and second excited state (3.6893 eV). From these results, it can be observed that all compounds undergo electronic transitions to higher energy states upon absorption of light. The differences in excitation energies between the ground and excited states reflect the energy required to promote electrons to higher orbitals. To assess the stability and reactivity of compounds based on these results, several factors need to be considered. Therefore, compounds with lower excitation energies may exhibit greater stability because less energy is required for excitation. Conversely, compounds with higher excitation energies may be more reactive, as they have higher energy levels available for participating in chemical reactions. This knowledge is supported by the higher wavelengths observed across each energy level of our studied compounds. Additionally, reports suggest that compounds with low energy levels tend to exhibit higher wavelengths [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Thus, comparing the provided data, compound 2C has the lowest excitation energies among the compounds, potentially indicating greater stability. Conversely, compound 2B has the highest excitation energy, suggesting that it might be more reactive. This finding supported the results revealed in the structural studies and frontier molecular orbital analysis, thereby providing more evidence of the reactivity and stability characteristics of the study compounds.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eUV‒Vis results for all the studied thiophene derivatives optimized at the B3LYP/6-311G ++ (d, p) level of theory\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSystem\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTransition Type\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEnergy (eV)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWavelength (nm)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eOscillator strength (\u003cem\u003ef\u003c/em\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePercentage contribution (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eTransition\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS\u003csub\u003e0\u003c/sub\u003e-S\u003csub\u003e1\u003c/sub\u003e(101 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\to\\)\u003c/span\u003e\u003c/span\u003e102)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.8601\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e433.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0521\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.66466\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eH \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\to\\)\u003c/span\u003e\u003c/span\u003e L\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS\u003csub\u003e0\u003c/sub\u003e-S\u003csub\u003e2\u003c/sub\u003e (100 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\to\\)\u003c/span\u003e\u003c/span\u003e102)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.5718\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e347.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.3951\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.65256\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eH \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\to\\)\u003c/span\u003e\u003c/span\u003e L\u0026thinsp;+\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS\u003csub\u003e0\u003c/sub\u003e-S\u003csub\u003e3\u003c/sub\u003e (98 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\to\\)\u003c/span\u003e\u003c/span\u003e102)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.7185\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e333.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.55956\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eH \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\to\\)\u003c/span\u003e\u003c/span\u003e L\u0026thinsp;+\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS\u003csub\u003e0\u003c/sub\u003e-S\u003csub\u003e1\u003c/sub\u003e(105 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\to\\)\u003c/span\u003e\u003c/span\u003e106)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.8532\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e434.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0548\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.66258\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eH \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\to\\)\u003c/span\u003e\u003c/span\u003e L\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS\u003csub\u003e0\u003c/sub\u003e-S\u003csub\u003e2\u003c/sub\u003e (104 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\to\\)\u003c/span\u003e\u003c/span\u003e106)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.5514\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e349.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.4486\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.64502\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eH \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\to\\)\u003c/span\u003e\u003c/span\u003e L\u0026thinsp;+\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS\u003csub\u003e0\u003c/sub\u003e-S\u003csub\u003e3\u003c/sub\u003e (102 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\to\\)\u003c/span\u003e\u003c/span\u003e106)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.6887\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e336.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.50153\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eH \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\to\\)\u003c/span\u003e\u003c/span\u003e L\u0026thinsp;+\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2D\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS\u003csub\u003e0\u003c/sub\u003e-S\u003csub\u003e1\u003c/sub\u003e (97 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\to\\)\u003c/span\u003e\u003c/span\u003e98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.8489\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e435.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0532\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.66797\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eH \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\to\\)\u003c/span\u003e\u003c/span\u003e L\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS\u003csub\u003e0\u003c/sub\u003e-S\u003csub\u003e2\u003c/sub\u003e (96 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\to\\)\u003c/span\u003e\u003c/span\u003e98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.5688\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e347.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.4078\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.65138\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eH \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\to\\)\u003c/span\u003e\u003c/span\u003e L\u0026thinsp;+\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS\u003csub\u003e0\u003c/sub\u003e-S\u003csub\u003e3\u003c/sub\u003e (94 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\to\\)\u003c/span\u003e\u003c/span\u003e98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.6989\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e335.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0046\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.54718\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eH \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\to\\)\u003c/span\u003e\u003c/span\u003e L\u0026thinsp;+\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2E\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS\u003csub\u003e0\u003c/sub\u003e-S\u003csub\u003e1\u003c/sub\u003e (105 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\to\\)\u003c/span\u003e\u003c/span\u003e106)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.8551\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e434.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0691\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.65726\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eH \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\to\\)\u003c/span\u003e\u003c/span\u003e L\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS\u003csub\u003e0\u003c/sub\u003e-S\u003csub\u003e2\u003c/sub\u003e (104 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\to\\)\u003c/span\u003e\u003c/span\u003e106)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.5574\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e348.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.6108\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.58147\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eH \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\to\\)\u003c/span\u003e\u003c/span\u003e L\u0026thinsp;+\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS\u003csub\u003e0\u003c/sub\u003e-S\u003csub\u003e3\u003c/sub\u003e (103 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\to\\)\u003c/span\u003e\u003c/span\u003e106)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.6893\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e336.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0089\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.57503\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eH \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\to\\)\u003c/span\u003e\u003c/span\u003e L\u0026thinsp;+\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Electronic properties\u003c/h2\u003e \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e \u003ch2\u003e3.3.1 Frontier molecular orbital analysis\u003c/h2\u003e \u003cp\u003eFrontier molecular orbital analysis elucidates the mechanisms involved in the transfer of charges from the filled orbital to the unfilled orbital. The application of the highest occupied molecular orbital and lowest unoccupied molecular orbital (HOMO-LUMO) analysis has provided valuable insights into the electronic structure and reactivity of molecules and provided insight into their potential interactions with other compounds [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. The analyzed HOMO and LUMO energies, as presented in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, were further used to calculate parameters such as the energy gap, ionization potential (IP), electron affinity (EA), chemical softness and hardness (σ and η), chemical potential (\u0026micro;), electrophilicity index (ω) and Fermi energy level (EFL) [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. The energy gap (\u003cem\u003eE\u003c/em\u003e\u003csub\u003e\u003cem\u003eg\u003c/em\u003e\u003c/sub\u003e), defined as the range within a solid where no electron states are present [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e], was calculated using the following equation:\u003c/p\u003e \u003cp\u003e \u003cem\u003eE\u003c/em\u003e \u003csub\u003e \u003cem\u003eg\u003c/em\u003e \u003c/sub\u003e \u003cem\u003e= E\u003c/em\u003e \u003csub\u003e \u003cem\u003eLUMO\u003c/em\u003e \u003c/sub\u003e \u003cem\u003e- E\u003c/em\u003e\u003csub\u003e\u003cem\u003eHOMO\u003c/em\u003e\u003c/sub\u003e\u003c/p\u003e \u003cp\u003ewhere \u003cem\u003eE\u003c/em\u003e\u003csub\u003e\u003cem\u003eg\u003c/em\u003e\u003c/sub\u003e represents the energy gap, \u003cem\u003eE\u003c/em\u003e\u003csub\u003e\u003cem\u003eLUMO\u003c/em\u003e\u003c/sub\u003e represents the energy of the LUMO and \u003cem\u003eE\u003c/em\u003e\u003csub\u003e\u003cem\u003eHOMO\u003c/em\u003e\u003c/sub\u003e represents the energy of the HOMO. The obtained results exhibit varying energy gaps in the following trend: 3.758 eV\u0026thinsp;\u0026gt;\u0026thinsp;3.750 eV\u0026thinsp;\u0026gt;\u0026thinsp;3.743 eV\u0026thinsp;\u0026gt;\u0026thinsp;3.724 eV for 2B, 2C, 2D, and 2E \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. This result signifies that the 2B compound possesses a higher energy gap of 3.758 eV, indicating that a greater amount of energy is required to move an electron from the occupied orbital to the uncopied orbital, thus making it less reactive than the other compounds. Conversely, the 2E compound exhibits the lowest energy gap, suggesting that less energy is needed to move an electron from the occupied orbital to the uncopied orbital, thereby indicating that it is the most reactive compound among those under study [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. The ionization potential reflects the ability of a compound to undergo chemical reactions involving ion formation or electron donation. The calculated values presented in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e suggest that the 2C compound demonstrates a higher ionization potential (IP) at 6.120 eV because of its stability, and a high ionization potential indicates low susceptibility to certain chemical reactions involving electron transfer. In the context of drug design, this characteristic may contribute to the stability of drug atoms, ensuring their structural integrity during storage and transportation. Conversely, the 2E compound exhibits a lower ionization potential of 5.926 eV, signifying the ease of electron loss. Additionally, the investigation of chemical potential, chemical hardness, and chemical softness provided insights into the polarity of these compounds. Chemical hardness indicates how molecules are polarizable and the distortion of the electron cloud in an electric field. The chemical hardness was found to be higher in 2B, with a hardness value of 1.879 eV, and lower in the 2E compound. Higher chemical softness indicates a lower degree of polarizability and low distortion of the electron cloud in response to an electric field. Hence, the chemical softness aligns with the trend in chemical hardness. However, it is clear that 2E is likely to be a highly reactive thiophene, while 2E is less reactive than the other studied thiophene derivatives. This finding is comprehensively supported by the results highlighted in the geometry optimization study.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eHOMO-LUMO and quantum descriptor results for all the studied compounds\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCompound\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHOMO-eV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLUMO-eV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEnergy gap (eV)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eEA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eσ\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eη\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026micro;\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eω\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eEFL\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2B\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-6.089\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-2.331\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.758\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6.089\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-2.331\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.266\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.879\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e-4.210\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e4.716\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e4.210\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2C\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-6.120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-2.370\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.750\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6.120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.370\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.267\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.875\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e-4.245\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e4.804\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e4.245\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2D\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-6.021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-2.278\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.743\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6.021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.278\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.267\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.872\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e-4.149\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e4.600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e4.149\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2E\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-5.926\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-2.201\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.724\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5.926\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.201\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.268\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.862\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e-4.064\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e4.434\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e4.064\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section3\"\u003e \u003ch2\u003e3.3.2 Natural Bond Orbital (NBO) Analysis\u003c/h2\u003e \u003cp\u003eThe utilization of natural bond orbital (NBO) analysis can allow for the examination of both intermolecular and intramolecular interactions between donor and acceptor orbitals [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. This study provides insights into the extent of charge transfer from the valence band to the conduction band. Regarding the Schr\u0026ouml;dinger equation, the NBO method enhances our understanding of chemical bonding concepts [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. Therefore, to ascertain the degree of conjugation within our studied compounds, second-order perturbation theory analysis was employed, as documented in the literature [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. This knowledge is critical in the novelty of the drug; hence, the magnitude of the perturbation energy E\u003csup\u003e2\u003c/sup\u003e correlates with the strength of interaction between the donor and acceptor, thereby enabling us to predict the stability of these compounds [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. However, E\u003csup\u003e2,\u003c/sup\u003e also known as the stabilization energy, signifies electron delocalization between occupied and unoccupied orbitals, illustrating a stable donor-acceptor relationship. The calculation of the perturbation energy E\u003csup\u003e2\u003c/sup\u003e involves the use of \u003cb\u003eEq.\u0026nbsp;1\u003c/b\u003e.\u003c/p\u003e \u003cp\u003eE\u003csup\u003e2\u003c/sup\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(=qi\\frac{\\left(Fij\\right){)}^{2}}{E\\left(i\\right)-E\\left(j\\right)}\\)\u003c/span\u003e\u003c/span\u003e \u003cb\u003e(1)\u003c/b\u003e\u003c/p\u003e \u003cp\u003ewhere E\u003csup\u003e2\u003c/sup\u003e represents the perturbation energy of the second order, Fij signifies the off-diagonal elements on the folk matrix, and E(j) - E(i) denotes the diagonal elements. Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e displays the computed values of the donor-acceptor interactions derived from the higher perturbation energy among the examined compounds. The identified\u003c/p\u003e \u003cp\u003eInteractions include double anti-bonding to double anti-bonding (π*\u0026rarr; π*), lone pair to single anti-bonding (LP\u0026rarr; σ*), single anti-bonding to single anti-bonding (σ*\u0026rarr; σ*), and lone pair to lone pair (LP\u0026rarr; LP) interactions, with a predominant occurrence of σ*\u0026rarr; σ* on 2C, 2D, and 2E compounds. These interactions were chosen based on their significant contributions to the charge transfer process observed for various charge transitions from the donor to acceptor orbital. The NBO results revealed a 2B compound with electron delocalization between πC5\u0026rarr; πC6 and πC4\u0026rarr; π*C5 and the highest perturbation energy of 121.13 kcal/mol, suggesting a strong interaction that underlines the robust stability of the compound, as described earlier in frontier molecular studies and other quantum descriptor analyses. Hence, 2B was more stable than the other thiophene compounds because of its large perturbation energy and double bond transition between the donor and acceptor (π*\u0026rarr; π*). In contrast, the 2E compound displayed lower perturbation energy (E2) at most of its door-acceptor orbitals and a simple transition of charges within a bonding from LP\u0026rarr; LP, σ*\u0026rarr; σ*, and σ*\u0026rarr; σ transition, contributing to the easy flow of electrons from the donor to acceptor.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSecond-Order Perturbation Theory Analysis of the Fock Matrix in the NBO Basis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCompound\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTransition\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDonor NBO (i)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAcceptor (j)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eE(2) (Kcal/mol)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eE(j)-E(i) (a.u)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eF(ij) (a.u)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2B\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eπ*\u0026rarr; π*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eπ*C\u003csub\u003e5\u003c/sub\u003e\u0026rarr; π*C\u003csub\u003e6\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eπ*C\u003csub\u003e4\u003c/sub\u003e\u0026rarr; π*C\u003csub\u003e5\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e121.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.065\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eπ*\u0026rarr; π*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eπ*C\u003csub\u003e17\u003c/sub\u003e\u0026rarr; π*C\u003csub\u003e19\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eπ*C\u003csub\u003e14\u003c/sub\u003e\u0026rarr; π*C\u003csub\u003e15\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e60.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.058\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLP\u0026rarr; σ*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLP S\u003csub\u003e29\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eσ*C\u003csub\u003e4\u003c/sub\u003e\u0026rarr;LP H\u003csub\u003e30\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e76.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.169\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2C\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eσ*\u0026rarr; σ*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eσ*C\u003csub\u003e5\u003c/sub\u003e\u0026rarr; σ*C\u003csub\u003e6\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eσ*C\u003csub\u003e3\u003c/sub\u003e\u0026rarr; σ*C\u003csub\u003e4\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e93.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.065\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eσ*\u0026rarr; σ*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eσ*C\u003csub\u003e1\u003c/sub\u003e\u0026rarr; σ*C\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eσ*C\u003csub\u003e3\u003c/sub\u003e\u0026rarr; σ*C\u003csub\u003e4\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e75.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.063\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eσ*\u0026rarr; σ*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eσ*C\u003csub\u003e17\u003c/sub\u003e\u0026rarr; σ*C\u003csub\u003e19\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eσ*C\u003csub\u003e14\u003c/sub\u003e\u0026rarr; σ*C\u003csub\u003e15\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e60.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.058\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2D\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eσ*\u0026rarr; σ*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eσ*C\u003csub\u003e5\u003c/sub\u003e\u0026rarr; σ*C\u003csub\u003e6\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eσ*C\u003csub\u003e1\u003c/sub\u003e\u0026rarr; π*C\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e96.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.063\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eσ*\u0026rarr; σ*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eσ*C\u003csub\u003e5\u003c/sub\u003e\u0026rarr; σ*C\u003csub\u003e6\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eσ*C\u003csub\u003e3\u003c/sub\u003e\u0026rarr; π*C\u003csub\u003e4\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e85.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.065\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eσ*\u0026rarr; σ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eσ*C\u003csub\u003e17\u003c/sub\u003e\u0026rarr; σ*C\u003csub\u003e19\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eσC\u003csub\u003e14\u003c/sub\u003e\u0026rarr;σC\u003csub\u003e15\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e59.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.058\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2E\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLP\u0026rarr; LP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLP S\u003csub\u003e29\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLP C\u003csub\u003e10\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e79.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.116\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eσ*\u0026rarr; σ*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eσ*C\u003csub\u003e3\u003c/sub\u003e\u0026rarr; σ*C\u003csub\u003e4\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eσ*C\u003csub\u003e5\u003c/sub\u003e\u0026rarr; π*C\u003csub\u003e6\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e50.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.063\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eσ*\u0026rarr; σ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eσ*C\u003csub\u003e17\u003c/sub\u003e\u0026rarr; σ*C\u003csub\u003e19\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eσC\u003csub\u003e14\u003c/sub\u003e\u0026rarr; σ*C\u003csub\u003e15\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e48.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.058\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section3\"\u003e \u003ch2\u003e3.3.3 Density of state analysis\u003c/h2\u003e \u003cp\u003eThe study of density of states involves analyzing the complete density of states (TDOS), partial density of states (PDOS), and overlap partial density of states (OPDOS). This study is illustrated in plots to make predictions about the contributions of molecular orbitals. In the field of drug design, DOS analysis was conducted to gain significant insights into the fragments responsible for the redistribution of electrons in a compound, thereby pioneering the compounds\u0026rsquo; reactivity and stability characteristics [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. The electron occurrence patterns of the highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) were clarified by this analysis. It also provided an accurate count of the state available for the study compounds to occupy at different energy intervals [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. From the results plotted, the left side, as divided by the dotted line, represents the bonding molecular orbitals, whereas the antibonding molecular orbitals are illustrated on the right side. In the graphical representation of the compounds, the energy of the bonded atoms is considered based on their contributions to the molecular orbitals [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e reveals that the four different compounds (2B, 2C, 2D, and 2E) exhibit similar distributions of electrons due to their similar properties. In all the compounds, the carbon atom exhibits the highest peak, suggesting its significant contribution to the compound's reactivity. Hence, the trends are observed in the following order: carbon\u0026thinsp;\u0026gt;\u0026thinsp;hydrogen\u0026thinsp;\u0026gt;\u0026thinsp;nitrogen\u0026thinsp;\u0026gt;\u0026thinsp;bromine for all the compounds except 2D, which replaced Br with sulfur. The fragments with the least distribution of charges are the atoms that provided the unique variations in the compound (fluorine in 2C, chlorine in 2B, bromine in 2D, and oxygen in 2E). Additionally, the 2E compound exhibited a slightly low Fermi energy level (0.149 a.u.), indicating the easy distribution of charges of atoms from the conduction band into the valence band, resulting in increased reactivity. Conversely, the 2C and 2D compounds had the highest Fermi energy levels (0.156 a.u.), indicating that they were slightly less reactive than the 2B and 2E compounds.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Visual studies\u003c/h2\u003e \u003cdiv id=\"Sec16\" class=\"Section3\"\u003e \u003ch2\u003e3.4.1 Noncovalent interaction (NCI) analysis\u003c/h2\u003e \u003cp\u003eNoncovalent interactions characterized by their weak nature and absence of chemical reactions are often referred to as nonbonded interactions [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. There are three distinct types of noncovalent interactions (hydrogen bonds, van der Waals interactions, and electrostatic interactions), with van der Waals interactions being the most prevalent and known to involve close-distance interactions [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. These short-range interactions occur whenever atoms or molecules closely approach each other, thereby involving atoms within distances comparable to their sizes [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]. Hydrogen bonds, situated at the interface between chemical bonds and noncovalent interactions, form between pairs of atoms when one acts as a proton donor and the other acts as a proton acceptor. In contrast, electrostatic interactions represent the third category of noncovalent interactions, distinguished by their long-range nature. The electrostatic interactions extend beyond the confines of the closest atoms, making their description more complex. This study is vital in drug design because it provides a comprehensive understanding of the various natures of the interactions of compounds. However, the various interactions are represented by different colors; van der Waals interactions are denoted by green, hydrogen interactions are denoted by blue, and electrostatic interactions, also known as steric repulsion, are denoted by red [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e], as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. This result illustrates the dominance of the green iso-surfaces in all the studied compounds. Close observation revealed that the green color was dominant at the outside regions of the methanethioamide scaffold, hydrazineylmethanide scaffold, and 4-bromo-5-(methylthio)-2,3-dihydrothiophen-3-ide scaffold, indicating good characteristics of the drug. Additionally, steric repulsion forces were highlighted at the intramolecular region of the methane-thioamide scaffold and benzene ring of the compounds, whereas no hydrogen bonds were present across the compounds. The nature of the interactions observed suggested that the studied compounds could be promising candidates for the development of novel drugs.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section3\"\u003e \u003ch2\u003e3.4.2 Electron Localization Function (ELF) Analysis\u003c/h2\u003e \u003cp\u003eAn electron localization function (ELF) investigation quantifies the probability of locating an electron within the locality of a position electron situated at a specific point with the same spin [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]. The ELF revealed the degree of spatial confinement of the reference electron, offering a means to map the probability distribution of electron pairs in a biological compound. One of the crucial aspects of developing a novel drug is gaining wide knowledge of the compound; hence, this study revealed important regions that are electron-rich, providing an advantage for interference with another biological system [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]. Interestingly, the results of this analysis illustrate the spatial distribution of electrons within the molecule through distinct colorations in various regions. The red areas signify high electron localization values, which indicate electron density, thus highlighting the active site and likely binding with another compound. The yellow areas denote moderate ELF values, representing less pronounced electron localization. In contrast, the blue regions indicate extremely low ELF regions, suggesting weak electron localization and extensive electron delocalization. Figure\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e shows that all the studied compounds exhibit electron localization at most of the scaffolds. However, the 2E compound displayed more electron localization at the 4-bromo-5-(methylthio)-2,3-dihydrothiophen-3-ide scaffold and benzene ring regions even at its unique OCH\u003csub\u003e3\u003c/sub\u003e, which made it exempt from other compounds. This implies that the 2E compound would likely react with another compound, thus supporting its reactivity, as pointed out in the HOMO-LUMO investigation. Additionally, the spatial distributions of the electron density and charge within compounds 2B, 2C, 2D, and 2E predict the potential properties of the compounds, such as their ability to interact with biological targets, indicating their potential as drugs.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e3.5 Molecular Docking Analysis\u003c/h2\u003e \u003cp\u003eThis method plays an essential role in evaluating the chemical interactions between a ligand and disease-related proteins or receptors [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e]. However, by predicting the active site of a protein to which the ligand binds, this analysis provides insights into the interaction strength and type, thus providing valuable information on the ligand's activity and mechanism against the disease [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]. In this context, our investigation investigated the biological activity and compatibility of four distinct compounds, labeled 2B, 2C, 2D, and 2E, against human papillomavirus. We conducted a comparison between the structures and DNA binding properties of E2 proteins obtained from oncogenic and nononcogenic human papillomaviruses (1R8H). Furthermore, we analyzed the crystal structure of the complete human papillomavirus oncoprotein E6 in complex with the LXXLL peptide of the ubiquitin ligase E6AP at a resolution of 2.55 \u0026Aring; (4GIZ). Vital parameters such as binding affinity, bond distance, and hydrogen bond interactions were ascertained and are presented in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. Furthermore, the docking results are graphically illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e. Upon evaluation of the results, the protein‒ligand interactions between compound 2B and 1R8H and 4GIZ exhibited binding energies of -5.3 kcal/mol and \u0026minus;\u0026thinsp;5.6 kcal/mol, corresponding to 4 and 3 conventional hydrogen bonds, respectively. The 2C compound demonstrated binding affinities of -5.6 kcal/mol and \u0026minus;\u0026thinsp;4.8 kcal/mol with 3 and 2 conventional hydrogen bonds, respectively, while the 2D compound displayed binding affinities of -4.8 kcal/mol and \u0026minus;\u0026thinsp;5.7 kcal/mol with 2 and 3 conventional hydrogen bonds, respectively. Similarly, 2E had binding affinities of -5.2 kcal/mol and \u0026minus;\u0026thinsp;6.4 kcal/mol, respectively, with 3 hydrogen bonds. Notably, our findings indicate that the ligand‒protein interaction between the 2E compound and 4GIZ has the highest binding affinity of -6.4 kcal/mol, with three hydrogen bond interactions: D: GLN35:OE1, D: GLN35:OE1, and D: GLN35:OE1. This suggests its high efficacy against human papillomavirus. Although the studied thiophene derivative compounds show great binding affinity for 1R8H and 4GIZ, they exhibit strong negative values and short distances, as shown in the table. However, isotretinoin, a conventional drug, showed strong affinities of -8.3 kcal/mol and \u0026minus;\u0026thinsp;6.6 kcal/mol for 1R8H and 4GIZ, respectively, indicating that it has a greater affinity than the other studied compounds. However, it was notable that the 2E compound also displayed strong interaction behavior following a binding affinity \u0026lt; -5, which is indicative of strong binding. Therefore, it can be deduced that the study compounds show a good ability to inhibit the action of the selected protein, which is vital for the survival of HPV. This finding also implies that the studied compounds possess the potential to be considered novel antiviral agents, especially human papillomavirus.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe binding affinity and animal residue results for the interaction between the studied compounds, conventional drug, and selected protein of HPV\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCompound\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBest pose binding Affinity (kcal/mol)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAmino acid residue\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBond distance (\u0026Aring;)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2B-1R8H\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-5.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eA: THR316: O\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.2159\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eB: THR316: O\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.5773\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eA: SER315: OG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.6591\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eB: THR316: O\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.0308\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2B-4GIZ\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-5.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eC: LYS72:HZ2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.9798\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eD: GLN35:OE1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.2671\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eD: GLU41:OE2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.2499\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2C-1R8H\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-5.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eA: THR316: O\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.1944\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eB: THR316: O\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.1303\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eA: SER315: OG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.7491\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2C-4GIZ\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-5.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eD: GLN35: OE1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.3445\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eD: GLU41: OE2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.0839\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2D-1R8H\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-4.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eB: HIS318: HD1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.9887\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eB: LYS327: O\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.1144\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2D-4GIZ\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-5.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eD: GLU41: OE2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.9860\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eD: GLN35: OE1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.2542\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eD: CYS63: SG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.8373\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2E-1R8H\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-5.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eB: THR316: O\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.9059\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eA: SER315: OG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.7654\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eB: THR316: O\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.9302\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2E-4GIZ\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-6.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eD: GLN35: OE1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.5940\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eD: GLN35: OE1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.3511\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eD: GLN35: OE1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.7216\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIsotretinoin\u0026thinsp;+\u0026thinsp;1R8H\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-8.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eD: PO4501\u003c/p\u003e \u003cp\u003eC: ARG300\u003c/p\u003e \u003cp\u003eC: ASN304\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003cp\u003e-\u003c/p\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIsotretinoin\u0026thinsp;+\u0026thinsp;4GIZ\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-6.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eB: ARG67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e3.6 Pharmacokinetic\u003c/h2\u003e \u003cp\u003ePharmacokinetics entails the action and disposition of a drug on the body system through the determination of absorption, distribution, metabolism, elimination, and toxicity [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e]. Herein, the toxicity and drug likeness of the studied compounds were predicted to further elucidate their adverse effects and drug-like nature. This is crucial in drug development, as drugs with more adverse effects can hinder or damage the human body. However, this analysis was carried out using two online databases, protox II (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://tox-new.charite.de/\u003c/span\u003e\u003cspan address=\"https://tox-new.charite.de/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and swissADME (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.swissadme.ch/\u003c/span\u003e\u003cspan address=\"http://www.swissadme.ch/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Protox II was used to determine the toxicity of the compounds, while the drug likeness was determined using swissADME. Accurate prediction of toxicity and drug likeness can help save resources and time by ensuring that only compounds with desirable characteristics are used for drug development.\u003c/p\u003e \u003cdiv id=\"Sec20\" class=\"Section3\"\u003e \u003ch2\u003e3.6.1 Toxicity\u003c/h2\u003e \u003cp\u003eToxicity denotes the extent of harm that a substance can inflict on an organism following administration. The toxic effects of drugs are contingent upon the dosage administered. These effects can range from mild, targeting specific organs, to severe, impacting the entire biological system [\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e]. The liver is an important organ in the human body responsible for the elimination and metabolism of drugs, and hepatotoxicity provides information about the ability of a drug to cause damage or impairment to the liver. The results from Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e indicate active hepatotoxicity at a probability of 0.69 for all the studied compounds. However, carcinogenicity, which refers to the ability of substances to cause cancer or promote the development of cancerous cells in living organisms, was also predicted. The result shows inactivity at a probability of 0.62 across all the compounds. The tendency of a substance to confer adverse effects on the immune system was determined through immunotoxicity prediction, and the results highlighted that the probability of activity was 0.96 for all the studied compounds. The induction of genetic mutations was observed through mutagenicity prediction; therefore, the result was inactive at a probability of 0.97. Ultimately, the cytotoxicity of the compounds indicated that they were inactive at a probability of 0.93.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePharmacotoxicity results for the studied compounds\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCompound\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eClassification\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTargets\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePrediction\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eProbability\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2B\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOrgan toxicity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHepatotoxicity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eActive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eToxicity endpoint\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCarcinogenicity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eInactive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eToxicity endpoint\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eImmunotoxicity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eActive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eToxicity endpoint\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMutagenicity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eInactive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eToxicity endpoint\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCytotoxicity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eInactive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2C\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOrgan toxicity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHepatotoxicity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eActive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eToxicity endpoint\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCarcinogenicity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eInactive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eToxicity endpoint\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eImmunotoxicity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eActive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eToxicity endpoint\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMutagenicity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eInactive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eToxicity endpoint\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCytotoxicity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eInactive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2D\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOrgan toxicity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHepatotoxicity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eActive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eToxicity endpoint\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCarcinogenicity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eInactive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eToxicity endpoint\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eImmunotoxicity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eActive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eToxicity endpoint\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMutagenicity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eInactive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eToxicity endpoint\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCytotoxicity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eInactive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2E\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOrgan toxicity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHepatotoxicity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eActive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eToxicity endpoint\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCarcinogenicity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eInactive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eToxicity endpoint\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eImmunotoxicity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eActive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eToxicity endpoint\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMutagenicity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eInactive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eToxicity endpoint\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCytotoxicity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eInactive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section3\"\u003e \u003ch2\u003e3.6.2 Drug Likeness\u003c/h2\u003e \u003cp\u003eThe term drug likeness encompasses the capacity of substances to possess physical properties or functional groups consistent with those found in established pharmaceutical compounds. The concept of drug likeness is instrumental in providing valuable insights into the molecular features that resemble those present in approved medications. However, this evaluation aids in determining the potential suitability of a molecule for drug development and its likelihood of exhibiting favorable pharmacological properties. The drug likeness of a compound can be evaluated using Lipinski's rule of 5 (RO5), Ghose's rule, and bioavailability scoring. Lipinski's rule of 5, formulated by Christopher A. Lipinski in 1997, is based on the observation that the majority of orally active drugs are relatively small molecules with certain physicochemical properties, such as appropriate lipophilicity and molecular size [\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e]. Lipinski's rule is a set of guidelines that specifies the ideal characteristics for drugs taken orally, including a molecular mass of less than 500 Daltons, a log P not exceeding 5, no more than 10 hydrogen bond acceptors, and no more than 5 hydrogen bond donors. The compounds in question (2B, 2C, 2D, and 2E) met all of these criteria, following the predictions analyzed in Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e. In addition, the Ghose filter assesses drug likeness based on the compound's molecular weight falling between 160 and 480 Daltons, a refractivity value greater than or equal to 40, between 20 and 70 atoms in the molecule, and a partition coefficient (log P) ranging from \u0026minus;\u0026thinsp;0.4 to 5.6. The results of the study indicate that the compounds (2B, 2C, 2D, and 2E) satisfy all of Ghose's rules [\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e]. It is highly desirable to accurately predict the drug-like properties of a drug in the early stages of drug discovery, as this approach can help rationalize the discovery process and save costs and time.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDrug-likeness prediction results for the studied compounds\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCompound\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMolecular weight\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLipinski rule\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGhose rule\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eViolation\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2B\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e404.34 g/mol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMW\u0026thinsp;\u0026le;\u0026thinsp;500\u003c/p\u003e \u003cp\u003eMLOGP\u0026thinsp;\u0026le;\u0026thinsp;4.15\u003c/p\u003e \u003cp\u003eN or O\u0026thinsp;\u0026le;\u0026thinsp;10\u003c/p\u003e \u003cp\u003eNH or OH\u0026thinsp;\u0026le;\u0026thinsp;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e160\u0026thinsp;\u0026le;\u0026thinsp;MW\u0026thinsp;\u0026le;\u0026thinsp;480\u003c/p\u003e \u003cp\u003e-0.4\u0026thinsp;\u0026le;\u0026thinsp;WLOGP\u0026thinsp;\u0026le;\u0026thinsp;5.6\u003c/p\u003e \u003cp\u003e40\u0026thinsp;\u0026le;\u0026thinsp;MR\u0026thinsp;\u0026le;\u0026thinsp;130\u003c/p\u003e \u003cp\u003e20\u0026thinsp;\u0026le;\u0026thinsp;atom\u0026thinsp;\u0026le;\u0026thinsp;70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eYES;0 violation\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2C\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e420.80 g/mol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMW\u0026thinsp;\u0026le;\u0026thinsp;500\u003c/p\u003e \u003cp\u003eMLOGP\u0026thinsp;\u0026le;\u0026thinsp;4.15\u003c/p\u003e \u003cp\u003eN or O\u0026thinsp;\u0026le;\u0026thinsp;10\u003c/p\u003e \u003cp\u003eNH or OH\u0026thinsp;\u0026le;\u0026thinsp;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e160\u0026thinsp;\u0026le;\u0026thinsp;MW\u0026thinsp;\u0026le;\u0026thinsp;480\u003c/p\u003e \u003cp\u003e-0.4\u0026thinsp;\u0026le;\u0026thinsp;WLOGP\u0026thinsp;\u0026le;\u0026thinsp;5.6\u003c/p\u003e \u003cp\u003e40\u0026thinsp;\u0026le;\u0026thinsp;MR\u0026thinsp;\u0026le;\u0026thinsp;130\u003c/p\u003e \u003cp\u003e20\u0026thinsp;\u0026le;\u0026thinsp;atom\u0026thinsp;\u0026le;\u0026thinsp;70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eYES;0 violation\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2D\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e386.35 g/mol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMW\u0026thinsp;\u0026le;\u0026thinsp;500\u003c/p\u003e \u003cp\u003eMLOGP\u0026thinsp;\u0026le;\u0026thinsp;4.15\u003c/p\u003e \u003cp\u003eN or O\u0026thinsp;\u0026le;\u0026thinsp;10\u003c/p\u003e \u003cp\u003eNH or OH\u0026thinsp;\u0026le;\u0026thinsp;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e160\u0026thinsp;\u0026le;\u0026thinsp;MW\u0026thinsp;\u0026le;\u0026thinsp;480\u003c/p\u003e \u003cp\u003e-0.4\u0026thinsp;\u0026le;\u0026thinsp;WLOGP\u0026thinsp;\u0026le;\u0026thinsp;5.6\u003c/p\u003e \u003cp\u003e40\u0026thinsp;\u0026le;\u0026thinsp;MR\u0026thinsp;\u0026le;\u0026thinsp;130\u003c/p\u003e \u003cp\u003e20\u0026thinsp;\u0026le;\u0026thinsp;atom\u0026thinsp;\u0026le;\u0026thinsp;70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eYES ;0 violation\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2E\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e416.38 g/mol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMW\u0026thinsp;\u0026le;\u0026thinsp;500\u003c/p\u003e \u003cp\u003eMLOGP\u0026thinsp;\u0026le;\u0026thinsp;4.15\u003c/p\u003e \u003cp\u003eN or O\u0026thinsp;\u0026le;\u0026thinsp;10\u003c/p\u003e \u003cp\u003eNH or OH\u0026thinsp;\u0026le;\u0026thinsp;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e160\u0026thinsp;\u0026le;\u0026thinsp;MW\u0026thinsp;\u0026le;\u0026thinsp;480\u003c/p\u003e \u003cp\u003e-0.4\u0026thinsp;\u0026le;\u0026thinsp;WLOGP\u0026thinsp;\u0026le;\u0026thinsp;5.6\u003c/p\u003e \u003cp\u003e40\u0026thinsp;\u0026le;\u0026thinsp;MR\u0026thinsp;\u0026le;\u0026thinsp;130\u003c/p\u003e \u003cp\u003e20\u0026thinsp;\u0026le;\u0026thinsp;atom\u0026thinsp;\u0026le;\u0026thinsp;70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eYES;0 violation\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":" Conclusion","content":"\u003cp\u003eThe antiviral efficacy of compounds 2B, 2C, 2D and 2E was investigated using DFT at the B3LYP/6-311G ++ (d, p) level of theory. Several objectives were applied to these thiophene derivatives, which aided us in exploring their diverse characteristics. Insight into the nature of the stability of the material was revealed through FMO determination, NBO analysis, and spectral analysis. NBO exhibited great transitions and bonding types at higher perturbation energies, such as LP\u0026rarr; LP, σ*\u0026rarr; σ*, and σ*\u0026rarr; σ transitions, whereby 2B was dominated by π*\u0026rarr; π*. Additionally, the FMO analysis revealed energy gap values of 3.758 eV, 3.750 eV, 3.743 eV, and 3.724 eV for 2B, 2C, 2D, and 2E, respectively. Moreover, UV‒Vis analysis also supported these results by revealing large wavelengths (433.49 nm, 347.12 nm, and 333.43 nm for compound 2B; 434.54 nm, 349.11 nm, and 336.12 nm for compound 2C; 435.20 nm, 347.41 nm, and 335.19 nm for compound 2D; and 434.26 nm, 348.53 nm, and 336.07 nm for compound 2E) at different excitation states. The compounds were observed to have dominant symmetric and asymmetric vibrations at their carbonic, amide, and methylated groups via FT-IR. We further investigated the reactivity and nature of the bonding interactions of the compounds via virtual studies. Thus, the NCI revealed a robust van der Waal and steric repulsion within the regions of the methanethioamide scaffold, hydrazineylmethanide scaffold, and 4-bromo-5-(methylthio)-2,3-dihydrothiophen-3-ide scaffold of all the compounds. Moreover, the ELF study showed high localization of electrons at the respective scaffolds, most specifically at the hydrogens, although 2E was pinpointed with a large density of electrons, providing additional reasons for its reactive nature, as also observed in the energy gap and Fermi energy of density of state analysis. Interestingly, the molecular docking approach shows a great affinity between the compounds and the target proteins of human papillomavirus (HPV). The protein‒ligand interactions between the 2B compound and 1R8H and 4GIZ exhibited binding energies of -5.3 kcal/mol and \u0026minus;\u0026thinsp;5.6 kcal/mol, respectively; the 2C compound demonstrated binding affinities of -5.6 kcal/mol and \u0026minus;\u0026thinsp;4.8 kcal/mol, respectively; the 2D compound displayed binding affinities of -4.8 kcal/mol and \u0026minus;\u0026thinsp;5.7 kcal/mol, respectively; and the 2E compound showed binding affinities of -5.2 kcal/mol and \u0026minus;\u0026thinsp;6.4 kcal/mol, respectively. All the compounds had a robust affinity for 4GIZ, particularly 2E, which exhibited a affinity of -6.4 kcal/mol. Isotretinoin, a conventional drug, showed strong affinities of -8.3 kcal/mol and \u0026minus;\u0026thinsp;6.6 kcal/mol for 1R8H and 4GIZ, respectively. Ultimately, our study demonstrated that all the studied compounds possess promising drug characteristics, especially antiviral potential, with 2E showing greater activity against HPV. Hence, these thiophene derivatives should be further investigated as promising drugs for the development of novel antiviral agents with fewer adverse effects and greater efficacy against HPV.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e5.1 Competing interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors declare zero financial or interpersonal conflicts of interest that could have influenced the research or the results reported in this research paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e5.2 Authorship Contribution Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMichael O. Odey\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e Conceptualization, design, and supervision. \u003cstrong\u003eAlpha O. Gulack\u003c/strong\u003e: Supervision, validation, and\u0026nbsp;investigation\u003cstrong\u003e. Rose O. Ogar and Stanley J. Oduma:\u0026nbsp;\u003c/strong\u003eanalysis,\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003ewriting,\u0026nbsp;and visualization.\u003cstrong\u003e\u0026nbsp;Diana O. Odey:\u003c/strong\u003e Analysis, editing, and writing. \u003cstrong\u003eSandra Ifeoma Iyen:\u0026nbsp;\u003c/strong\u003eSoftware, Resource, and methodology.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e5.3\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;Funding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was not funded by any governmental or nongovernmental agency.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eThompson, A. B., \u0026amp; Flowers, L. C. (2020). Human papillomavirus (HPV). \u003cem\u003eSexually Transmitted Infections in Adolescence and Young Adulthood: A Practical Guide for Clinicians\u003c/em\u003e, 279-297.\u003c/li\u003e\n\u003cli\u003eTrottier, H., \u0026amp; Burchell, A. N. (2009). 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The bioavailability and absorption of anthocyanins: toward a better understanding. \u003cem\u003eMolecular Nutrition \u0026amp; Food Research\u003c/em\u003e, \u003cem\u003e51\u003c/em\u003e(6), 702-713.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Scheme 1","content":"\u003cp\u003eScheme 1 is available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Human papillomavirus (HPV), thiophene derivative, drug design, molecular docking, DFT study","lastPublishedDoi":"10.21203/rs.3.rs-4247398/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4247398/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eOwing to the public health concern of human papillomavirus infection, which is capable of progressing into cancer among the population today, desperation to mitigate the cause of this infection is needed; hence, in this research, we unveiled the antiviral effects of four thiophene derivatives, 2B, 2C, 2D and 2E, against human papillomavirus (HPV) via computational DFT and molecular docking approaches along with ADMET prediction. Interestingly, the compounds showed great stability according to conformational assessment, spectroscopic studies (FT-IR and UV‒Vis), NBO studies, and quantum descriptor analysis. These compounds mostly exhibit LP\u0026rarr; LP, σ*\u0026rarr; σ*, and σ*\u0026rarr; σ transitions, as 2B shows a dominant π*\u0026rarr; π* orbital transition. Their reactivity was observed in different studies; for example, the HOMO-LUMO and DOS results highlighted 2B as the most reactive, among others. The energy gaps were 3.758 eV, 3.750 eV, 3.743 eV, and 3.724 eV for 2B, 2C, 2D, and 2E, respectively. During the docking process, the compounds displayed a high binding affinity and number of amino acids after interacting with the 1R8H and 4GIZ proteins of HPV, especially when they interacted with the 4GIZ protein, as the 2E-4GIZ complex displayed a robust affinity of -6.4 kcal/mol. Hence, these compounds show great antiviral potential against HPV and are promising candidates for novel HPV infection therapies.\u003c/p\u003e","manuscriptTitle":"Exploration of the antiviral efficacy of thiophene derivatives targeting human papillomavirus (HPV) and prevention of cancer: A comprehensive computational approach","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-16 12:13:39","doi":"10.21203/rs.3.rs-4247398/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"03c4eba4-f0ba-4888-8605-fbb01ad65536","owner":[],"postedDate":"April 16th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-04-18T14:42:23+00:00","versionOfRecord":[],"versionCreatedAt":"2024-04-16 12:13:39","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4247398","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4247398","identity":"rs-4247398","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}