Predictive Modelling of 6-Fluoro-3-Hydroxy-2-Pyrazine Carboxamide Drug Delivery Efficacy in Pegylated Bionanocomposite Through First Principles Simulation

Predictive Modelling of 6-Fluoro-3-Hydroxy-2-Pyrazine Carboxamide Drug Delivery Efficacy in Pegylated Bionanocomposite Through First Principles Simulation | 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 Predictive Modelling of 6-Fluoro-3-Hydroxy-2-Pyrazine Carboxamide Drug Delivery Efficacy in Pegylated Bionanocomposite Through First Principles Simulation Oluwasegun Chijioke Adekoya, Gbolahan Joseph Adekoya, Wanjun Liu, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4688547/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 This research investigates the drug delivery efficacy for 6-fluoro-3-hydroxy-2-pyrazinecarboxamide (Favipiravir) in PEGylated bionanocomposites using a predictive modelling approach. The study focuses on understanding the interaction mechanisms between Favipiravir (FAV) and polyethylene glycol (PEG)/graphene oxide (GO) (GO/PEG) nanosheets, across various environmental conditions. To evaluate drug delivery efficacy, the following key parameters were calculated: adsorption energies ranging from-202.61 to -3.46 kcal/mol indicating the strength of binding between the drug and nanocarrier; net charge transfer values between -0.222 to 0.373 electrons, reflecting the degree of charge migration; release times spanning a wide range from 3.4×10 −14 to 2.38×10 132 ms, which impacts the drug release kinetics; and thermodynamic parameters such as changes in Gibbs free energy (ΔG) between 183.34 and 16.95 kcal/mol, and changes in enthalpy (ΔH) between -203.64 and 0.55 kcal/mol, providing insights into the favorability and spontaneity of the drug-nanocarrier interactions. The results show that incorporating PEG onto GO nanosheets enhances adsorption energies and binding affinities for Favipiravir. Environmental factors and PEGylation influence the charge transfer and non-covalent interactions. PEGylation leads to faster Favipiravir release kinetics. Favorable thermodynamics are observed, especially in aqueous environments. Electronic properties, quantum descriptors, and theoretical spectra provide further insights into molecular interactions. DFT Drug delivery Favipiravir Graphene oxide Polyethylene glycol Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 1. Introduction The COVID-19 pandemic has emphasized the urgent need for innovative therapeutic strategies to effectively combat the spread and severity of the viral infection.[ 1 – 4 ] One such potential solution is the use of antiviral drugs like FAV, renowned for its broad-spectrum antiviral activity. Various clinical trials have demonstrated promising results, especially against RNA viruses such as SARS-CoV-2.[ 5 – 8 ] To enhance the delivery of FAV, researchers have explored many diverse polymer-based carriers, ranging from polymeric nanoparticles to dendrimer-based nanocarriers.[ 9 – 17 ] Each carrier system addresses specific challenges associated with drug delivery, such as improving solubility, bioavailability, sustained release, and targeted delivery to specific tissues or cells. For instance, studies on alginate-based nanoparticles and aerosolized solid lipid nanoparticles have shown potential for addressing these challenges.[ 12 , 14 , 16 , 18 ] Despite these efforts, challenges persist in the efficient delivery of FAV, to target sites within the human body, including issues, such as low bioavailability, inadequate specificity, and potential side effects from traditional drug delivery systems.[ 19 , 20 ] To overcome these challenges, advanced nanotechnological approaches, specifically the PEG-based bionanocomposites, offer promise. In a previous study, a graphene oxide-based PEG nanocomposite, demonstrated its effectiveness as a drug delivery substrate, highlighting the potential of this approach in biomedical applications.[ 21 ] The first principles simulations, based on quantum mechanical principles, offer unprecedented accuracy in predicting the behavior and interactions of molecular entities. Notably, Density Functional Theory (DFT) has played a crucial role in recent research on nanomaterials for drug delivery.[ 21 – 23 ] For instance, studies by using DFT, explored the drug delivery potential of two-dimensional nanostructures, such as graphene flakes.[ 24 ] The findings suggested the substantial promise of these nanostructures as carriers for FAV, with alterations in the electronic properties of the systems and the potential solubility enhancement.[ 24 ] Additionally, the molecular docking studies, assessed the interactions of various inhibitors with the COVID-19 main protease, identifying chloroquine and hydroxychloroquine as potent inhibitors.[ 25 ] Meanwhile, Sekineh and colleagues [ 9 ] employed the DFT to investigate the electronic sensitivity and reactivity of polyamidoamine (PAMAM) and polyester dendrimers towards FAV.[ 9 ] This research aims to utilize the predictive modeling techniques, grounded in first Principles simulations, to investigate and optimize the drug delivery efficiency of FAV.[ 23 ] The primary focus of this research is the incorporation of FAV into PEGylated bionanocomposites, with the aim to capitalize on the advantageous properties of both the drug and the nanocomposite carrier. The integration of PEG is expected to improve stability, solubility, and biocompatibility, ultimately enhancing the therapeutic potential of FAV. The study seeks to deepen the understanding of the interaction mechanism, miscibility, electronic, thermodynamic, and chemical reactivity of the FAV-PEGylated bionanocomposite system, through a rigorous evaluation of the quantum molecular descriptors in various phases. Figure 1 depicts the graphical representation of the GO, PEG, and the drug, in its neutral, protonated, and de-protonated states. The outcomes of this research hold the potential to advance the understanding of the molecular intricacies in FAV drug delivery and contribute significantly to the development of novel therapeutic strategies for combating viral infections. The integration of first Principles simulations with nanotechnology, represents a cutting-edge and inter-disciplinary approach, placing this research at the forefront of efforts, to address the challenges may be posed by possible re-occurrence of a global pandemic. 2. Computational Method In this study, the adsorption energies between a dimer of polyethylene glycol (PEG) and the 2x2-GO by using the integrated DFT methods, were investigated. The structures of PEG, GO, and the FAV drug molecule were optimized by using the DMol 3 module within Materials Studio 2020 software with the B3LYP exchange-correlation functional and DNP basis set.[ 26 , 27 ] The DFT calculations incorporated a long-range dispersion correction by using the Grimme method.[ 23 , 28 – 30 ] To determine the most thermodynamically favorable configuration for the drug-excipient system, an adsorption calculation was conducted by employing the Adsorption Locator module. The adsorption energies of the FAV drug on PEGylated GO nanosheets in the gas, water, acidic, and alkaline phases were calculated, and energetic properties, such as the: quantum molecular descriptors, electrostatic potential, and charge transfer were evaluated. The solvent environment was emulated by using the COSMO software, while the acidic and alkaline conditions were induced by protonating and de-protonating the drug.[ 31 – 35 ] The convergence criteria for the geometry optimization and energy calculations, were rigorously defined. The electronic properties, including the Molecular Electrostatic Potential (MEP) and charge transfer, which are essential for the understanding of the behaviour of molecules in various chemical reactions and processes, were evaluated via the single-point energy calculations by using the DMol 3 module. Mulliken analysis, facilitated the quantification of the charge transfer between the drug and excipient components.[ 36 ] The Visual Molecular Dynamics (VMD) and the Multiwfn softwares, aided in the visualization of the NCI isosurface plots, enabling a comprehensive understanding of the non-covalent interactions within the molecular system.[ 37 ] Moreover, the theoretical IR and UV spectra were computed by using the DMol 3 and the VAMP modules, respectively, providing insights into the electronic transitions and optical properties of the drug-excipient complexes. Furthermore, the compatibility between the drug and the nanocarrier, was simulated by using the blend calculator in Materials Studio, employing the COMPASSIII force field. The energy of mixing and the Chi interaction parameter were computed to ascertain the optimal thermodynamic compatibility across the different temperature conditions. Figure 2 illustrates an integrated DFT methodology, employed to model the drug delivery effectiveness of FAV within the PEGylated GO systems. 3. Results and Discussion 3.1. Interaction of Polyethylene Glycol/Graphene Oxide with FAV 3.1.1. Adsorption Energies The adsorption energies ( E ad ) and the adsorption distances ( d ) of FAV on GO and PEGylated GO nanosheets, were calculated[ 38 ] across various phases, viz : gas, aqueous, acidic, and alkaline environments (Equations 1 and 2 ). The results, summarized in Table 1 , shed light on the efficacy of drug delivery in different conditions. $$\:{{\rm\:E}}_{ad}=\:{{\rm\:E}}_{\text{G}\text{P}\text{F}}-\:\left({{\rm\:E}}_{\text{F}\text{A}\text{V}\:}+\:{{\rm\:E}}_{\:\text{G}\text{O}/\text{P}\text{E}\text{G}}\right)$$ 1 $$\:{{\rm\:E}}_{DFT-D}=\:{{\rm\:E}}_{DFT}+\:{{\rm\:E}}_{Disp}$$ 2 In the given equation, \(\:{{\rm\:E}}_{\text{G}\text{P}\text{F}}\) , \(\:{{\rm\:E}}_{\text{F}\text{A}\text{V}\:}\) and \(\:{{\rm\:E}}_{\:\text{G}\text{O}/\text{P}\text{E}\text{G}}\) denote the energies of the drug-excipient system, the drug molecule, and the nanocarrier, respectively. Furthermore, \(\:{{\rm\:E}}_{Disp}\) , as proposed by Grimme, denotes the long-range dispersion correction energy. In the case of the GF interactions, the adsorption energies varied significantly, among the phases, indicating the sensitivity of the system to environmental factors. In the gas phase, a moderate adsorption energy of -3.46 kcal/mol was observed, with an adsorption distance of 1.89 Å. However, in aqueous environments, a considerable enhancement in the adsorption energy was noted, with values dropping to -66.38 kcal/mol, suggesting a more favourable interaction between the drug and the carrier. This trend was consistent with the acidic and alkaline environments, where the adsorption energies further increased, reaching values of -202.61 kcal/mol and − 101.17 kcal/mol, respectively, indicating stronger interactions between FAV and GO. On the other hand, the incorporation of polyethylene glycol (PEG) onto the GO nanosheets, significantly altered the adsorption behaviour. In the gas phase, the adsorption energy for the GPF complex was notably higher (-27.69 kcal/mol) when compared to the GF interaction, indicating a stronger binding affinity, facilitated by the PEGylation. This trend persisted across all phases, with the most significant enhancement observed in acidic conditions, where the adsorption energy reached − 179.11 kcal/mol, highlighting the effectiveness of the PEGylation in the promotion of drug delivery under varying pH conditions. When examining the gas phase data alongside the available literature, it's evident that PAMAM dendrimers demonstrate a marginally reduced adsorption energy of -27.26 kcal/mol for the FAV in contrast to the PEGylated GO bionanocomposites, which was registered at -27.69 kcal/mol.[ 9 ] The optimized 3D structures of the GF and GPF complexes, depicted in Fig. 3 and S1, illustrate the structural arrangements of the system in different phases. These visualizations provide insights into the spatial orientation of the drug molecules within the nanocomposites, thereby, facilitating a better understanding of the adsorption mechanisms. The enhanced adsorption energies observed in the PEGylated systems, suggest their potential applications in optimizing the drug delivery strategies, particularly in the context of COVID-19 treatment, where efficient drug delivery is paramount for therapeutic efficacy. Table 1 Summary of the calculated adsorption energies and corresponding distances ( d ) between FAV and the nanocomposite surfaces, charge transfer and release time of the complexes in the various phases Species Phases E ad (Kcal/mol) d (Å) Adsorption site Q(e) Chi (298 K) E mix (298 K) \(\:\varvec{\tau\:}\) (ms) GF gas -3.46 1.89 N \(\:\to\:\) O -0.008 57.90 34.29 \(\:3.4\:\times\:{10}^{-14}\) water -66.38 1.82 N \(\:\to\:\) O 0.036 46.87 27.76 \(\:4.12\:\times\:\:{10}^{32}\) acidic -202.61 1.50 N \(\:\to\:\) O 0.373 13.62 8.06 \(\:2.38\:\times\:\:{10}^{132}\) alkaline -101.17 2.90 - 0.001 15.67 9.28 \(\:1.22\:\times\:\:{10}^{58}\) GPF gas -27.69 3.15 - 0.008 68.03 40.28 \(\:1.9\:\times\:\:{10}^{4}\) water -19.71 3.20 - -0.009 68.64 40.65 \(\:2.71\:\times\:\:{10}^{-2}\) acidic -179.11 0.98 N \(\:\to\:\) O 0.352 16.62 9.84 \(\:1.48\:\times\:\:{10}^{115}\) alkaline -76.54 1.45 O \(\:\to\:\) H -0.222 14.84 8.79 \(\:1.13\:\times\:\:{10}^{40}\) 3.1.2. Electrostatic Interactions and Charge Transfer Analysis The investigation into the electrostatic interactions and charge transfer within the FAV (FAV) drug delivery system, elucidated crucial insights into the nature of the intermolecular forces, governing the stability and efficacy of PEGylated bionanocomposites. Across the different phases and configurations, the net charge on the FAV drug varied, indicating the influence of the environmental factors and the PEGylation on the charge distribution within the system (Table 1 ). In the absence of PEGylation, the net charge on FAV was observed to be slightly negative in the gas phase (-0.008 e), while it became increasingly positive in the: aqueous (0.036 e), acidic (0.373 e), and alkaline (0.001 e) environments, when interacting with the GO nanocarriers. This trend suggests a shift in the charge distribution of the FAV molecules, induced by the interactions with the nanocarrier surface and environmental conditions. Upon the PEGylation of the GO nanosheets, the charge distribution on FAV, exhibited further alterations. Notably, in the gas phase, the net charge on FAV, became slightly positive (0.008 e), indicating a reversal of the charge polarity, facilitated by the PEGylation. In aqueous and alkaline environments, a similar reversal was observed, with FAV exhibiting a slightly negative charge (-0.009 e and − 0.222 e, respectively), suggesting a nuanced interplay between the PEGylation process and the environmental factors in modulating charge transfer dynamics. The molecular electrostatic potential (MEP) maps, depicted in Figs. 4 and S2, offer visual representations of the electrostatic potential distribution within the optimized GPF and GF complexes across the various phases. These maps reveal the distinct patterns of negative and positive electrostatic potentials, with negative potentials predominantly, localized around the oxygen atoms of the drug and carriers, while the positive potentials are concentrated around the carbon and hydrogen atoms. These observations underscore the significance of electrostatic interactions in mediating the binding affinity and stability of the drug-carrier complexes in different environments. The variability in the charge distribution and the electrostatic potential maps, across phases and configurations, underscores the dynamic nature of intermolecular interactions within the PEGylated bionanocomposites. These findings provide valuable insights into the mechanisms that govern the drug-carrier interactions and hold implications for the optimization of the drug delivery strategies. By elucidating the role of the electrostatic interactions in mediating the drug adsorption and the release kinetics, the study advances the understanding of FAV delivery by using PEGylated graphene oxide nano-vehicles, thereby paving the way for its potential applications in antiviral treatment, where a precise control over drug delivery, is essential for therapeutic efficacy. 3.1.3 . Non-covalent Interaction (NCI) of the FAV drug-GO nanocarrier systems The investigation into NCI within the FAV drug delivery system, provides crucial insights into the nature of the molecular interactions that govern the stability and efficacy of PEGylated bionanocomposites across different phases and configurations. Herein, the reduced density gradient (RDG) is calculated by using Eq. 3 , providing insights into the electron density ( \(\:\rho\:\left(r\right)\) ) distribution and the strength of the non-covalent interactions between the FAV molecules and the nanocomposite surfaces. $$\:RDGs=\:\frac{1}{2{\left(3{\pi\:}^{2}\right)}^{\frac{1}{3}}}\frac{\left|\stackrel{-}{\varDelta\:\rho\:}\left(r\right)\right|}{{\stackrel{-}{\rho\:\left(r\right)}}^{\frac{4}{3}}}$$ 3 The RDG isosurface maps and the scattered plots, depicted in Figs. 5 , 6 , S3, and S4, offer the visual representations of the non-covalent interactions within the optimized GPF and GF complexes in various phases. These visualizations reveal the spatial distribution of the non-covalent interactions and provide insights into the nature and strength of the molecular bonding within the systems. Table 1 summarizes the key findings regarding the non-covalent interactions between FAV and the nanocarrier surfaces in different phases. The analysis revealed distinct types of interactions, including strong hydrogen bonds and van der Waals forces, influencing the adsorption behaviour of FAV onto the nanocarrier surfaces. In the absence of PEGylation, GF interactions exhibited strong hydrogen bonds across all phases, with nitrogen atoms of the FAV, forming hydrogen bonds with the oxygen atoms on the nanocarrier surface. This interaction was particularly, prominent in the: gas, aqueous, and acidic environments, thereby, contributing to the significant adsorption energies observed in these phases. Conversely, in alkaline environments, the van der Waals forces dominated the interaction, leading to relatively weaker adsorption energies. Upon the PEGylation of the GO nanosheets, the nature of the non-covalent interactions underwent certain alterations. In gas and aqueous phases, the van der Waals forces became the predominant mode of interaction, resulting in lower adsorption energies when compared to the GF interactions. However, in acidic environments, the strong hydrogen bonds persisted between FAV and the carrier surface, indicating the resilience of these interactions, in modulating the drug adsorption behaviour. Interestingly, in alkaline environments, a shift was observed, with the oxygen atoms of FAV, forming strong hydrogen bonds with the hydrogen atoms of the nanocarrier surfaces, highlighting the nuanced interplay between the environmental conditions and the molecular interactions. These findings provide valuable insights into the mechanisms underlying FAV delivery by using PEGylated graphene oxide nano-vehicles. By elucidating the role of the non-covalent interactions in mediating the drug-carrier interactions, the study advances the understanding of the factors that influence the drug adsorption and the release kinetics. Moreover, the identification of key interaction sites and types, offers the opportunities for rational a design and optimization of the drug delivery systems, tailored for specific environmental conditions. The implications of these findings for their potential applications in antiviral treatment, are profound. The ability to modulate the drug adsorption behaviour, through the precise control over the non-covalent interactions, opens-up, the avenues for developing targeted and efficient drug delivery strategies. By leveraging the unique properties, such as enhanced stability and biocompatibility, of PEGylated bionanocomposites, this research lays the groundwork for the development of novel therapeutics with improved efficacy and reduced side effects, thereby addressing the critical challenges associated with antiviral treatment. 3.2. Miscibility Study of the FAV drug-GO nanocarrier systems The miscibility of the complexes was investigated through a comprehensive analysis of the Chi parameter and the energy of the mixture ( E mix ) in various environmental conditions. The study provides crucial insights into the interaction dynamics between the FAV drug molecules and the GO nanocarriers, which are essential for the optimization of drug delivery efficacy. The Chi parameter, indicative of the degree of miscibility between the components in a binary system, was evaluated as a function of temperature for GF and GPF complexes, across different phases, viz the: gas, aqueous, acidic, and alkaline environments. As illustrated in Fig. 7 , the Chi parameter exhibited a decreasing trend with increasing temperature in all the phases for both complexes. This temperature-dependent behaviour suggests an enhanced miscibility between FAV drug molecules and the nanocarrier surfaces, as the system transitioned to higher temperatures. Furthermore, the binding configurations of the GPF complex were examined in the: gas, aqueous, acidic, and alkaline phases to elucidate the spatial arrangement of FAV molecules on the nanocomposite surface. Figures 8 and S5 illustrate the binding configurations of the GPF and GF complexes, which provide valuable insights into the intermolecular interactions that govern the drug-nanocarrier complexation process. The E mix values, calculated at room temperature (298 K) by using Eq. 4 , provide quantitative assessments of the energy contributions from the drug-nanocarrier interactions, in the binary system. Tables 1 and S1 summarize the Chi interaction parameter and the E mix values for the GF and GPF complexes, across the different phases studied. $$\:{E}_{mix}=\frac{1}{2}z\left({E}_{bs}+{E}_{sb}-{E}_{bb}-{E}_{ss}\right)$$ 4 In all phases, higher Chi parameter values were observed for the GPF complex when compared to the GF counterpart, indicating an enhanced miscibility upon the PEGylation of the nanocarriers. Additionally, the E mix values reflect the energetically favorable interactions between the FAV drug molecules and the nanocomposite surfaces, with higher E mix values indicating strong binding affinity and improved stability of the drug-carrier complexes. 3.3. Release Mechanism of the FAV drug-GO nanocarrier systems The release mechanism of FAV from GO nanocarriers, with and without PEG modification, was investigated across the various phases, i.e., the: gas, aqueous, acidic, and alkaline environments. The release time of the drug from the nanocarriers was determined, providing insights into the efficacy of the drug delivery systems for its potential applications in COVID-19 treatment. The adsorption energy ( E ad ) of the drug on the GO-based nanocarriers, was found to influence the release time (τ), according to Eq. ( 5 ), where higher adsorption energies correspond to longer release times. In the case of the GF complexes, the adsorption energies varied significantly, across the different phases, with the highest values observed in acidic environments, followed by alkaline, water, and gas phases (in that order). Conversely, the GPF complexes exhibited lower adsorption energies overall, indicating a potentially faster release kinetics, when compared to their GO-only counterparts. $$\:\tau\:=\:{v}_{0}^{-1}\:\:exp\left(\frac{{-E}_{b}}{KT}\right)$$ 5 In this equation, T represents the temperature, k denotes Boltzmann's constant (~ \(\:1.99\:\times\:{10}^{-3}\) kcal/mol•K), and \(\:{v}_{0}\) stands for the frequency of the attempt. When utilizing the UV light for this application, the value of \(\:{v}_{0}\) at room temperature, was found to be \(\:{10}^{12}\) .[ 39 – 43 ] Table 1 summarizes the release time of FAV from the GO nanocarriers in various phases. Notably, the release times span a wide range, from the orders of magnitude ranging between \(\:{10}^{-14}\:\text{t}\text{o}\:{10}^{132}\) milliseconds. In this study, it is pertinent to note that release times greater than 10 8 milliseconds indicate a prolonged release, which may not be suitable for drug delivery at the target site. In the gas phase, both the GF and GPF complexes exhibited relatively short release times, suggesting efficient drug release kinetics in this environment. However, in the aqueous, acidic, and alkaline phases, the release times varied significantly, with the highest release times observed in acidic environments for both complexes. This implies the fact that the acidic environment can hinder the release of FAV from the nanocarriers, potentially impacting on its efficacy in acidic conditions, such as those found in certain physiological environments or diseased states. The observed recovery time for the FAV desorption from PAMAM (9.2 x 10 3 s) and polyester (4.2 x 10 3 s), are considerably, longer than that from PEGylated GO bionanocomposites, particularly in the gas and aqueous phases, making the material superior.[ 9 , 25 ] Hence, the findings provide valuable insights into the release mechanism of FAV from the GO nanocarriers, highlighting the influence of environmental factors on the drug release kinetics. The shorter the release times observed in the presence of PEGylation suggests the potential of PEGylated graphene oxide nano-vehicles to enhance the drug delivery efficacy, by facilitating faster release kinetics. These insights contribute to a better understanding of FAV delivery by using nanocarrier systems and thus, have tangible implications for the development of more effective treatments for infectious diseases. By optimizing the drug delivery systems, based on GO nanocarriers, researchers can potentially, improve on the therapeutic outcomes of FAV and other antiviral drugs, thereby ultimately, aiding in the fight against infectious diseases. 3.4. Thermodynamics of the FAV drug-GO nanocarrier systems In the thermodynamic analysis of the FAV drug-GO nanocarrier systems, across different phases, the changes in the Gibbs free energy (ΔG) and the enthalpy (ΔH), provide crucial insights into the stability and feasibility of drug delivery. These parameters were calculated at room temperature for each system, incorporating the finite temperature corrections (Equations 6 and 7 ). Table 2 summarizes the changes in Gibbs free energy (ΔG, Kcal/mol) and enthalpy (ΔH, Kcal/mol) for the drug-excipient complexes in various environments. $$\:{\varDelta\:G}^{298.15K}=627.51\:\left[{G}_{TCorr}^{298.15}\:\:\left(complex\right)-\:\left[{G}_{TCorr}^{298.15}\:\:\left(excipient\right)+\:{G}_{TCorr}^{298.15}\:\:\left(drug\right)\right]\right]$$ 6 $$\:{\varDelta\:H}^{298.15K}=627.51\:\left[{H}_{TCorr}^{298.15}\:\:\left(complex\right)-\:\left[{H}_{TCorr}^{298.15}\:\:\left(excipient\right)+\:{H}_{TCorr}^{298.15}\:\:\left(drug\right)\right]\right]$$ 7 In the gas phase, the ΔG values for both GF and GPF complexes, indicate favorable interactions between the drug and the nanocarriers, with values of 16.95 Kcal/mol and − 10.62 Kcal/mol, respectively, for ΔG and ΔH. These negative ΔH values suggest spontaneous processes, indicating the likelihood of stable complexes formation. However, it is noteworthy that the enthalpy change (ΔH) for the GF complex, is positive (0.55 Kcal/mol), implying an endothermic behavior during the formation process. Conversely, the GPF complex exhibits an exothermic process with a negative ΔH value of -23.59 Kcal/mol, indicating an energy release scenario during the complex formation. Transitioning to the aqueous phase, both complexes experience a significant decrease in the Gibbs free energy, indicating stronger interactions between the drug and nanocarriers in a water environment. The negative ΔG values (-52.43 Kcal/mol for GF and − 3.93 Kcal/mol for GPF) suggest thermodynamically, favorable conditions for drug delivery. However, the enthalpy change remains negative for GPF (-17.71 Kcal/mol), indicating an exothermic behavior, while GF displayed a highly negative ΔH (-68.83 Kcal/mol), indicating strong exothermic interactions. In acidic and alkaline environments, the thermodynamic parameters further highlight the stability of the drug-excipient complexes. Both the GF and GPF complexes, demonstrate negative ΔG values across these phases, indicating favorable conditions for drug encapsulation and release. The enthalpy changes also suggest exothermic processes, facilitating a complex formation in acidic (-203.64 Kcal/mol for GF and − 183.68 Kcal/mol for GPF) and in alkaline (-100.19 Kcal/mol for GF and − 68.7522 Kcal/mol for GPF) environments. These findings contribute significantly to the understanding of the behavior of FAV delivery by using PEGylated graphene oxide nano-vehicles across various phases. The positive ΔG values in the gas phase for GF, suggest the fact that without PEGylation, the interaction between the drug and the carrier may not be thermodynamically favorable. However, the incorporation of PEG, led to negative ΔG values across all phases, indicating an improved feasibility and a stability of the drug delivery system, especially in aqueous environments. In the context of its potential applications for antiviral treatment, these results underscore the importance of PEGylation in enhancing the efficacy of FAV delivery. By improving the thermodynamic parameters and thereby improving the stability of the drug-carrier complex, PEGylated graphene oxide nano-vehicles offer promising prospects for efficient drug delivery systems, particularly in aqueous environments that are relevant to biological systems. This enhanced stability and efficiency could potentially translate into improved therapeutic outcomes and efficacy in combating infectious diseases. Table 2 Thermodynamics energy parameters for various drug-excipient species in different phases Species E tot (Ha) \(\:{\varvec{H}}_{\begin{array}{c}TCorr\\\:\:\end{array}}^{298.15}\) (Ha) \(\:{\varvec{G}}_{\begin{array}{c}TCorr\\\:\:\end{array}}^{298.15}\) (Ha) \(\:{\varDelta\:\varvec{H}}^{298.15\varvec{K}}\) (Kcal/mol) \(\:{\varDelta\:\varvec{G}}^{298.15\varvec{K}}\) (Kcal/mol) Gas FAV -642.12 -642.00 -642.05 - - GO -1538.75 -1538.39 -1538.47 - - GO/PEG -1865.58 -1865.07 -1865.16 - - GF -2180.87 -2180.40 -2180.50 0.55 16.95 GPF -2507.74 -2507.11 -2507.23 -23.59 -10.62 Aqueous FAV -642.15 -642.04 -642.08 - - GO -1538.78 -1538.42 -1538.50 - - GO/PEG -1865.62 -1865.11 -1865.20 - - GF -2181.04 -2180.57 -2180.66 -68.83 -52.43 GPF -2507.80 -2507.18 -2507.29 -17.71 -3.93 Acidic FAV -642.45 -642.33 -642.37 - - GF -2181.52 -2181.04 -2181.13 -203.64 -183.34 GPF -2508.32 -2507.69 -2507.79 -183.68 -164.08 Alkaline FAV -641.12 -641.03 -641.07 - - GF -2180.03 -2179.57 -2179.67 -100.19 -84.05 GPF -2506.82 -2506.20 -2506.31 -68.7522 -53.21 3.5. Electronic and Quantum Chemical Descriptors of the FAV drug-GO nanocarrier systems The electronic and quantum chemical descriptors provide crucial insights into the molecular interactions and properties of the FAV drug-GO nanocarrier systems across various phases, shedding light on their potential for drug delivery applications. The frontier molecular orbitals, as depicted in Figs. 9 and S6, offer a visual representation of the electronic structure and the reactivity of the complexes in different environments. These orbitals play a vital role in determining the interactions between the drug and the nanocarrier, thereby, influencing their stability and efficacy in drug delivery applications. In the gas and water phases, the HOMO and LUMO energies, predominantly, reside on the GO nanocarrier for both the GF and GPF complexes, indicating strong interactions between the drug and nano-vehicles. This suggests that GO serves as an effective carrier for FAV delivery, with the PEGylation process not significantly altering the electronic properties of these systems, in these environments. Meanwhile, in acidic environments, a shift in the electronic structure is observed, particularly for the GF complex, where the LUMO is found on both the FAV drug and the GO molecules. This suggests a re-distribution of the electron density, due to the acid-induced changes in the nanocarrier's surface properties. Conversely, the GPF complex exhibits a different electronic configuration, with the LUMO, primarily residing on the FAV drug, indicating a distinct mode of interaction that was facilitated by the PEGylation. In alkaline environments, a further alteration in the electronic structure is evident, with the HOMO and LUMO energies, predominantly residing on the FAV drug for both the GF and GPF complexes. This suggests a shift in electron density towards the drug molecule, possibly due to alkaline-induced changes in the nanocarrier's surface charge or conformation. Furthermore, the energy band gap ( \(\:{E}_{g}\) ) serves as a measure of the sensitivity of the nanostructure to chemical agents.[ 43 , 44 ] The percentage change in the \(\:{E}_{g}\) (%∆ \(\:{E}_{g}\) ) before and after the FAV adsorption, indicates the extent of the electronic restructuring upon drug loading. Across all the phases studied, a decrease in the \(\:{E}_{g}\) , was observed after the drug adsorption, suggesting enhanced electrical conductivity and sensitivity of the nanocarriers to chemical agents. This phenomenon was more pronounced in the acidic and alkaline environments, where significant %∆ \(\:{E}_{g}\) values were observed, indicating a substantial electronic restructuring, upon FAV loading. The calculated quantum descriptors (Table 3 ), i.e., electron affinity (χ), chemical hardness (η), electronegativity (µ), and softness ( s ), provide additional insights into the reactivity and stability of the complexes.[ 45 ] These descriptors help to elucidate the nature of intermolecular interactions, such as: charge transfer and non-covalent bonding, and hence, contributing to the overall understanding of the drug-nanocarrier interactions and their implications for drug delivery applications. Comparatively, in the gas phase, both the GF and GPF complexes, exhibit similar values for the: electron affinity (χ), chemical hardness (η), and electronegativity (µ), indicating comparable stability and reactivity of the systems/complexes.[ 21 ] However, the GPF exhibited a slightly higher softness ( s ) value when compared to GF, suggesting an increased susceptibility to electronic perturbations. In water, acidic, and alkaline environments, notable differences emerged, particularly in the chemical hardness (η) and the softness ( s ). In these environments, the GPF complex consistently, exhibited higher η and lower s values when compared to the GF complex, indicating enhanced stability and resistance to electron transfer. Moreover, the significant increase in η for the GPF complex in acidic and alkaline phases, suggests a greater resistance to chemical changes, and therefore, potentially enhancing its suitability for drug delivery applications in varying physiological conditions. In all, these findings contribute to the understanding of FAV delivery by using PEGylated graphene oxide nano-vehicles across various phases, which was achieved by the elucidation of the electronic interactions and structural changes, induced by different environmental conditions. The ability to predict and optimize the electronic properties of drug-nanocarrier complexes, offers significant insights into their stability and efficacy, and hence, facilitating the development of targeted drug delivery systems for COVID-19 treatment and other infectious diseases. Moreover, the significant %∆ \(\:{E}_{g}\) values obtained, underscore the potential of these nanocomposites for sensor and detection applications, highlighting their versatility far beyond drug delivery applications. Table 3 Quantum descriptors of FAV Drug-GO nanocarrier complexes in different phases Structure configuration E HOMO (eV) E LUMO (eV) E g (eV) ΔE g (%) \(\:\varvec{\eta\:}\) (eV) µ (eV) s (eV) \(\:\varvec{\omega\:}\) (eV) ECT Gas FAV -6.83 -2.91 3.92 - 1.96 -4.87 0.51 6.05 - GO -4.67 -4.02 0.65 - 0.33 -4.34 3.06 28.83 - GO/PEG -4.51 -3.86 0.65 - 0.32 -4.19 3.09 27.12 - GF -4.46 -3.88 0.58 -10.93 0.29 -4.17 3.43 29.87 10.79 GPF -4.47 -3.86 0.61 -5.43 0.31 -4.17 3.27 28.42 10.47 Water FAV -6.77 -2.86 3.91 - 1.95 -4.81 0.51 5.93 - GO -4.60 -3.95 0.65 - 0.33 -4.28 3.06 27.96 - GO/PEG -4.51 -3.87 0.64 - 0.32 -4.19 3.13 27.50 - GF -4.51 -3.90 0.61 -6.33 0.31 -4.21 3.27 28.88 10.62 GPF -4.51 -3.90 0.61 -4.13 0.31 -4.21 3.27 28.88 10.66 Acidic FAV -11.17 -7.86 3.31 - 1.66 -9.51 0.60 27.34 - GF -4.33 -3.81 0.52 -20.50 0.26 -4.07 3.85 31.89 7.53 GPF -4.09 -3.11 0.98 51.37 0.49 -3.60 2.04 13.24 7.21 Alkaline FAV -12.24 -10.61 1.63 - 0.81 -11.42 1.23 80.28 - GF -8.56 -7.61 0.95 45.85 0.48 -8.08 2.10 68.50 -0.78 GPF -7.65 -7.42 0.23 -64.38 0.12 -7.54 8.69 246.77 -1.10 3.6. Theoretical IR and UV Spectra Analysis of the FAV drug-GO nanocarrier systems Theoretical spectroscopic analyses, including the IR and UV spectra (Figs. 10 and 11 ), were conducted to characterize the interactions between FAV and PEGylated GO nanocarriers across different environments. The spectra obtained provide valuable insights into the structural changes and vibrational modes of the drug-nanocarrier complexes, shedding light on their potential for drug delivery applications, particularly in the context of COVID-19 treatment. The IR spectra of the PEG/GF complexes reveal significant shifts and intensity variations in the vibrational bands, indicating strong interactions between the drug and nanocarriers across different phases. In the gas phase, prominent peaks at wavenumbers of ~ 3356.63 cm⁻¹ and ~ 1176 cm⁻¹, correspond to the stretching and bending vibrations of the O-H bonds in PEG, respectively, suggesting hydrogen bonding interactions with the FAV and GO molecules. In the aqueous phase, new peaks emerge at ~ 3107.70 cm⁻¹ and ~ 1767.20 cm⁻¹, corresponding to the O-H stretching vibrations in water and the C = O stretching vibrations in FAV, indicating hydration and solvation effects. In acidic and alkaline environments, distinct peaks appear at ~ 3425.41 cm⁻¹ and ~ 1806 cm⁻¹, respectively, suggesting the protonation and de-protonation of the functional groups, which further corroborate the pH-dependent behavior of the drug-nanocarrier complexes. The UV spectra of the GF and GPF complexes provide useful insights into the electronic transitions and energy levels of the drug-nanocarrier systems (Table 4 ). In the gas phase, characteristic peaks at wavelengths 281.31 nm and 531.31 nm for GF, and 287.45 nm and 555.45 nm for GPF, indicating a π-π* transitions within the aromatic rings of the FAV and GO/PEG, respectively. In the aqueous phase, redshifts in the absorption peaks are observed, suggesting solvation effects and electronic restructuring upon interaction with water molecules. These spectral changes reflect the environmental dependence of the electronic transitions and energy levels in the drug-nanocarrier complexes, highlighting their potential for responsive drug delivery in physiological conditions. The theoretical spectroscopic analyses offer valuable insights into the structural and electronic properties of the FAV-loaded PEGylated graphene oxide nanocarriers, across different phases. Understanding of vibrational modes and electronic transitions, provides crucial information for optimizing drug delivery efficacy and stability. Moreover, the pH-dependent behavior observed in the IR spectra suggests its potential applications in targeted drug release in acidic tumor micro-environments or alkaline bacterial infections. The UV spectra reveal the environmental influences on the electronic transitions, facilitating the design of responsive drug delivery systems for COVID-19 treatment and other infectious diseases. Hence, these findings are significant enough to contribute to the development of effective and tailored drug delivery strategies, with implications for enhancing therapeutic outcomes and minimizing side effects in clinical applications. Table 4 UV Parameters for GF and GPF in gas and aqueous phases Species Phases Level Energy (eV) Excitation (λ max ) Oscillator strength (f) GF gas 4.44 281.31 1.09 2.33 531.31 0.22 1.59 778.31 0.08 water 4.75 260.82 0.90 2.80 426.82 0.11 GPF gas 4.30 287.45 1.20 2.23 555.45 0.27 water 4.37 283.32 1.17 2.30 543.82 0.24 4. Conclusion The research on the predictive modeling of FAV drug delivery efficacy, through the first Principles simulation in PEGylated bionanocomposites, reveals significant insights. The study demonstrates the sensitivity of FAV interaction with nanocarriers to environmental conditions, with enhanced adsorption energies, observed in aqueous, acidic, and alkaline phases. The PEGylation of graphene oxide (GO) nanosheets, substantially improved the drug binding affinity, particularly in acidic environments, with the adsorption energies reaching − 179.11 kcal/mol. Analysis of the electrostatic interactions highlights a nuanced interplay between the PEGylation and the environmental factors that influence the charge distribution and stability of drug-carrier complexes. A non-covalent interaction analysis reveals strong hydrogen bonds and van der Waals forces, governing adsorption behavior, which are crucial for the optimization of drug delivery strategies. Miscibility studies demonstrate enhanced drug-nanocarrier interactions with increasing temperature, while the thermodynamics analysis underscores the stability and feasibility of drug encapsulation, particularly in aqueous environments. The electronic and quantum chemical descriptors provide insights into the electronic structure and the reactivity of the drug-nanocarrier complexes, with GPF exhibiting enhanced stability and resistance to electron transfer. Theoretical spectroscopic analyses corroborate the structural changes and the vibrational modes, further characterizing the drug-carrier interactions. Hence, the findings offer valuable implications for the optimization of drug delivery systems, particularly in the context of COVID-19 treatment, with PEGylated bionanocomposites, showing promise for enhanced therapeutic efficacy. Declarations AUTHOR INFORMATION Corresponding Author Gbolahan Joseph Adekoya - Institute of Nanoengineering Research (INER), Department of Chemical, Metallurgical and Materials Engineering, Faculty of Engineering and the Built Environment, Tshwane University of Technology, Pretoria 0001, South Africa: https://orcid.org/0000-0001-6381-0914 Email: [email protected] Authors Oluwasegun Chijioke Adekoya - Institute of Nanoengineering Research (INER), Department of Chemical, Metallurgical and Materials Engineering, Faculty of Engineering and the Built Environment, Tshwane University of Technology, Pretoria 0001, South Africa ; https://orcid.org/0000-0002-5386-5919 Wanjun Liu - Key Laboratory of Textile Science & Technology, Ministry of Education, College of Textiles, Donghua University, Shanghai 201620, China Rotimi Emmanuel Sadiku - Institute of Nanoengineering Research (INER), Department of Chemical, Metallurgical and Materials Engineering, Faculty of Engineering and the Built Environment, Tshwane University of Technology, Pretoria 0001, South Africa Yskandar Hamam - Department of Electrical Engineering, Faculty of Engineering and the Built Environment, Tshwane University of Technology, Pretoria 001, South Africa ; École Supérieure d’Ingénieurs en Électrotechnique et Électronique, Cité Descartes, 2 Boulevard Blaise Pascal, Noisy-le-Grand, Paris 93160, France Ethics declarations This study does not involve any clinical trial and therefore does not require registration in a clinical trial registry. Ethical approval and consent to participate: No animal or human studies were carried out by the authors of this article. Consent for publication: Not applicable (no individual data or images are included) Availability of data and materials: All data and materials are available upon request Credit authorship contribution statement: OCA and GJA: Software, Data curation, Conceptualization, Methodology, Formal analysis; YH and ERS: Supervision, Validation, Writing-review & editing; WL: Writing - review & editing. Acknowledgments: OCA and GJA would like to thank Center for High Performance Computing (CHPC), South Africa for access to computing resources. Additionally, OCA lovingly appreciates his wife, Omolola Felicia Adekoya, while GJA expresses deep gratitude to Oluwaferanmi Tiara Adekoya, with sincere thanks and affection from her father. Competing Interest: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Funding: No funding was received for this study References Du, Y.X. and X.P. Chen, Favipiravir: pharmacokinetics and concerns about clinical trials for 2019 ‐nCoV infection. Clinical Pharmacology & Therapeutics, 2020. 108 (2): p. 242-247. Hassanipour, S., et al., The efficacy and safety of Favipiravir in treatment of COVID-19: a systematic review and meta-analysis of clinical trials. Scientific reports, 2021. 11 (1): p. 11022. Deng, W., et al., Evaluation of favipiravir in the treatment of COVID-19 based on the real-world. Expert review of anti-infective therapy, 2022. 20 (4): p. 555-565. Abdelnabi, R., et al., The combined treatment of Molnupiravir and Favipiravir results in a potentiation of antiviral efficacy in a SARS-CoV-2 hamster infection model. EBioMedicine, 2021. 72 . Driouich, J.-S., et al., Favipiravir antiviral efficacy against SARS-CoV-2 in a hamster model. Nature Communications, 2021. 12 (1): p. 1735. Yamamura, H., et al., Effect of favipiravir and an anti-inflammatory strategy for COVID-19. Critical Care, 2020. 24 (1): p. 413. Agrawal, U., R. Raju, and Z.F. Udwadia, Favipiravir: A new and emerging antiviral option in COVID-19. Medical Journal Armed Forces India, 2020. 76 (4): p. 370-376. Shah, P.L., et al., Favipiravir in patients hospitalised with COVID-19 (PIONEER trial): a multicentre, open-label, phase 3, randomised controlled trial of early intervention versus standard care. The Lancet Respiratory Medicine, 2023. 11 (5): p. 415-424. Bazyari-Delavar, S., et al., PAMAM and polyester dendrimers as favipiravir nanocarriers: a comparative study using DFT method. Journal of Nanoparticle Research, 2021. 23 (10): p. 231. Alcantara, K.P., et al., Enhanced nasal deposition and anti-coronavirus effect of favipiravir-loaded mucoadhesive chitosan–alginate nanoparticles. Pharmaceutics, 2022. 14 (12): p. 2680. Xu, L., et al., Temperature-Responsive Multilayer Films Based on Block Copolymer-Coated Silica Nanoparticles for Long-Term Release of Favipiravir. ACS Applied Nano Materials, 2021. 4 (12): p. 14014-14025. Gattani, V. and S. Dawre, Development of favipiravir loaded PLGA nanoparticles entrapped in in-situ gel for treatment of Covid-19 via nasal route. Journal of Drug Delivery Science and Technology, 2023. 79 : p. 104082. Reddy Obireddy, S., et al., Synthesis and properties of alginate-based nanoparticles incorporated with different inorganic nanoparticulate modifiers for enhanced encapsulation and controlled release of favipiravir. Arabian Journal of Chemistry, 2023. 16 (7): p. 104751. Tulbah, A.S. and W.-H. Lee, Physicochemical Characteristics and In Vitro Toxicity/Anti-SARS-CoV-2 Activity of Favipiravir Solid Lipid Nanoparticles (SLNs). Pharmaceuticals, 2021. 14 (10): p. 1059. Ahangarani-Farahani, R., M.A. Bodaghifard, and S. Asadbegi, Magnetic triazine-based dendrimer as a versatile nanocarrier for efficient antiviral drugs delivery. Scientific Reports, 2022. 12 (1): p. 19469. Xu, L., et al., Steric Effects in the Deposition Mode and Drug-Delivering Efficiency of Nanocapsule-Based Multilayer Films. ACS Omega, 2022. 7 (34): p. 30321-30332. Adekoya, O.C., et al., A mini-review on the application of machine learning in polymer nanogels for drug delivery. Materials Today: Proceedings, 2022: p. 1-4. Salawi, A., et al., Development of Statistically Optimized Chemically Cross-Linked Hydrogel for the Sustained-Release Delivery of Favipiravir. Polymers, 2022. 14 (12): p. 2369. Shrestha, D.B., et al., Favipiravir versus other antiviral or standard of care for COVID-19 treatment: a rapid systematic review and meta-analysis. Virology Journal, 2020. 17 (1): p. 141. Xu, L., et al., Environmentally Responsive Multilayer Films Based on Block Copolymer Micelles and Natural Peptides for Controlled Release of Favipiravir. Available at SSRN 4194451, 2022. Adekoya, O.C., et al., Density Functional Theory Interaction Study of a Polyethylene Glycol-Based Nanocomposite with Cephalexin Drug for the Elimination of Wound Infection. ACS omega, 2022. 7 (38): p. 33808-33820. Cao, Y., et al., Coronene surface for delivery of Favipiravir: Computational approach. Inorganic Chemistry Communications, 2022. 136 : p. 109133. Adekoya, O.C., et al., Application of DFT Calculations in Designing Polymer-Based Drug Delivery Systems: An Overview. Pharmaceutics, 2022. 14 (9): p. 1972. Al-Qargholi, B., et al., Nanosheets (CC-BC3-C3N) as an carrier for favipiravir drug: A density functional theory study. Inorganic Chemistry Communications, 2023. 150 : p. 110475. Silva Arouche, T.d., et al., Interactions between remdesivir, ribavirin, favipiravir, galidesivir, hydroxychloroquine and chloroquine with fragment molecular of the COVID-19 main protease with inhibitor N3 complex (PDB ID: 6LU7) using molecular docking. Journal of Nanoscience and Nanotechnology, 2020. 20 (12): p. 7311-7323. Ahmed, T., et al., Unravelling the adsorption performance of BN, AlN, GaN and InN 2D nanosheets towards the ciclopirox, 5-fluorouracil and nitrosourea for anticancer drug delivery motive: A DFT-D with QTAIM, PCM and COSMO investigations. Computational and Theoretical Chemistry, 2022. 1214 : p. 113797. Delley, B., An all ‐electron numerical method for solving the local density functional for polyatomic molecules. The Journal of Chemical Physics, 1990. 92 (1): p. 508-517. Sedlak, R., et al., Accuracy of Quantum Chemical Methods for Large Noncovalent Complexes. Journal of Chemical Theory and Computation, 2013. 9 (8): p. 3364-3374. Caldeweyher, E., C. Bannwarth, and S. Grimme, Extension of the D3 dispersion coefficient model. The Journal of chemical physics, 2017. 147 (3): p. 034112. Grimme, S., et al., A consistent and accurate ab initio parametrization of density functional dispersion correction (DFT-D) for the 94 elements H-Pu. The Journal of Chemical Physics, 2010. 132 (15): p. 154104. Klamt, A. and G. Schüürmann, COSMO: a new approach to dielectric screening in solvents with explicit expressions for the screening energy and its gradient. Journal of the Chemical Society, Perkin Transactions 2, 1993(5): p. 799-805. Xu, H., et al., DFT study of nanotubes as the drug delivery vehicles of Efavirenz. Computational and Theoretical Chemistry, 2018. 1131 : p. 57-68. Swietach, P., et al., The chemistry, physiology and pathology of pH in cancer. Philosophical transactions of the royal society B: biological sciences, 2014. 369 (1638): p. 20130099. Mollarasouli, F., N. Zare-Shehneh, and M. Ghaedi, A review on corona virus disease 2019 (COVID-19): current progress, clinical features and bioanalytical diagnostic methods. Microchimica Acta, 2022. 189 (3): p. 103. Yapasert, R., P. Khaw-On, and R. Banjerdpongchai, Coronavirus infection-associated cell death signaling and potential therapeutic targets. Molecules, 2021. 26 (24): p. 7459. McNellis, E.R., J. Meyer, and K. Reuter, Azobenzene at coinage metal surfaces: Role of dispersive van der Waals interactions. Physical Review B, 2009. 80 (20): p. 205414. Farzad, F. and H. Hashemzadeh, Probing the effect of polyethene glycol on the adsorption mechanisms of Gem on the hexagonal boron nitride as a highly efficient polymer-based drug delivery system: DFT, classical MD and Well-tempered Metadynamics simulations. Journal of Molecular Graphics and Modelling, 2020. 98 : p. 107613. Grimme, S., Density functional theory with London dispersion corrections. WIREs Computational Molecular Science, 2011. 1 (2): p. 211-228. Hosseinian, A., et al., Benzoylethanamine drug interaction with the AlN nanosheet, nanotube and nanocage: Density functional theory studies. Thin Solid Films, 2017. 640 : p. 93-98. Bagheri, R., et al., Si-doped phagraphene as a drug carrier for adrucil anti-cancer drug: DFT studies. Inorganic Chemistry Communications, 2018. 90 : p. 8-14. Onsori, S. and E. Alipour, A computational study on the cisplatin drug interaction with boron nitride nanocluster. Journal of Molecular Graphics and Modelling, 2018. 79 : p. 223-229. Nejati, K., et al., A comparative DFT study on the interaction of cathinone drug with BN nanotubes, nanocages, and nanosheets. Applied Surface Science, 2017. 422 : p. 763-768. Wang, M. and C. Tang, Silicon Doped Boron Carbide (BC 3 ) Nanosheet as a Promising Sensitive Material for Detection of Acetaminophen Drug Based on the DFT Approach. Silicon, 2021. 14 (10): p. 5463-5470. Xiao, C., et al., Borophene as an electronic sensor for metronidazole drug: A computational study. Journal of Molecular Graphics and Modelling, 2020. 96 : p. 107539. Rahimi, R. and M. Solimannejad, BC 3 graphene-like monolayer as a drug delivery system for nitrosourea anticancer drug: A first-principles perception. Applied Surface Science, 2020. 525 : p. 146577. Additional Declarations No competing interests reported. Supplementary Files SupportingDocGOPEGFAV.docx Graphicalabstract.jpg Graphical abstract 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. 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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-4688547","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":338535701,"identity":"f4aeb088-7763-4655-9f5e-a5eec443decb","order_by":0,"name":"Oluwasegun Chijioke Adekoya","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4ElEQVRIiWNgGAWjYFCCBGYog/kAkJCQIUULWwJICw8pWngMwCRBDfztyYcNPrbZMfCzn/n86kaNBQ8D++GjG/BpkTjzLDlxZlsyg2RP7jbrnGNAh/Gkpd3Aa82NHOPDvG3MDAY3eLcZ57ABtUjwmOHVIn8j/zNQSz1QC88z45x/RGgxuJHDnMzbdhikhflxbhsRWgzPPDM2nHHuOI9kT5oZc26fBA8bIb/IHU9+LPGhrFqOn/3w48853+pAjGP4vQ8CjGzg6GCTAHHYCCoHgz9gkvkDcapHwSgYBaNgpAEATZJDjPsjwXYAAAAASUVORK5CYII=","orcid":"","institution":"Tshwane University of Technology","correspondingAuthor":true,"prefix":"","firstName":"Oluwasegun","middleName":"Chijioke","lastName":"Adekoya","suffix":""},{"id":338535702,"identity":"d8b8b031-644b-4aa8-9c5f-008d08ec89ed","order_by":1,"name":"Gbolahan Joseph Adekoya","email":"","orcid":"","institution":"Tshwane University of Technology","correspondingAuthor":false,"prefix":"","firstName":"Gbolahan","middleName":"Joseph","lastName":"Adekoya","suffix":""},{"id":338535703,"identity":"10d82845-4a34-41ad-94e9-9edde421c0aa","order_by":2,"name":"Wanjun Liu","email":"","orcid":"","institution":"Donghua University","correspondingAuthor":false,"prefix":"","firstName":"Wanjun","middleName":"","lastName":"Liu","suffix":""},{"id":338535704,"identity":"3cd92e3d-23ed-43c0-8bc4-ea3fdd750047","order_by":3,"name":"Emmanuel Rotimi Sadiku","email":"","orcid":"","institution":"Tshwane University of Technology","correspondingAuthor":false,"prefix":"","firstName":"Emmanuel","middleName":"Rotimi","lastName":"Sadiku","suffix":""},{"id":338535705,"identity":"b53d1dd7-49e1-4c63-bdf9-986f78d789a6","order_by":4,"name":"Yskandar Hamam","email":"","orcid":"","institution":"Tshwane University of Technology","correspondingAuthor":false,"prefix":"","firstName":"Yskandar","middleName":"","lastName":"Hamam","suffix":""}],"badges":[],"createdAt":"2024-07-04 21:08:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4688547/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4688547/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":63097184,"identity":"87d035d8-6569-412c-91ab-c346ae493d4e","added_by":"auto","created_at":"2024-08-23 06:01:07","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":173463,"visible":true,"origin":"","legend":"\u003cp\u003e3-D structure of the optimized configuration of the: (a) GO, (b) PEG, and (c) 3-D structure of the optimized structure of FAV in its neutral, protonated, and de-protonated states. Colors: red, grey, white, and blue represent oxygen, carbon, hydrogen, and nitrogen, respectively.\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4688547/v1/5906e05605ad016efdf70f0f.jpg"},{"id":63097190,"identity":"1b3b42b2-062e-4af6-95c8-0a21afbc9501","added_by":"auto","created_at":"2024-08-23 06:01:07","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":434458,"visible":true,"origin":"","legend":"\u003cp\u003eAn integrated DFT approach to simulate the drug delivery efficacy of FAV in PEGylated systems.\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4688547/v1/ca90761510b0a10fdd132b75.jpg"},{"id":63097557,"identity":"b7de5526-dbff-4162-bff1-91c3f7941d20","added_by":"auto","created_at":"2024-08-23 06:09:07","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":195913,"visible":true,"origin":"","legend":"\u003cp\u003eDisplay of the optimized 3-D structures of the GPF complex across various phases: (a) gas, (b) aqueous, (c) acidic, and (d) alkaline.\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4688547/v1/791f0dcb576b7c0f2d04de12.jpg"},{"id":63097185,"identity":"5a8a7740-94b0-4334-b50c-73c8f4f49cbe","added_by":"auto","created_at":"2024-08-23 06:01:07","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":206798,"visible":true,"origin":"","legend":"\u003cp\u003eThe molecular electrostatic potential map that depicts the optimized GPF complex across different phases, \u003cem\u003eviz\u003c/em\u003e: (a) gas, (b) aqueous, (c) acidic, and (d) alkaline.\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4688547/v1/4351b4c261285364bdcda165.jpg"},{"id":63097552,"identity":"feca5641-82d3-40db-804a-1f53acc022ca","added_by":"auto","created_at":"2024-08-23 06:09:07","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":445613,"visible":true,"origin":"","legend":"\u003cp\u003eIllustration of an RDG isosurface map (left) andthe scatter plot (right), showcasing the noncovalent interactions within the optimized GPF complex in the gas (a) and aqueous (b) phases.\u003c/p\u003e","description":"","filename":"5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4688547/v1/a68ffb62c6e9f6f7a3f7bf15.jpg"},{"id":63098486,"identity":"f8a60d4a-8504-49c2-bac0-fa493d95d2ac","added_by":"auto","created_at":"2024-08-23 06:25:07","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":494920,"visible":true,"origin":"","legend":"\u003cp\u003eIllustration of an RDG isosurface map (left) and the scatter plot (right), showcasing the noncovalent interactions within the optimized GPF complex in the (a) acidic and (b) alkaline phases.\u003c/p\u003e","description":"","filename":"6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4688547/v1/f23090f6b4e177a89db82d53.jpg"},{"id":63098071,"identity":"29864ac4-8f19-4cdd-8fd0-4c8e94abab20","added_by":"auto","created_at":"2024-08-23 06:17:07","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":110746,"visible":true,"origin":"","legend":"\u003cp\u003eDisplaysof the plots depicting the Chi interaction parameter, plotted as a function temperature for (a) GF and (b) GPF complexes across different phases.\u003c/p\u003e","description":"","filename":"7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4688547/v1/4d75c84f9f0329f5976c60fb.jpg"},{"id":63097188,"identity":"ecbb560c-4c23-483d-a075-58816c85a85d","added_by":"auto","created_at":"2024-08-23 06:01:07","extension":"jpg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":235929,"visible":true,"origin":"","legend":"\u003cp\u003eIllustration of the binding configuration of the GPF complex in: (a) gas, (b) aqueous, (c) acidic, and (d) alkaline phases.\u003c/p\u003e","description":"","filename":"8.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4688547/v1/7d7aa82d6563f1344fd55d71.jpg"},{"id":63099202,"identity":"748dc94b-2c02-4920-94dc-bdd87b2ff904","added_by":"auto","created_at":"2024-08-23 06:33:07","extension":"jpg","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":1976218,"visible":true,"origin":"","legend":"\u003cp\u003eIllustration of the three-dimensional representations of the frontier molecular orbitals of the PEG/GF complexes in the: (a) gas, (b) aqueous, (c) acidic, and (d) alkaline phases\u003c/p\u003e","description":"","filename":"9.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4688547/v1/bdaaeadae1cc3d8731957a51.jpg"},{"id":63097192,"identity":"0bfef522-77db-46ec-b168-fc2f42a41ead","added_by":"auto","created_at":"2024-08-23 06:01:07","extension":"jpg","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":217933,"visible":true,"origin":"","legend":"\u003cp\u003eIR spectra of the PEG/GF complexes in the: gas, aqueous, acidic, and alkaline phases\u003c/p\u003e","description":"","filename":"10.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4688547/v1/d32c1e2f88ac394683b46a63.jpg"},{"id":63097555,"identity":"157b60bf-0fe4-49ef-8a86-f8e8017ad66e","added_by":"auto","created_at":"2024-08-23 06:09:07","extension":"jpg","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":117061,"visible":true,"origin":"","legend":"\u003cp\u003eUV spectra of the (a) GF and (b) PEG/GF complexes in the gas, and aqueous\u003c/p\u003e","description":"","filename":"11.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4688547/v1/32ab809ca6f823c498418058.jpg"},{"id":73148141,"identity":"d6b0641d-a681-4562-a659-b096265dcf06","added_by":"auto","created_at":"2025-01-07 08:03:12","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5686932,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4688547/v1/4befa860-6dec-471b-b629-957a847ff5f1.pdf"},{"id":63097196,"identity":"a9f7c72b-25a7-48a6-a7c3-5d595f653a9b","added_by":"auto","created_at":"2024-08-23 06:01:07","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":8872366,"visible":true,"origin":"","legend":"","description":"","filename":"SupportingDocGOPEGFAV.docx","url":"https://assets-eu.researchsquare.com/files/rs-4688547/v1/a29dd8f5efcdb7bd561e7d0b.docx"},{"id":63097193,"identity":"43798725-dae7-479f-b295-b008cda6b0ad","added_by":"auto","created_at":"2024-08-23 06:01:07","extension":"jpg","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":87536,"visible":true,"origin":"","legend":"\u003cp\u003eGraphical abstract\u003c/p\u003e","description":"","filename":"Graphicalabstract.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4688547/v1/02b23c249d86d8a7404eb3a8.jpg"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003ePredictive Modelling of 6-Fluoro-3-Hydroxy-2-Pyrazine Carboxamide Drug Delivery Efficacy in Pegylated Bionanocomposite Through First Principles Simulation \u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eThe COVID-19 pandemic has emphasized the urgent need for innovative therapeutic strategies to effectively combat the spread and severity of the viral infection.[\u003cspan additionalcitationids=\"CR2 CR3\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] One such potential solution is the use of antiviral drugs like FAV, renowned for its broad-spectrum antiviral activity. Various clinical trials have demonstrated promising results, especially against RNA viruses such as SARS-CoV-2.[\u003cspan additionalcitationids=\"CR6 CR7\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eTo enhance the delivery of FAV, researchers have explored many diverse polymer-based carriers, ranging from polymeric nanoparticles to dendrimer-based nanocarriers.[\u003cspan additionalcitationids=\"CR10 CR11 CR12 CR13 CR14 CR15 CR16\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] Each carrier system addresses specific challenges associated with drug delivery, such as improving solubility, bioavailability, sustained release, and targeted delivery to specific tissues or cells. For instance, studies on alginate-based nanoparticles and aerosolized solid lipid nanoparticles have shown potential for addressing these challenges.[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eDespite these efforts, challenges persist in the efficient delivery of FAV, to target sites within the human body, including issues, such as low bioavailability, inadequate specificity, and potential side effects from traditional drug delivery systems.[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] To overcome these challenges, advanced nanotechnological approaches, specifically the PEG-based bionanocomposites, offer promise. In a previous study, a graphene oxide-based PEG nanocomposite, demonstrated its effectiveness as a drug delivery substrate, highlighting the potential of this approach in biomedical applications.[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eThe first principles simulations, based on quantum mechanical principles, offer unprecedented accuracy in predicting the behavior and interactions of molecular entities. Notably, Density Functional Theory (DFT) has played a crucial role in recent research on nanomaterials for drug delivery.[\u003cspan additionalcitationids=\"CR22\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eFor instance, studies by using DFT, explored the drug delivery potential of two-dimensional nanostructures, such as graphene flakes.[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] The findings suggested the substantial promise of these nanostructures as carriers for FAV, with alterations in the electronic properties of the systems and the potential solubility enhancement.[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] Additionally, the molecular docking studies, assessed the interactions of various inhibitors with the COVID-19 main protease, identifying chloroquine and hydroxychloroquine as potent inhibitors.[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] Meanwhile, Sekineh and colleagues [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] employed the DFT to investigate the electronic sensitivity and reactivity of polyamidoamine (PAMAM) and polyester dendrimers towards FAV.[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eThis research aims to utilize the predictive modeling techniques, grounded in first Principles simulations, to investigate and optimize the drug delivery efficiency of FAV.[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] The primary focus of this research is the incorporation of FAV into PEGylated bionanocomposites, with the aim to capitalize on the advantageous properties of both the drug and the nanocomposite carrier. The integration of PEG is expected to improve stability, solubility, and biocompatibility, ultimately enhancing the therapeutic potential of FAV. The study seeks to deepen the understanding of the interaction mechanism, miscibility, electronic, thermodynamic, and chemical reactivity of the FAV-PEGylated bionanocomposite system, through a rigorous evaluation of the quantum molecular descriptors in various phases. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e depicts the graphical representation of the GO, PEG, and the drug, in its neutral, protonated, and de-protonated states. The outcomes of this research hold the potential to advance the understanding of the molecular intricacies in FAV drug delivery and contribute significantly to the development of novel therapeutic strategies for combating viral infections. The integration of first Principles simulations with nanotechnology, represents a cutting-edge and inter-disciplinary approach, placing this research at the forefront of efforts, to address the challenges may be posed by possible re-occurrence of a global pandemic.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"2. Computational Method","content":"\u003cp\u003eIn this study, the adsorption energies between a dimer of polyethylene glycol (PEG) and the 2x2-GO by using the integrated DFT methods, were investigated. The structures of PEG, GO, and the FAV drug molecule were optimized by using the DMol\u003csup\u003e3\u003c/sup\u003e module within Materials Studio 2020 software with the B3LYP exchange-correlation functional and DNP basis set.[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] The DFT calculations incorporated a long-range dispersion correction by using the Grimme method.[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan additionalcitationids=\"CR29\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e] To determine the most thermodynamically favorable configuration for the drug-excipient system, an adsorption calculation was conducted by employing the Adsorption Locator module. The adsorption energies of the FAV drug on PEGylated GO nanosheets in the gas, water, acidic, and alkaline phases were calculated, and energetic properties, such as the: quantum molecular descriptors, electrostatic potential, and charge transfer were evaluated. The solvent environment was emulated by using the COSMO software, while the acidic and alkaline conditions were induced by protonating and de-protonating the drug.[\u003cspan additionalcitationids=\"CR32 CR33 CR34\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e] The convergence criteria for the geometry optimization and energy calculations, were rigorously defined. The electronic properties, including the Molecular Electrostatic Potential (MEP) and charge transfer, which are essential for the understanding of the behaviour of molecules in various chemical reactions and processes, were evaluated \u003cem\u003evia\u003c/em\u003e the single-point energy calculations by using the DMol\u003csup\u003e3\u003c/sup\u003e module. Mulliken analysis, facilitated the quantification of the charge transfer between the drug and excipient components.[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e] The Visual Molecular Dynamics (VMD) and the Multiwfn softwares, aided in the visualization of the NCI isosurface plots, enabling a comprehensive understanding of the non-covalent interactions within the molecular system.[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e] Moreover, the theoretical IR and UV spectra were computed by using the DMol\u003csup\u003e3\u003c/sup\u003e and the VAMP modules, respectively, providing insights into the electronic transitions and optical properties of the drug-excipient complexes. Furthermore, the compatibility between the drug and the nanocarrier, was simulated by using the blend calculator in Materials Studio, employing the COMPASSIII force field. The energy of mixing and the Chi interaction parameter were computed to ascertain the optimal thermodynamic compatibility across the different temperature conditions. Figure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e illustrates an integrated DFT methodology, employed to model the drug delivery effectiveness of FAV within the PEGylated GO systems.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"3. Results and Discussion","content":"\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e\u003cb\u003e3.1. Interaction of Polyethylene Glycol/Graphene Oxide with FAV\u003c/b\u003e\u003c/h2\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003e3.1.1. Adsorption Energies\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe adsorption energies (\u003cem\u003eE\u003c/em\u003e\u003csub\u003e\u003cem\u003ead\u003c/em\u003e\u003c/sub\u003e) and the adsorption distances (\u003cem\u003ed\u003c/em\u003e) of FAV on GO and PEGylated GO nanosheets, were calculated[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e] across various phases, \u003cem\u003eviz\u003c/em\u003e: gas, aqueous, acidic, and alkaline environments (Equations \u003cspan refid=\"Equ1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and \u003cspan refid=\"Equ2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The results, summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, shed light on the efficacy of drug delivery in different conditions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Equ1\" class=\"Equation\"\u003e \u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e\n$$\\:{{\\rm\\:E}}_{ad}=\\:{{\\rm\\:E}}_{\\text{G}\\text{P}\\text{F}}-\\:\\left({{\\rm\\:E}}_{\\text{F}\\text{A}\\text{V}\\:}+\\:{{\\rm\\:E}}_{\\:\\text{G}\\text{O}/\\text{P}\\text{E}\\text{G}}\\right)$$\u003c/div\u003e \u003cdiv class=\"EquationNumber\"\u003e1\u003c/div\u003e\u003c/div\u003e \u003cdiv id=\"Equ2\" class=\"Equation\"\u003e \u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ2\" name=\"EquationSource\"\u003e\n$$\\:{{\\rm\\:E}}_{DFT-D}=\\:{{\\rm\\:E}}_{DFT}+\\:{{\\rm\\:E}}_{Disp}$$\u003c/div\u003e \u003cdiv class=\"EquationNumber\"\u003e2\u003c/div\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eIn the given equation, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{{\\rm\\:E}}_{\\text{G}\\text{P}\\text{F}}\\)\u003c/span\u003e\u003c/span\u003e, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{{\\rm\\:E}}_{\\text{F}\\text{A}\\text{V}\\:}\\)\u003c/span\u003e\u003c/span\u003eand \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{{\\rm\\:E}}_{\\:\\text{G}\\text{O}/\\text{P}\\text{E}\\text{G}}\\)\u003c/span\u003e\u003c/span\u003e denote the energies of the drug-excipient system, the drug molecule, and the nanocarrier, respectively. Furthermore, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{{\\rm\\:E}}_{Disp}\\)\u003c/span\u003e\u003c/span\u003e, as proposed by Grimme, denotes the long-range dispersion correction energy.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn the case of the GF interactions, the adsorption energies varied significantly, among the phases, indicating the sensitivity of the system to environmental factors. In the gas phase, a moderate adsorption energy of -3.46 kcal/mol was observed, with an adsorption distance of 1.89 \u0026Aring;. However, in aqueous environments, a considerable enhancement in the adsorption energy was noted, with values dropping to -66.38 kcal/mol, suggesting a more favourable interaction between the drug and the carrier. This trend was consistent with the acidic and alkaline environments, where the adsorption energies further increased, reaching values of -202.61 kcal/mol and \u0026minus;\u0026thinsp;101.17 kcal/mol, respectively, indicating stronger interactions between FAV and GO.\u003c/p\u003e \u003cp\u003eOn the other hand, the incorporation of polyethylene glycol (PEG) onto the GO nanosheets, significantly altered the adsorption behaviour. In the gas phase, the adsorption energy for the GPF complex was notably higher (-27.69 kcal/mol) when compared to the GF interaction, indicating a stronger binding affinity, facilitated by the PEGylation. This trend persisted across all phases, with the most significant enhancement observed in acidic conditions, where the adsorption energy reached \u0026minus;\u0026thinsp;179.11 kcal/mol, highlighting the effectiveness of the PEGylation in the promotion of drug delivery under varying pH conditions. When examining the gas phase data alongside the available literature, it's evident that PAMAM dendrimers demonstrate a marginally reduced adsorption energy of -27.26 kcal/mol for the FAV in contrast to the PEGylated GO bionanocomposites, which was registered at -27.69 kcal/mol.[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eThe optimized 3D structures of the GF and GPF complexes, depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and S1, illustrate the structural arrangements of the system in different phases. These visualizations provide insights into the spatial orientation of the drug molecules within the nanocomposites, thereby, facilitating a better understanding of the adsorption mechanisms. The enhanced adsorption energies observed in the PEGylated systems, suggest their potential applications in optimizing the drug delivery strategies, particularly in the context of COVID-19 treatment, where efficient drug delivery is paramount for therapeutic efficacy.\u003c/p\u003e \u003cp\u003e \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\u003eSummary of the calculated adsorption energies and corresponding distances (\u003cem\u003ed\u003c/em\u003e) between FAV and the nanocomposite surfaces, charge transfer and release time of the complexes in the various phases\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\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=\"left\" 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=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpecies\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePhases\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eE\u003csub\u003ead\u003c/sub\u003e (Kcal/mol)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003ed\u003c/em\u003e\u003c/p\u003e \u003cp\u003e(\u0026Aring;)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAdsorption site\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eQ(e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eChi\u003c/p\u003e \u003cp\u003e(298 K)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eE\u003csub\u003emix\u003c/sub\u003e\u003c/p\u003e \u003cp\u003e(298 K)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\varvec{\\tau\\:}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003cp\u003e(ms)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eGF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003egas\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-3.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eN \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\to\\:\\)\u003c/span\u003e\u003c/span\u003e O\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e57.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e34.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:3.4\\:\\times\\:{10}^{-14}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ewater\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-66.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eN \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\to\\:\\)\u003c/span\u003e\u003c/span\u003e O\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e46.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e27.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:4.12\\:\\times\\:\\:{10}^{32}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eacidic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-202.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eN \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\to\\:\\)\u003c/span\u003e\u003c/span\u003e O\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.373\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e13.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e8.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:2.38\\:\\times\\:\\:{10}^{132}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ealkaline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-101.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e15.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e9.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:1.22\\:\\times\\:\\:{10}^{58}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eGPF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003egas\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-27.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e68.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e40.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:1.9\\:\\times\\:\\:{10}^{4}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ewater\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-19.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e68.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e40.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:2.71\\:\\times\\:\\:{10}^{-2}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eacidic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-179.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eN \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\to\\:\\)\u003c/span\u003e\u003c/span\u003e O\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.352\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e16.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e9.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:1.48\\:\\times\\:\\:{10}^{115}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ealkaline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-76.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eO \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\to\\:\\)\u003c/span\u003e\u003c/span\u003e H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-0.222\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e14.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e8.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:1.13\\:\\times\\:\\:{10}^{40}\\)\u003c/span\u003e\u003c/span\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 \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e3.1.2. Electrostatic Interactions and Charge Transfer Analysis\u003c/h2\u003e \u003cp\u003eThe investigation into the electrostatic interactions and charge transfer within the FAV (FAV) drug delivery system, elucidated crucial insights into the nature of the intermolecular forces, governing the stability and efficacy of PEGylated bionanocomposites.\u003c/p\u003e \u003cp\u003eAcross the different phases and configurations, the net charge on the FAV drug varied, indicating the influence of the environmental factors and the PEGylation on the charge distribution within the system (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). In the absence of PEGylation, the net charge on FAV was observed to be slightly negative in the gas phase (-0.008 e), while it became increasingly positive in the: aqueous (0.036 e), acidic (0.373 e), and alkaline (0.001 e) environments, when interacting with the GO nanocarriers. This trend suggests a shift in the charge distribution of the FAV molecules, induced by the interactions with the nanocarrier surface and environmental conditions.\u003c/p\u003e \u003cp\u003eUpon the PEGylation of the GO nanosheets, the charge distribution on FAV, exhibited further alterations. Notably, in the gas phase, the net charge on FAV, became slightly positive (0.008 e), indicating a reversal of the charge polarity, facilitated by the PEGylation. In aqueous and alkaline environments, a similar reversal was observed, with FAV exhibiting a slightly negative charge (-0.009 e and \u0026minus;\u0026thinsp;0.222 e, respectively), suggesting a nuanced interplay between the PEGylation process and the environmental factors in modulating charge transfer dynamics.\u003c/p\u003e \u003cp\u003eThe molecular electrostatic potential (MEP) maps, depicted in Figs.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e and S2, offer visual representations of the electrostatic potential distribution within the optimized GPF and GF complexes across the various phases. These maps reveal the distinct patterns of negative and positive electrostatic potentials, with negative potentials predominantly, localized around the oxygen atoms of the drug and carriers, while the positive potentials are concentrated around the carbon and hydrogen atoms. These observations underscore the significance of electrostatic interactions in mediating the binding affinity and stability of the drug-carrier complexes in different environments.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe variability in the charge distribution and the electrostatic potential maps, across phases and configurations, underscores the dynamic nature of intermolecular interactions within the PEGylated bionanocomposites. These findings provide valuable insights into the mechanisms that govern the drug-carrier interactions and hold implications for the optimization of the drug delivery strategies. By elucidating the role of the electrostatic interactions in mediating the drug adsorption and the release kinetics, the study advances the understanding of FAV delivery by using PEGylated graphene oxide nano-vehicles, thereby paving the way for its potential applications in antiviral treatment, where a precise control over drug delivery, is essential for therapeutic efficacy.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e\u003cem\u003e3.1.3\u003c/em\u003e. Non-covalent Interaction (NCI) of the FAV drug-GO nanocarrier systems\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe investigation into NCI within the FAV drug delivery system, provides crucial insights into the nature of the molecular interactions that govern the stability and efficacy of PEGylated bionanocomposites across different phases and configurations.\u003c/p\u003e \u003cp\u003eHerein, the reduced density gradient (RDG) is calculated by using Eq.\u0026nbsp;\u003cspan refid=\"Equ3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, providing insights into the electron density (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\rho\\:\\left(r\\right)\\)\u003c/span\u003e\u003c/span\u003e) distribution and the strength of the non-covalent interactions between the FAV molecules and the nanocomposite surfaces.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Equ3\" class=\"Equation\"\u003e \u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ3\" name=\"EquationSource\"\u003e\n$$\\:RDGs=\\:\\frac{1}{2{\\left(3{\\pi\\:}^{2}\\right)}^{\\frac{1}{3}}}\\frac{\\left|\\stackrel{-}{\\varDelta\\:\\rho\\:}\\left(r\\right)\\right|}{{\\stackrel{-}{\\rho\\:\\left(r\\right)}}^{\\frac{4}{3}}}$$\u003c/div\u003e \u003cdiv class=\"EquationNumber\"\u003e3\u003c/div\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe RDG isosurface maps and the scattered plots, depicted in Figs.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e, S3, and S4, offer the visual representations of the non-covalent interactions within the optimized GPF and GF complexes in various phases. These visualizations reveal the spatial distribution of the non-covalent interactions and provide insights into the nature and strength of the molecular bonding within the systems.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e summarizes the key findings regarding the non-covalent interactions between FAV and the nanocarrier surfaces in different phases. The analysis revealed distinct types of interactions, including strong hydrogen bonds and van der Waals forces, influencing the adsorption behaviour of FAV onto the nanocarrier surfaces.\u003c/p\u003e \u003cp\u003eIn the absence of PEGylation, GF interactions exhibited strong hydrogen bonds across all phases, with nitrogen atoms of the FAV, forming hydrogen bonds with the oxygen atoms on the nanocarrier surface. This interaction was particularly, prominent in the: gas, aqueous, and acidic environments, thereby, contributing to the significant adsorption energies observed in these phases. Conversely, in alkaline environments, the van der Waals forces dominated the interaction, leading to relatively weaker adsorption energies.\u003c/p\u003e \u003cp\u003eUpon the PEGylation of the GO nanosheets, the nature of the non-covalent interactions underwent certain alterations. In gas and aqueous phases, the van der Waals forces became the predominant mode of interaction, resulting in lower adsorption energies when compared to the GF interactions. However, in acidic environments, the strong hydrogen bonds persisted between FAV and the carrier surface, indicating the resilience of these interactions, in modulating the drug adsorption behaviour. Interestingly, in alkaline environments, a shift was observed, with the oxygen atoms of FAV, forming strong hydrogen bonds with the hydrogen atoms of the nanocarrier surfaces, highlighting the nuanced interplay between the environmental conditions and the molecular interactions.\u003c/p\u003e \u003cp\u003eThese findings provide valuable insights into the mechanisms underlying FAV delivery by using PEGylated graphene oxide nano-vehicles. By elucidating the role of the non-covalent interactions in mediating the drug-carrier interactions, the study advances the understanding of the factors that influence the drug adsorption and the release kinetics. Moreover, the identification of key interaction sites and types, offers the opportunities for rational a design and optimization of the drug delivery systems, tailored for specific environmental conditions.\u003c/p\u003e \u003cp\u003eThe implications of these findings for their potential applications in antiviral treatment, are profound. The ability to modulate the drug adsorption behaviour, through the precise control over the non-covalent interactions, opens-up, the avenues for developing targeted and efficient drug delivery strategies. By leveraging the unique properties, such as enhanced stability and biocompatibility, of PEGylated bionanocomposites, this research lays the groundwork for the development of novel therapeutics with improved efficacy and reduced side effects, thereby addressing the critical challenges associated with antiviral treatment.\u003c/p\u003e\u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Miscibility Study of the FAV drug-GO nanocarrier systems\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe miscibility of the complexes was investigated through a comprehensive analysis of the Chi parameter and the energy of the mixture (\u003cem\u003eE\u003c/em\u003e\u003csub\u003e\u003cem\u003emix\u003c/em\u003e\u003c/sub\u003e) in various environmental conditions. The study provides crucial insights into the interaction dynamics between the FAV drug molecules and the GO nanocarriers, which are essential for the optimization of drug delivery efficacy.\u003c/p\u003e \u003cp\u003eThe Chi parameter, indicative of the degree of miscibility between the components in a binary system, was evaluated as a function of temperature for GF and GPF complexes, across different phases, \u003cem\u003eviz\u003c/em\u003e the: gas, aqueous, acidic, and alkaline environments. As illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e, the Chi parameter exhibited a decreasing trend with increasing temperature in all the phases for both complexes. This temperature-dependent behaviour suggests an enhanced miscibility between FAV drug molecules and the nanocarrier surfaces, as the system transitioned to higher temperatures.\u003c/p\u003e \u003cp\u003eFurthermore, the binding configurations of the GPF complex were examined in the: gas, aqueous, acidic, and alkaline phases to elucidate the spatial arrangement of FAV molecules on the nanocomposite surface. Figures\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e and S5 illustrate the binding configurations of the GPF and GF complexes, which provide valuable insights into the intermolecular interactions that govern the drug-nanocarrier complexation process.\u003c/p\u003e \u003cp\u003eThe \u003cem\u003eE\u003c/em\u003e\u003csub\u003e\u003cem\u003emix\u003c/em\u003e\u003c/sub\u003e values, calculated at room temperature (298 K) by using Eq.\u0026nbsp;\u003cspan refid=\"Equ4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, provide quantitative assessments of the energy contributions from the drug-nanocarrier interactions, in the binary system. Tables\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and S1 summarize the Chi interaction parameter and the \u003cem\u003eE\u003c/em\u003e\u003csub\u003e\u003cem\u003emix\u003c/em\u003e\u003c/sub\u003e values for the GF and GPF complexes, across the different phases studied.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Equ4\" class=\"Equation\"\u003e \u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ4\" name=\"EquationSource\"\u003e\n$$\\:{E}_{mix}=\\frac{1}{2}z\\left({E}_{bs}+{E}_{sb}-{E}_{bb}-{E}_{ss}\\right)$$\u003c/div\u003e \u003cdiv class=\"EquationNumber\"\u003e4\u003c/div\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eIn all phases, higher Chi parameter values were observed for the GPF complex when compared to the GF counterpart, indicating an enhanced miscibility upon the PEGylation of the nanocarriers. Additionally, the \u003cem\u003eE\u003c/em\u003e\u003csub\u003e\u003cem\u003emix\u003c/em\u003e\u003c/sub\u003e values reflect the energetically favorable interactions between the FAV drug molecules and the nanocomposite surfaces, with higher \u003cem\u003eE\u003c/em\u003e\u003csub\u003e\u003cem\u003emix\u003c/em\u003e\u003c/sub\u003e values indicating strong binding affinity and improved stability of the drug-carrier complexes.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Release Mechanism of the FAV drug-GO nanocarrier systems\u003c/h2\u003e \u003cp\u003eThe release mechanism of FAV from GO nanocarriers, with and without PEG modification, was investigated across the various phases, i.e., the: gas, aqueous, acidic, and alkaline environments. The release time of the drug from the nanocarriers was determined, providing insights into the efficacy of the drug delivery systems for its potential applications in COVID-19 treatment.\u003c/p\u003e \u003cp\u003eThe adsorption energy (\u003cem\u003eE\u003c/em\u003e\u003csub\u003e\u003cem\u003ead\u003c/em\u003e\u003c/sub\u003e) of the drug on the GO-based nanocarriers, was found to influence the release time (τ), according to Eq.\u0026nbsp;(\u003cspan refid=\"Equ5\" class=\"InternalRef\"\u003e5\u003c/span\u003e), where higher adsorption energies correspond to longer release times. In the case of the GF complexes, the adsorption energies varied significantly, across the different phases, with the highest values observed in acidic environments, followed by alkaline, water, and gas phases (in that order). Conversely, the GPF complexes exhibited lower adsorption energies overall, indicating a potentially faster release kinetics, when compared to their GO-only counterparts.\u003cdiv id=\"Equ5\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ5\" name=\"EquationSource\"\u003e\n$$\\:\\tau\\:=\\:{v}_{0}^{-1}\\:\\:exp\\left(\\frac{{-E}_{b}}{KT}\\right)$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e5\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eIn this equation, T represents the temperature, k denotes Boltzmann's constant (~\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:1.99\\:\\times\\:{10}^{-3}\\)\u003c/span\u003e\u003c/span\u003e kcal/mol\u0026bull;K), and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{v}_{0}\\)\u003c/span\u003e\u003c/span\u003e stands for the frequency of the attempt. When utilizing the UV light for this application, the value of \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{v}_{0}\\)\u003c/span\u003e\u003c/span\u003e at room temperature, was found to be \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{10}^{12}\\)\u003c/span\u003e\u003c/span\u003e.[\u003cspan additionalcitationids=\"CR40 CR41 CR42\" citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e summarizes the release time of FAV from the GO nanocarriers in various phases. Notably, the release times span a wide range, from the orders of magnitude ranging between \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{10}^{-14}\\:\\text{t}\\text{o}\\:{10}^{132}\\)\u003c/span\u003e\u003c/span\u003e milliseconds. In this study, it is pertinent to note that release times greater than 10\u003csup\u003e8\u003c/sup\u003e milliseconds indicate a prolonged release, which may not be suitable for drug delivery at the target site.\u003c/p\u003e \u003cp\u003eIn the gas phase, both the GF and GPF complexes exhibited relatively short release times, suggesting efficient drug release kinetics in this environment. However, in the aqueous, acidic, and alkaline phases, the release times varied significantly, with the highest release times observed in acidic environments for both complexes. This implies the fact that the acidic environment can hinder the release of FAV from the nanocarriers, potentially impacting on its efficacy in acidic conditions, such as those found in certain physiological environments or diseased states. The observed recovery time for the FAV desorption from PAMAM (9.2 x 10\u003csup\u003e3\u003c/sup\u003e s) and polyester (4.2 x 10\u003csup\u003e3\u003c/sup\u003e s), are considerably, longer than that from PEGylated GO bionanocomposites, particularly in the gas and aqueous phases, making the material superior.[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eHence, the findings provide valuable insights into the release mechanism of FAV from the GO nanocarriers, highlighting the influence of environmental factors on the drug release kinetics. The shorter the release times observed in the presence of PEGylation suggests the potential of PEGylated graphene oxide nano-vehicles to enhance the drug delivery efficacy, by facilitating faster release kinetics. These insights contribute to a better understanding of FAV delivery by using nanocarrier systems and thus, have tangible implications for the development of more effective treatments for infectious diseases. By optimizing the drug delivery systems, based on GO nanocarriers, researchers can potentially, improve on the therapeutic outcomes of FAV and other antiviral drugs, thereby ultimately, aiding in the fight against infectious diseases.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.4. Thermodynamics of the FAV drug-GO nanocarrier systems\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eIn the thermodynamic analysis of the FAV drug-GO nanocarrier systems, across different phases, the changes in the Gibbs free energy (ΔG) and the enthalpy (ΔH), provide crucial insights into the stability and feasibility of drug delivery. These parameters were calculated at room temperature for each system, incorporating the finite temperature corrections (Equations \u003cspan refid=\"Equ6\" class=\"InternalRef\"\u003e6\u003c/span\u003e and \u003cspan refid=\"Equ7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e summarizes the changes in Gibbs free energy (ΔG, Kcal/mol) and enthalpy (ΔH, Kcal/mol) for the drug-excipient complexes in various environments.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Equ6\" class=\"Equation\"\u003e \u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ6\" name=\"EquationSource\"\u003e\n$$\\:{\\varDelta\\:G}^{298.15K}=627.51\\:\\left[{G}_{TCorr}^{298.15}\\:\\:\\left(complex\\right)-\\:\\left[{G}_{TCorr}^{298.15}\\:\\:\\left(excipient\\right)+\\:{G}_{TCorr}^{298.15}\\:\\:\\left(drug\\right)\\right]\\right]$$\u003c/div\u003e \u003cdiv class=\"EquationNumber\"\u003e6\u003c/div\u003e\u003c/div\u003e \u003cdiv id=\"Equ7\" class=\"Equation\"\u003e \u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ7\" name=\"EquationSource\"\u003e\n$$\\:{\\varDelta\\:H}^{298.15K}=627.51\\:\\left[{H}_{TCorr}^{298.15}\\:\\:\\left(complex\\right)-\\:\\left[{H}_{TCorr}^{298.15}\\:\\:\\left(excipient\\right)+\\:{H}_{TCorr}^{298.15}\\:\\:\\left(drug\\right)\\right]\\right]$$\u003c/div\u003e \u003cdiv class=\"EquationNumber\"\u003e7\u003c/div\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eIn the gas phase, the ΔG values for both GF and GPF complexes, indicate favorable interactions between the drug and the nanocarriers, with values of 16.95 Kcal/mol and \u0026minus;\u0026thinsp;10.62 Kcal/mol, respectively, for ΔG and ΔH. These negative ΔH values suggest spontaneous processes, indicating the likelihood of stable complexes formation. However, it is noteworthy that the enthalpy change (ΔH) for the GF complex, is positive (0.55 Kcal/mol), implying an endothermic behavior during the formation process. Conversely, the GPF complex exhibits an exothermic process with a negative ΔH value of -23.59 Kcal/mol, indicating an energy release scenario during the complex formation.\u003c/p\u003e \u003cp\u003eTransitioning to the aqueous phase, both complexes experience a significant decrease in the Gibbs free energy, indicating stronger interactions between the drug and nanocarriers in a water environment. The negative ΔG values (-52.43 Kcal/mol for GF and \u0026minus;\u0026thinsp;3.93 Kcal/mol for GPF) suggest thermodynamically, favorable conditions for drug delivery. However, the enthalpy change remains negative for GPF (-17.71 Kcal/mol), indicating an exothermic behavior, while GF displayed a highly negative ΔH (-68.83 Kcal/mol), indicating strong exothermic interactions.\u003c/p\u003e \u003cp\u003eIn acidic and alkaline environments, the thermodynamic parameters further highlight the stability of the drug-excipient complexes. Both the GF and GPF complexes, demonstrate negative ΔG values across these phases, indicating favorable conditions for drug encapsulation and release. The enthalpy changes also suggest exothermic processes, facilitating a complex formation in acidic (-203.64 Kcal/mol for GF and \u0026minus;\u0026thinsp;183.68 Kcal/mol for GPF) and in alkaline (-100.19 Kcal/mol for GF and \u0026minus;\u0026thinsp;68.7522 Kcal/mol for GPF) environments.\u003c/p\u003e \u003cp\u003eThese findings contribute significantly to the understanding of the behavior of FAV delivery by using PEGylated graphene oxide nano-vehicles across various phases. The positive ΔG values in the gas phase for GF, suggest the fact that without PEGylation, the interaction between the drug and the carrier may not be thermodynamically favorable. However, the incorporation of PEG, led to negative ΔG values across all phases, indicating an improved feasibility and a stability of the drug delivery system, especially in aqueous environments.\u003c/p\u003e \u003cp\u003eIn the context of its potential applications for antiviral treatment, these results underscore the importance of PEGylation in enhancing the efficacy of FAV delivery. By improving the thermodynamic parameters and thereby improving the stability of the drug-carrier complex, PEGylated graphene oxide nano-vehicles offer promising prospects for efficient drug delivery systems, particularly in aqueous environments that are relevant to biological systems. This enhanced stability and efficiency could potentially translate into improved therapeutic outcomes and efficacy in combating infectious diseases.\u003c/p\u003e \u003c/div\u003e \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\u003eThermodynamics energy parameters for various drug-excipient species in different phases\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpecies\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eE\u003csub\u003etot\u003c/sub\u003e\u003c/p\u003e \u003cp\u003e(Ha)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\varvec{H}}_{\\begin{array}{c}TCorr\\\\\\:\\:\\end{array}}^{298.15}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003cp\u003e(Ha)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\varvec{G}}_{\\begin{array}{c}TCorr\\\\\\:\\:\\end{array}}^{298.15}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003cp\u003e(Ha)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\varDelta\\:\\varvec{H}}^{298.15\\varvec{K}}\\)\u003c/span\u003e\u003c/span\u003e (Kcal/mol)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\varDelta\\:\\varvec{G}}^{298.15\\varvec{K}}\\)\u003c/span\u003e\u003c/span\u003e (Kcal/mol)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eGas\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFAV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-642.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-642.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-642.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-1538.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-1538.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1538.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGO/PEG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-1865.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-1865.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1865.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-2180.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-2180.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2180.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16.95\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGPF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-2507.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-2507.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2507.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-23.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-10.62\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAqueous\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFAV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-642.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-642.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-642.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-1538.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-1538.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1538.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGO/PEG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-1865.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-1865.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1865.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-2181.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-2180.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2180.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-68.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-52.43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGPF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-2507.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-2507.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2507.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-17.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-3.93\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAcidic\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFAV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-642.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-642.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-642.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-2181.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-2181.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2181.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-203.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-183.34\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGPF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-2508.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-2507.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2507.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-183.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-164.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAlkaline\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFAV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-641.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-641.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-641.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-2180.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-2179.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2179.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-100.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-84.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGPF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-2506.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-2506.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2506.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-68.7522\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-53.21\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=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.5. Electronic and Quantum Chemical Descriptors of the FAV drug-GO nanocarrier systems\u003c/h2\u003e \u003cp\u003eThe electronic and quantum chemical descriptors provide crucial insights into the molecular interactions and properties of the FAV drug-GO nanocarrier systems across various phases, shedding light on their potential for drug delivery applications.\u003c/p\u003e \u003cp\u003eThe frontier molecular orbitals, as depicted in Figs.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e and S6, offer a visual representation of the electronic structure and the reactivity of the complexes in different environments. These orbitals play a vital role in determining the interactions between the drug and the nanocarrier, thereby, influencing their stability and efficacy in drug delivery applications.\u003c/p\u003e \u003cp\u003eIn the gas and water phases, the HOMO and LUMO energies, predominantly, reside on the GO nanocarrier for both the GF and GPF complexes, indicating strong interactions between the drug and nano-vehicles. This suggests that GO serves as an effective carrier for FAV delivery, with the PEGylation process not significantly altering the electronic properties of these systems, in these environments.\u003c/p\u003e \u003cp\u003eMeanwhile, in acidic environments, a shift in the electronic structure is observed, particularly for the GF complex, where the LUMO is found on both the FAV drug and the GO molecules. This suggests a re-distribution of the electron density, due to the acid-induced changes in the nanocarrier's surface properties. Conversely, the GPF complex exhibits a different electronic configuration, with the LUMO, primarily residing on the FAV drug, indicating a distinct mode of interaction that was facilitated by the PEGylation.\u003c/p\u003e \u003cp\u003eIn alkaline environments, a further alteration in the electronic structure is evident, with the HOMO and LUMO energies, predominantly residing on the FAV drug for both the GF and GPF complexes. This suggests a shift in electron density towards the drug molecule, possibly due to alkaline-induced changes in the nanocarrier's surface charge or conformation.\u003c/p\u003e \u003cp\u003eFurthermore, the energy band gap (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{E}_{g}\\)\u003c/span\u003e\u003c/span\u003e) serves as a measure of the sensitivity of the nanostructure to chemical agents.[\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e] The percentage change in the \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{E}_{g}\\)\u003c/span\u003e\u003c/span\u003e (%∆\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{E}_{g}\\)\u003c/span\u003e\u003c/span\u003e) before and after the FAV adsorption, indicates the extent of the electronic restructuring upon drug loading. Across all the phases studied, a decrease in the \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{E}_{g}\\)\u003c/span\u003e\u003c/span\u003e, was observed after the drug adsorption, suggesting enhanced electrical conductivity and sensitivity of the nanocarriers to chemical agents. This phenomenon was more pronounced in the acidic and alkaline environments, where significant %∆\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{E}_{g}\\)\u003c/span\u003e\u003c/span\u003e values were observed, indicating a substantial electronic restructuring, upon FAV loading.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe calculated quantum descriptors (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), i.e., electron affinity (χ), chemical hardness (η), electronegativity (\u0026micro;), and softness (\u003cem\u003es\u003c/em\u003e), provide additional insights into the reactivity and stability of the complexes.[\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e] These descriptors help to elucidate the nature of intermolecular interactions, such as: charge transfer and non-covalent bonding, and hence, contributing to the overall understanding of the drug-nanocarrier interactions and their implications for drug delivery applications.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eComparatively, in the gas phase, both the GF and GPF complexes, exhibit similar values for the: electron affinity (χ), chemical hardness (η), and electronegativity (\u0026micro;), indicating comparable stability and reactivity of the systems/complexes.[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] However, the GPF exhibited a slightly higher softness (\u003cem\u003es\u003c/em\u003e) value when compared to GF, suggesting an increased susceptibility to electronic perturbations. In water, acidic, and alkaline environments, notable differences emerged, particularly in the chemical hardness (η) and the softness (\u003cem\u003es\u003c/em\u003e). In these environments, the GPF complex consistently, exhibited higher η and lower \u003cem\u003es\u003c/em\u003e values when compared to the GF complex, indicating enhanced stability and resistance to electron transfer. Moreover, the significant increase in η for the GPF complex in acidic and alkaline phases, suggests a greater resistance to chemical changes, and therefore, potentially enhancing its suitability for drug delivery applications in varying physiological conditions.\u003c/p\u003e \u003cp\u003eIn all, these findings contribute to the understanding of FAV delivery by using PEGylated graphene oxide nano-vehicles across various phases, which was achieved by the elucidation of the electronic interactions and structural changes, induced by different environmental conditions. The ability to predict and optimize the electronic properties of drug-nanocarrier complexes, offers significant insights into their stability and efficacy, and hence, facilitating the development of targeted drug delivery systems for COVID-19 treatment and other infectious diseases. Moreover, the significant %∆\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{E}_{g}\\)\u003c/span\u003e\u003c/span\u003e values obtained, underscore the potential of these nanocomposites for sensor and detection applications, highlighting their versatility far beyond drug delivery applications.\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\u003eQuantum descriptors of FAV Drug-GO nanocarrier complexes in different phases\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStructure\u003c/p\u003e \u003cp\u003econfiguration\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eE\u003csub\u003eHOMO\u003c/sub\u003e\u003c/p\u003e \u003cp\u003e(eV)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eE\u003csub\u003eLUMO\u003c/sub\u003e\u003c/p\u003e \u003cp\u003e(eV)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eE\u003csub\u003eg\u003c/sub\u003e\u003c/p\u003e \u003cp\u003e(eV)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eΔE\u003csub\u003eg\u003c/sub\u003e\u003c/p\u003e \u003cp\u003e(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\varvec{\\eta\\:}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003cp\u003e(eV)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026micro;\u003c/p\u003e \u003cp\u003e(eV)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003es\u003c/p\u003e \u003cp\u003e(eV)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\varvec{\\omega\\:}\\)\u003c/span\u003e\u003c/span\u003e (eV)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eECT\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGas\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFAV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-6.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-2.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-4.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e6.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-4.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-4.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-4.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e28.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGO/PEG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-4.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-3.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-4.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e27.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-4.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-3.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-10.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-4.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e29.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e10.79\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGPF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-4.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-3.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-5.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-4.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e28.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e10.47\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWater\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFAV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-6.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-2.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-4.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-4.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-3.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-4.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e27.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGO/PEG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-4.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-3.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-4.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e27.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-4.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-3.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-6.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-4.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e28.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e10.62\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGPF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-4.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-3.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-4.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-4.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e28.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e10.66\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAcidic\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFAV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-11.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-7.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-9.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e27.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-4.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-3.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-20.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-4.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e31.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e7.53\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGPF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-4.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-3.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e51.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-3.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e13.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e7.21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAlkaline\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFAV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-12.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-10.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-11.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e80.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-8.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-7.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e45.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-8.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e68.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.78\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGPF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-7.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-7.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-64.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-7.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e246.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-1.10\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=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.6. Theoretical IR and UV Spectra Analysis of the FAV drug-GO nanocarrier systems\u003c/h2\u003e \u003cp\u003eTheoretical spectroscopic analyses, including the IR and UV spectra (Figs.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003e and \u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003e), were conducted to characterize the interactions between FAV and PEGylated GO nanocarriers across different environments. The spectra obtained provide valuable insights into the structural changes and vibrational modes of the drug-nanocarrier complexes, shedding light on their potential for drug delivery applications, particularly in the context of COVID-19 treatment.\u003c/p\u003e \u003cp\u003eThe IR spectra of the PEG/GF complexes reveal significant shifts and intensity variations in the vibrational bands, indicating strong interactions between the drug and nanocarriers across different phases. In the gas phase, prominent peaks at wavenumbers of ~\u0026thinsp;3356.63 cm⁻\u0026sup1; and ~\u0026thinsp;1176 cm⁻\u0026sup1;, correspond to the stretching and bending vibrations of the O-H bonds in PEG, respectively, suggesting hydrogen bonding interactions with the FAV and GO molecules. In the aqueous phase, new peaks emerge at ~\u0026thinsp;3107.70 cm⁻\u0026sup1; and ~\u0026thinsp;1767.20 cm⁻\u0026sup1;, corresponding to the O-H stretching vibrations in water and the C\u0026thinsp;=\u0026thinsp;O stretching vibrations in FAV, indicating hydration and solvation effects. In acidic and alkaline environments, distinct peaks appear at ~\u0026thinsp;3425.41 cm⁻\u0026sup1; and ~\u0026thinsp;1806 cm⁻\u0026sup1;, respectively, suggesting the protonation and de-protonation of the functional groups, which further corroborate the pH-dependent behavior of the drug-nanocarrier complexes.\u003c/p\u003e \u003cp\u003eThe UV spectra of the GF and GPF complexes provide useful insights into the electronic transitions and energy levels of the drug-nanocarrier systems (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). In the gas phase, characteristic peaks at wavelengths 281.31 nm and 531.31 nm for GF, and 287.45 nm and 555.45 nm for GPF, indicating a π-π* transitions within the aromatic rings of the FAV and GO/PEG, respectively. In the aqueous phase, redshifts in the absorption peaks are observed, suggesting solvation effects and electronic restructuring upon interaction with water molecules. These spectral changes reflect the environmental dependence of the electronic transitions and energy levels in the drug-nanocarrier complexes, highlighting their potential for responsive drug delivery in physiological conditions.\u003c/p\u003e \u003cp\u003eThe theoretical spectroscopic analyses offer valuable insights into the structural and electronic properties of the FAV-loaded PEGylated graphene oxide nanocarriers, across different phases. Understanding of vibrational modes and electronic transitions, provides crucial information for optimizing drug delivery efficacy and stability. Moreover, the pH-dependent behavior observed in the IR spectra suggests its potential applications in targeted drug release in acidic tumor micro-environments or alkaline bacterial infections. The UV spectra reveal the environmental influences on the electronic transitions, facilitating the design of responsive drug delivery systems for COVID-19 treatment and other infectious diseases. Hence, these findings are significant enough to contribute to the development of effective and tailored drug delivery strategies, with implications for enhancing therapeutic outcomes and minimizing side effects in clinical applications.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \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\u003eUV Parameters for GF and GPF in gas and aqueous phases\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=\"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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpecies\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePhases\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLevel Energy (eV)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eExcitation (λ\u003csub\u003emax\u003c/sub\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eOscillator strength (f)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eGF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003egas\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e281.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e531.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e778.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ewater\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e260.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.90\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e426.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eGPF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003egas\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e287.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e555.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ewater\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e283.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e543.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.24\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"},{"header":"4. Conclusion","content":"\u003cp\u003eThe research on the predictive modeling of FAV drug delivery efficacy, through the first Principles simulation in PEGylated bionanocomposites, reveals significant insights. The study demonstrates the sensitivity of FAV interaction with nanocarriers to environmental conditions, with enhanced adsorption energies, observed in aqueous, acidic, and alkaline phases. The PEGylation of graphene oxide (GO) nanosheets, substantially improved the drug binding affinity, particularly in acidic environments, with the adsorption energies reaching \u0026minus;\u0026thinsp;179.11 kcal/mol. Analysis of the electrostatic interactions highlights a nuanced interplay between the PEGylation and the environmental factors that influence the charge distribution and stability of drug-carrier complexes. A non-covalent interaction analysis reveals strong hydrogen bonds and van der Waals forces, governing adsorption behavior, which are crucial for the optimization of drug delivery strategies. Miscibility studies demonstrate enhanced drug-nanocarrier interactions with increasing temperature, while the thermodynamics analysis underscores the stability and feasibility of drug encapsulation, particularly in aqueous environments. The electronic and quantum chemical descriptors provide insights into the electronic structure and the reactivity of the drug-nanocarrier complexes, with GPF exhibiting enhanced stability and resistance to electron transfer. Theoretical spectroscopic analyses corroborate the structural changes and the vibrational modes, further characterizing the drug-carrier interactions. Hence, the findings offer valuable implications for the optimization of drug delivery systems, particularly in the context of COVID-19 treatment, with PEGylated bionanocomposites, showing promise for enhanced therapeutic efficacy.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAUTHOR INFORMATION\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCorresponding Author\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGbolahan Joseph Adekoya\u003c/strong\u003e - \u003cem\u003eInstitute of Nanoengineering Research (INER), Department of Chemical, Metallurgical and Materials Engineering, Faculty of Engineering and the Built Environment, Tshwane University of Technology, Pretoria 0001, South Africa:\u003c/em\u003e\u003cem\u003ehttps://orcid.org/0000-0001-6381-0914\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eEmail: [email protected]\u003c/p\u003e\n\u003cp\u003eAuthors\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOluwasegun Chijioke Adekoya\u003c/strong\u003e - \u003cem\u003eInstitute of Nanoengineering Research (INER), Department of Chemical, Metallurgical and Materials Engineering, Faculty of Engineering and the Built Environment, Tshwane University of Technology, Pretoria 0001, South Africa\u003c/em\u003e; \u0026nbsp;https://orcid.org/0000-0002-5386-5919\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWanjun Liu\u0026nbsp;\u003c/strong\u003e- \u003cem\u003eKey Laboratory of Textile Science \u0026amp; Technology, Ministry of Education, College of Textiles, Donghua University, Shanghai 201620, China\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRotimi Emmanuel Sadiku\u003c/strong\u003e - \u003cem\u003eInstitute of Nanoengineering Research (INER), Department of Chemical, Metallurgical and Materials Engineering, Faculty of Engineering and the Built Environment, Tshwane University of Technology, Pretoria 0001, South Africa\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eYskandar Hamam\u003c/strong\u003e - \u003cem\u003eDepartment of Electrical Engineering, Faculty of Engineering and the Built Environment, Tshwane University of Technology, Pretoria 001, South Africa\u003c/em\u003e; \u0026nbsp;\u003cem\u003e\u0026Eacute;cole Sup\u0026eacute;rieure d\u0026rsquo;Ing\u0026eacute;nieurs en \u0026Eacute;lectrotechnique et \u0026Eacute;lectronique, Cit\u0026eacute; Descartes, 2 Boulevard Blaise Pascal, Noisy-le-Grand, Paris 93160, France\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics declarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study does not involve any clinical trial and therefore does not require registration in a clinical trial registry.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval and consent to participate:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo animal or human studies were carried out by the authors of this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable (no individual data or images are included)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data and materials are available upon request\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCredit authorship contribution statement:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOCA and GJA: Software, Data curation, Conceptualization, Methodology, Formal analysis; YH and ERS: Supervision, Validation, Writing-review \u0026amp; editing; WL: Writing - review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOCA and GJA would like to thank Center for High Performance Computing (CHPC), South Africa for access to computing resources. Additionally, OCA lovingly appreciates his wife, Omolola Felicia Adekoya, while GJA expresses deep gratitude to Oluwaferanmi Tiara Adekoya, with sincere thanks and affection from her father.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interest:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo funding was received for this study\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eDu, Y.X. and X.P. Chen, \u003cem\u003eFavipiravir: pharmacokinetics and concerns about clinical trials for 2019\u003c/em\u003e\u003cem\u003e‐nCoV infection.\u003c/em\u003e Clinical Pharmacology \u0026amp; Therapeutics, 2020. \u003cstrong\u003e108\u003c/strong\u003e(2): p. 242-247.\u003c/li\u003e\n\u003cli\u003eHassanipour, S., et al., \u003cem\u003eThe efficacy and safety of Favipiravir in treatment of COVID-19: a systematic review and meta-analysis of clinical trials.\u003c/em\u003e Scientific reports, 2021. \u003cstrong\u003e11\u003c/strong\u003e(1): p. 11022.\u003c/li\u003e\n\u003cli\u003eDeng, W., et al., \u003cem\u003eEvaluation of favipiravir in the treatment of COVID-19 based on the real-world.\u003c/em\u003e Expert review of anti-infective therapy, 2022. \u003cstrong\u003e20\u003c/strong\u003e(4): p. 555-565.\u003c/li\u003e\n\u003cli\u003eAbdelnabi, R., et al., \u003cem\u003eThe combined treatment of Molnupiravir and Favipiravir results in a potentiation of antiviral efficacy in a SARS-CoV-2 hamster infection model.\u003c/em\u003e EBioMedicine, 2021. \u003cstrong\u003e72\u003c/strong\u003e.\u003c/li\u003e\n\u003cli\u003eDriouich, J.-S., et al., \u003cem\u003eFavipiravir antiviral efficacy against SARS-CoV-2 in a hamster model.\u003c/em\u003e Nature Communications, 2021. \u003cstrong\u003e12\u003c/strong\u003e(1): p. 1735.\u003c/li\u003e\n\u003cli\u003eYamamura, H., et al., \u003cem\u003eEffect of favipiravir and an anti-inflammatory strategy for COVID-19.\u003c/em\u003e Critical Care, 2020. \u003cstrong\u003e24\u003c/strong\u003e(1): p. 413.\u003c/li\u003e\n\u003cli\u003eAgrawal, U., R. Raju, and Z.F. Udwadia, \u003cem\u003eFavipiravir: A new and emerging antiviral option in COVID-19.\u003c/em\u003e Medical Journal Armed Forces India, 2020. \u003cstrong\u003e76\u003c/strong\u003e(4): p. 370-376.\u003c/li\u003e\n\u003cli\u003eShah, P.L., et al., \u003cem\u003eFavipiravir in patients hospitalised with COVID-19 (PIONEER trial): a multicentre, open-label, phase 3, randomised controlled trial of early intervention versus standard care.\u003c/em\u003e The Lancet Respiratory Medicine, 2023. \u003cstrong\u003e11\u003c/strong\u003e(5): p. 415-424.\u003c/li\u003e\n\u003cli\u003eBazyari-Delavar, S., et al., \u003cem\u003ePAMAM and polyester dendrimers as favipiravir nanocarriers: a comparative study using DFT method.\u003c/em\u003e Journal of Nanoparticle Research, 2021. \u003cstrong\u003e23\u003c/strong\u003e(10): p. 231.\u003c/li\u003e\n\u003cli\u003eAlcantara, K.P., et al., \u003cem\u003eEnhanced nasal deposition and anti-coronavirus effect of favipiravir-loaded mucoadhesive chitosan\u0026ndash;alginate nanoparticles.\u003c/em\u003e Pharmaceutics, 2022. \u003cstrong\u003e14\u003c/strong\u003e(12): p. 2680.\u003c/li\u003e\n\u003cli\u003eXu, L., et al., \u003cem\u003eTemperature-Responsive Multilayer Films Based on Block Copolymer-Coated Silica Nanoparticles for Long-Term Release of Favipiravir.\u003c/em\u003e ACS Applied Nano Materials, 2021. \u003cstrong\u003e4\u003c/strong\u003e(12): p. 14014-14025.\u003c/li\u003e\n\u003cli\u003eGattani, V. and S. Dawre, \u003cem\u003eDevelopment of favipiravir loaded PLGA nanoparticles entrapped in in-situ gel for treatment of Covid-19 via nasal route.\u003c/em\u003e Journal of Drug Delivery Science and Technology, 2023. \u003cstrong\u003e79\u003c/strong\u003e: p. 104082.\u003c/li\u003e\n\u003cli\u003eReddy Obireddy, S., et al., \u003cem\u003eSynthesis and properties of alginate-based nanoparticles incorporated with different inorganic nanoparticulate modifiers for enhanced encapsulation and controlled release of favipiravir.\u003c/em\u003e Arabian Journal of Chemistry, 2023. \u003cstrong\u003e16\u003c/strong\u003e(7): p. 104751.\u003c/li\u003e\n\u003cli\u003eTulbah, A.S. and W.-H. Lee, \u003cem\u003ePhysicochemical Characteristics and In Vitro Toxicity/Anti-SARS-CoV-2 Activity of Favipiravir Solid Lipid Nanoparticles (SLNs).\u003c/em\u003e Pharmaceuticals, 2021. \u003cstrong\u003e14\u003c/strong\u003e(10): p. 1059.\u003c/li\u003e\n\u003cli\u003eAhangarani-Farahani, R., M.A. Bodaghifard, and S. Asadbegi, \u003cem\u003eMagnetic triazine-based dendrimer as a versatile nanocarrier for efficient antiviral drugs delivery.\u003c/em\u003e Scientific Reports, 2022. \u003cstrong\u003e12\u003c/strong\u003e(1): p. 19469.\u003c/li\u003e\n\u003cli\u003eXu, L., et al., \u003cem\u003eSteric Effects in the Deposition Mode and Drug-Delivering Efficiency of Nanocapsule-Based Multilayer Films.\u003c/em\u003e ACS Omega, 2022. \u003cstrong\u003e7\u003c/strong\u003e(34): p. 30321-30332.\u003c/li\u003e\n\u003cli\u003eAdekoya, O.C., et al., \u003cem\u003eA mini-review on the application of machine learning in polymer nanogels for drug delivery.\u003c/em\u003e Materials Today: Proceedings, 2022: p. 1-4.\u003c/li\u003e\n\u003cli\u003eSalawi, A., et al., \u003cem\u003eDevelopment of Statistically Optimized Chemically Cross-Linked Hydrogel for the Sustained-Release Delivery of Favipiravir.\u003c/em\u003e Polymers, 2022. \u003cstrong\u003e14\u003c/strong\u003e(12): p. 2369.\u003c/li\u003e\n\u003cli\u003eShrestha, D.B., et al., \u003cem\u003eFavipiravir versus other antiviral or standard of care for COVID-19 treatment: a rapid systematic review and meta-analysis.\u003c/em\u003e Virology Journal, 2020. \u003cstrong\u003e17\u003c/strong\u003e(1): p. 141.\u003c/li\u003e\n\u003cli\u003eXu, L., et al., \u003cem\u003eEnvironmentally Responsive Multilayer Films Based on Block Copolymer Micelles and Natural Peptides for Controlled Release of Favipiravir.\u003c/em\u003e Available at SSRN 4194451, 2022.\u003c/li\u003e\n\u003cli\u003eAdekoya, O.C., et al., \u003cem\u003eDensity Functional Theory Interaction Study of a Polyethylene Glycol-Based Nanocomposite with Cephalexin Drug for the Elimination of Wound Infection.\u003c/em\u003e ACS omega, 2022. \u003cstrong\u003e7\u003c/strong\u003e(38): p. 33808-33820.\u003c/li\u003e\n\u003cli\u003eCao, Y., et al., \u003cem\u003eCoronene surface for delivery of Favipiravir: Computational approach.\u003c/em\u003e Inorganic Chemistry Communications, 2022. \u003cstrong\u003e136\u003c/strong\u003e: p. 109133.\u003c/li\u003e\n\u003cli\u003eAdekoya, O.C., et al., \u003cem\u003eApplication of DFT Calculations in Designing Polymer-Based Drug Delivery Systems: An Overview.\u003c/em\u003e Pharmaceutics, 2022. \u003cstrong\u003e14\u003c/strong\u003e(9): p. 1972.\u003c/li\u003e\n\u003cli\u003eAl-Qargholi, B., et al., \u003cem\u003eNanosheets (CC-BC3-C3N) as an carrier for favipiravir drug: A density functional theory study.\u003c/em\u003e Inorganic Chemistry Communications, 2023. \u003cstrong\u003e150\u003c/strong\u003e: p. 110475.\u003c/li\u003e\n\u003cli\u003eSilva Arouche, T.d., et al., \u003cem\u003eInteractions between remdesivir, ribavirin, favipiravir, galidesivir, hydroxychloroquine and chloroquine with fragment molecular of the COVID-19 main protease with inhibitor N3 complex (PDB ID: 6LU7) using molecular docking.\u003c/em\u003e Journal of Nanoscience and Nanotechnology, 2020. \u003cstrong\u003e20\u003c/strong\u003e(12): p. 7311-7323.\u003c/li\u003e\n\u003cli\u003eAhmed, T., et al., \u003cem\u003eUnravelling the adsorption performance of BN, AlN, GaN and InN 2D nanosheets towards the ciclopirox, 5-fluorouracil and nitrosourea for anticancer drug delivery motive: A DFT-D with QTAIM, PCM and COSMO investigations.\u003c/em\u003e Computational and Theoretical Chemistry, 2022. \u003cstrong\u003e1214\u003c/strong\u003e: p. 113797.\u003c/li\u003e\n\u003cli\u003eDelley, B., \u003cem\u003eAn all\u003c/em\u003e\u003cem\u003e‐electron numerical method for solving the local density functional for polyatomic molecules.\u003c/em\u003e The Journal of Chemical Physics, 1990. \u003cstrong\u003e92\u003c/strong\u003e(1): p. 508-517.\u003c/li\u003e\n\u003cli\u003eSedlak, R., et al., \u003cem\u003eAccuracy of Quantum Chemical Methods for Large Noncovalent Complexes.\u003c/em\u003e Journal of Chemical Theory and Computation, 2013. \u003cstrong\u003e9\u003c/strong\u003e(8): p. 3364-3374.\u003c/li\u003e\n\u003cli\u003eCaldeweyher, E., C. Bannwarth, and S. Grimme, \u003cem\u003eExtension of the D3 dispersion coefficient model.\u003c/em\u003e The Journal of chemical physics, 2017. \u003cstrong\u003e147\u003c/strong\u003e(3): p. 034112.\u003c/li\u003e\n\u003cli\u003eGrimme, S., et al., \u003cem\u003eA consistent and accurate ab initio parametrization of density functional dispersion correction (DFT-D) for the 94 elements H-Pu.\u003c/em\u003e The Journal of Chemical Physics, 2010. \u003cstrong\u003e132\u003c/strong\u003e(15): p. 154104.\u003c/li\u003e\n\u003cli\u003eKlamt, A. and G. Sch\u0026uuml;\u0026uuml;rmann, \u003cem\u003eCOSMO: a new approach to dielectric screening in solvents with explicit expressions for the screening energy and its gradient.\u003c/em\u003e Journal of the Chemical Society, Perkin Transactions 2, 1993(5): p. 799-805.\u003c/li\u003e\n\u003cli\u003eXu, H., et al., \u003cem\u003eDFT study of nanotubes as the drug delivery vehicles of Efavirenz.\u003c/em\u003e Computational and Theoretical Chemistry, 2018. \u003cstrong\u003e1131\u003c/strong\u003e: p. 57-68.\u003c/li\u003e\n\u003cli\u003eSwietach, P., et al., \u003cem\u003eThe chemistry, physiology and pathology of pH in cancer.\u003c/em\u003e Philosophical transactions of the royal society B: biological sciences, 2014. \u003cstrong\u003e369\u003c/strong\u003e(1638): p. 20130099.\u003c/li\u003e\n\u003cli\u003eMollarasouli, F., N. Zare-Shehneh, and M. Ghaedi, \u003cem\u003eA review on corona virus disease 2019 (COVID-19): current progress, clinical features and bioanalytical diagnostic methods.\u003c/em\u003e Microchimica Acta, 2022. \u003cstrong\u003e189\u003c/strong\u003e(3): p. 103.\u003c/li\u003e\n\u003cli\u003eYapasert, R., P. Khaw-On, and R. Banjerdpongchai, \u003cem\u003eCoronavirus infection-associated cell death signaling and potential therapeutic targets.\u003c/em\u003e Molecules, 2021. \u003cstrong\u003e26\u003c/strong\u003e(24): p. 7459.\u003c/li\u003e\n\u003cli\u003eMcNellis, E.R., J. Meyer, and K. Reuter, \u003cem\u003eAzobenzene at coinage metal surfaces: Role of dispersive van der Waals interactions.\u003c/em\u003e Physical Review B, 2009. \u003cstrong\u003e80\u003c/strong\u003e(20): p. 205414.\u003c/li\u003e\n\u003cli\u003eFarzad, F. and H. Hashemzadeh, \u003cem\u003eProbing the effect of polyethene glycol on the adsorption mechanisms of Gem on the hexagonal boron nitride as a highly efficient polymer-based drug delivery system: DFT, classical MD and Well-tempered Metadynamics simulations.\u003c/em\u003e Journal of Molecular Graphics and Modelling, 2020. \u003cstrong\u003e98\u003c/strong\u003e: p. 107613.\u003c/li\u003e\n\u003cli\u003eGrimme, S., \u003cem\u003eDensity functional theory with London dispersion corrections.\u003c/em\u003e WIREs Computational Molecular Science, 2011. \u003cstrong\u003e1\u003c/strong\u003e(2): p. 211-228.\u003c/li\u003e\n\u003cli\u003eHosseinian, A., et al., \u003cem\u003eBenzoylethanamine drug interaction with the AlN nanosheet, nanotube and nanocage: Density functional theory studies.\u003c/em\u003e Thin Solid Films, 2017. \u003cstrong\u003e640\u003c/strong\u003e: p. 93-98.\u003c/li\u003e\n\u003cli\u003eBagheri, R., et al., \u003cem\u003eSi-doped phagraphene as a drug carrier for adrucil anti-cancer drug: DFT studies.\u003c/em\u003e Inorganic Chemistry Communications, 2018. \u003cstrong\u003e90\u003c/strong\u003e: p. 8-14.\u003c/li\u003e\n\u003cli\u003eOnsori, S. and E. Alipour, \u003cem\u003eA computational study on the cisplatin drug interaction with boron nitride nanocluster.\u003c/em\u003e Journal of Molecular Graphics and Modelling, 2018. \u003cstrong\u003e79\u003c/strong\u003e: p. 223-229.\u003c/li\u003e\n\u003cli\u003eNejati, K., et al., \u003cem\u003eA comparative DFT study on the interaction of cathinone drug with BN nanotubes, nanocages, and nanosheets.\u003c/em\u003e Applied Surface Science, 2017. \u003cstrong\u003e422\u003c/strong\u003e: p. 763-768.\u003c/li\u003e\n\u003cli\u003eWang, M. and C. Tang, \u003cem\u003eSilicon Doped Boron Carbide (BC\u003csub\u003e3\u003c/sub\u003e) Nanosheet as a Promising Sensitive Material for Detection of Acetaminophen Drug Based on the DFT Approach.\u003c/em\u003e Silicon, 2021. \u003cstrong\u003e14\u003c/strong\u003e(10): p. 5463-5470.\u003c/li\u003e\n\u003cli\u003eXiao, C., et al., \u003cem\u003eBorophene as an electronic sensor for metronidazole drug: A computational study.\u003c/em\u003e Journal of Molecular Graphics and Modelling, 2020. \u003cstrong\u003e96\u003c/strong\u003e: p. 107539.\u003c/li\u003e\n\u003cli\u003eRahimi, R. and M. Solimannejad, \u003cem\u003eBC\u003csub\u003e3\u003c/sub\u003e graphene-like monolayer as a drug delivery system for nitrosourea anticancer drug: A first-principles perception.\u003c/em\u003e Applied Surface Science, 2020. \u003cstrong\u003e525\u003c/strong\u003e: p. 146577.\u003c/li\u003e\n\u003c/ol\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":"DFT, Drug delivery, Favipiravir, Graphene oxide, Polyethylene glycol","lastPublishedDoi":"10.21203/rs.3.rs-4688547/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4688547/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis research investigates the drug delivery efficacy for 6-fluoro-3-hydroxy-2-pyrazinecarboxamide (Favipiravir) in PEGylated bionanocomposites using a predictive modelling approach. The study focuses on understanding the interaction mechanisms between Favipiravir (FAV) and polyethylene glycol (PEG)/graphene oxide (GO) (GO/PEG) nanosheets, across various environmental conditions. To evaluate drug delivery efficacy, the following key parameters were calculated: adsorption energies ranging from-202.61 to -3.46 kcal/mol indicating the strength of binding between the drug and nanocarrier; net charge transfer values between -0.222 to 0.373 electrons, reflecting the degree of charge migration; release times spanning a wide range from 3.4×10\u003csup\u003e−14\u003c/sup\u003e to 2.38×10\u003csup\u003e132\u003c/sup\u003e ms, which impacts the drug release kinetics; and thermodynamic parameters such as changes in Gibbs free energy (ΔG) between 183.34 and 16.95 kcal/mol, and changes in enthalpy (ΔH) between -203.64 and 0.55 kcal/mol, providing insights into the favorability and spontaneity of the drug-nanocarrier interactions. The results show that incorporating PEG onto GO nanosheets enhances adsorption energies and binding affinities for Favipiravir. Environmental factors and PEGylation influence the charge transfer and non-covalent interactions. PEGylation leads to faster Favipiravir release kinetics. Favorable thermodynamics are observed, especially in aqueous environments. Electronic properties, quantum descriptors, and theoretical spectra provide further insights into molecular interactions.\u003c/p\u003e","manuscriptTitle":"Predictive Modelling of 6-Fluoro-3-Hydroxy-2-Pyrazine Carboxamide Drug Delivery Efficacy in Pegylated Bionanocomposite Through First Principles Simulation","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-23 06:01:02","doi":"10.21203/rs.3.rs-4688547/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":"6b76e0e1-a243-4b9d-ad33-4ecde2663161","owner":[],"postedDate":"August 23rd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-01-07T07:54:48+00:00","versionOfRecord":[],"versionCreatedAt":"2024-08-23 06:01:02","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4688547","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4688547","identity":"rs-4688547","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}