Integrated Molecular Docking, DFT, ADME Profiling, and Cardiotoxicity Prediction of Artocarpin, Cycloartocarpin, Artocarpanone and Cyanomaclurin as Potential Antimalarial Agents

Integrated Molecular Docking, DFT, ADME Profiling, and Cardiotoxicity Prediction of Artocarpin, Cycloartocarpin, Artocarpanone and Cyanomaclurin as Potential Antimalarial Agents | 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 Integrated Molecular Docking, DFT, ADME Profiling, and Cardiotoxicity Prediction of Artocarpin, Cycloartocarpin, Artocarpanone and Cyanomaclurin as Potential Antimalarial Agents Neni Frimayanti, Armon Fernando, Miftahul Jannah, Abdi Wira Septama This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8615103/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 The escalating resistance of Plasmodium falciparum to existing antimalarial treatments necessitates the identification of novel medicines with enhanced efficacy and safety. This study utilized a comprehensive in silico approach to assess the potential of four flavonoids from Artocarpus heterophyllus î.e. artocarpin, cycloartocarpin, artocarpanone, and cyanomaclurin as inhibitors of P. falciparum dihydrofolate reductase–thymidylate synthase (PfDHFR-TS). Molecular docking demonstrated that artocarpin and cycloartocarpin displayed enhanced binding affinities and advantageous interaction patterns compared to chloroquine. Density functional theory and molecular electrostatic potential investigations corroborated their increased electronic reactivity and binding compatibility. ADME profiling demonstrated satisfactory drug-likeness properties; however, cardiotoxicity prediction revealed artocarpin and cycloartocarpin as non-hERG blockers, unlike chloroquine. Despite the anticipated mild toxicity hazards, the comprehensive computational data underscore artocarpin and cycloartocarpin as prospective lead scaffolds for subsequent optimization. These findings provide a compelling justification for the experimental validation and rational design of safer antimalarial medicines derived from A. heterophyllus. Malaria Artocarpus heterophyllus Molecular Docking DFT ADMET study Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Malaria continues to pose a major global health challenge, with Plasmodium falciparum responsible for the most severe and deadly infections. Although artemisinin-based combination therapies (ACTs) remain the cornerstone of treatment, the rapid rise in multidrug-resistant Plasmodium strains has significantly undermined their effectiveness [ 1 , 2 ]. This growing problem of resistance highlights the urgent need to discover new antimalarial agents, particularly those with novel mechanisms capable of bypassing existing resistance pathways. The tropical plant Artocarpus heterophyllus (jackfruit) has attracted considerable scientific attention because of its rich phytochemical profile and wide range of biological activities. Several flavonoid derivatives found in its heartwood, namely artocarpin, cycloartocarpin, artocarpanone, and cyanomaclurin, have been reported to exhibit antibacterial, antioxidant, antiviral, and anti-inflammatory effects. Notably, artocarpin also exhibits in vivo antimalarial activity. The structural resemblance of these flavonoids to other compounds known to disrupt Plasmodium metabolism further supports the possibility that they may serve as promising antimalarial agents [ 3 – 5 ]. One molecular target of particular interest is the Plasmodium falciparum dihydrofolate reductase–thymidylate synthase (PfDHFR-TS), which plays a central role in folate metabolism and nucleotide synthesis, which are vital for parasite survival. Although PfDHFR-TS has long been targeted by antifolate drugs such as pyrimethamine, widespread resistance has greatly reduced their therapeutic value [ 6 ]. Exploring natural compounds that can effectively bind to this enzyme offers a compelling strategy for overcoming resistant strains. Recent advances in computational chemistry have allowed researchers to investigate potential drug candidates more efficiently using in silico techniques. Molecular docking can predict the strength of binding of a compound to a target protein, whereas Density Functional Theory (DFT) provides insight into the electronic properties and reactivity of the molecule. Molecular Electrostatic Potential (MEP) mapping adds an additional layer of understanding by identifying the regions most likely to interact with the protein’s active site [ 7 – 9 ]. These methods, combined with drug-likeness and ADMET assessments, help evaluate whether a compound has the pharmacokinetic and safety characteristics required for further drug development. Given the therapeutic relevance of PfDHFR-TS and the diverse biological activities of Artocarpus -derived flavonoids, a comprehensive computational study is warranted. This study investigated the antimalarial potential of artocarpin, cycloartocarpin, artocarpanone, and cyanomaclurin using an integrated in silico approach, including molecular docking, DFT calculations, MEP visualization, and ADMET profiling. Through these analyses, we aimed to characterize the binding behavior, electronic features, and pharmacokinetic suitability of these compounds, ultimately identifying promising lead compounds for future antimalarial drug development. Research Methodology Molecular Docking In this study, four major phytochemical constituents of Artocarpus heterophyllus artocarpin, cycloartocarpin, artocarpanone, and cyanomaclurin [10] were selected as test ligands, with chloroquine serving as the reference drug. Ligand structures (Table 1) were drawn using ChemDraw Professional 15.0 and energy-minimized in MOE 2024.0901 to obtain optimized three-dimensional conformations. The crystal structure of Plasmodium falciparum dihydrofolate reductase–thymidylate synthase (PfDHFR-TS; PDB ID: 1J3I) was retrieved from the RCSB protein data bank and prepared using discovery studio visualizer by removing water molecules and heteroatoms, adding hydrogen atoms, repairing missing residues, and assigning partial charges. The structure was further protonated and energy-minimized in MOE before identifying the active site using Site Finder. Molecular docking was performed in MOE using the triangle matcher placement method and London dG scoring, followed by refinement with GBVI/WSA dG to generate and evaluate 100 binding poses for each ligand [11]. Density functional theory All structures were first drawn and converted into three-dimensional conformations using ChemDraw and MOE, followed by preliminary energy minimization. The optimized geometries were imported into the Gaussian software for quantum chemical analysis. DFT calculations were performed using the B3LYP hybrid functional with the 6-31G(d,p) basis set, which is a widely validated level of theory for evaluating molecular orbitals and electronic descriptors. For each ligand, the highest occupied molecular orbital (HOMO), lowest unoccupied molecular orbital (LUMO), energy gap (ΔE), dipole moment, and total electronic energy were obtained to assess their chemical reactivity and stability [12]. Molecular Electrostatic Potential (MEP) maps were subsequently generated from the DFT-optimized geometries using GaussView, allowing the identification of electrophilic and nucleophilic regions relevant to protein binding. These combined parameters, that is, HOMO–LUMO distribution, energy gap, charge density, and MEP patterns, were used to infer the electronic behavior of each compound and support the interpretation of the molecular docking results. Absortption, Distribution, Metabolism, Excretion (ADME) The pharmacokinetic and toxicity profiles of artocarpin, cycloartocarpin, artocarpanone, and cyanomaclurin were predicted using SwissADME, ADMETlab 3.0, and ProTox 3.0. The SMILES structure of each compound was submitted to SwissADME to evaluate the physicochemical properties, Lipinski compliance, lipophilicity, solubility, gastrointestinal absorption, and blood–brain barrier permeability. ADMETlab 3.0 was used to estimate pharmacokinetic parameters, including volume of distribution, clearance, CYP450 inhibition potential, and organ-specific toxicity. Acute toxicity (LD 50 ) and toxicity class were assessed using ProTox 3.0. All ADME outputs were integrated to determine the drug-likeness and preliminary safety profiles of the compounds as antimalarial candidates Cardiotoxicity Prediction Pred-hERG was used to evaluate cardiac toxicity using a probability map, prediction, and assurance of all compounds. The Pred-hERG provider aids users, using a fast, practical interface, for acknowledgment of hERG blockers and non-blockers [13]. Results and Discussion Molecular Docking Molecular docking was performed to predict the binding free energy and interaction between four major Artocarpus heterophyllus compounds i.e. artocarpin, cycloartocarpin, artocarpanone, and cyanomaclurin against the Plasmodium falciparum DHFR-TS enzyme (PDB ID: 1J3I). Chloroquine was used as positive control. Molecular docking results are presented in table 1. Docking simulations showed that artocarpin and cycloartocarpin has binding free energy of −9.506 and−9.407 kcal/mol, respectively. It were exhibited the strongest binding free energy toward PfDHFR-TS. Their values were notably better than those of artocarpanone and cyanomaclurin and were comparable or slightly superior to those of chloroquine. These findings indicate that the two prenylated flavonoids may have significant inhibitory potential against the DHFR domain, making them promising candidates for further antimalarial exploration. Table 1. Docking results Ligand Binding free energy RMSD Hydrogen bond Hydrophobic interaction Van der Waals interaction Other interaction Binding Factor Chloroquine -8.465 1.154 Phe58. Leu40 Lys49 Asp54 Ala16, Cys15 , Gly44, Gly165, Gly166, Ile14 , Ile112, Ile164, Leu46, Met55, Pro113, Ser108, Ser111, Tyr170, Val45 19 Cpd1 ( Artocarpin ) -9.506 1.596 Phe58, Asp54 Lys49 Asp54 Ala16, Cys15 , Gly41 , Gly44, Gly165, Gly166, Ile14 , Ile112, Ile164, Leu40, Leu46, Met55, Pro113, Ser108, Ser111, Val45, Val195 18 Cpd2 ( Cycloartocarpin ) -9.407 1.635 Leu46, Ser111 Lys49 Asp54 Ala16, Cys15 , Gly44, Gly165, Gly166, Ile14 , Ile112, Ile164, Leu40, Met55, Phe58, Ser108, Thr107 , Thr185 , Trp48 , Tyr57 , Tyr170, Val45 18 Cpd3 ( Artocarpanone ) -7.525 0.880 Asp54 , Gly165 Lys49 Asp54 Ala16, Cys15 , Gly166, Ile14 , Ile164, Leu40, Leu46, Met55, Phe58, Ser108, Thr185 , Trp48 , Tyr57 , Tyr170 14 Cpd4 ( Cyanomaclurin ) -6.777 0.843 Phe58 - Asp54 Ala16, Cys15 , Gly44, Gly165, Gly166, Ile14 , Ile112, Ile164, Leu40, Leu46, Met55, Ser108, Ser111, Ser167 , Tyr170, Val195 16 Note: Bold : The amino acid residues interacting with Cpd1–Cpd4 are identical to those interacting with the positive control Underline : catalytic triad The strong binding free energy observed for artocarpin and cycloartocarpin can be attributed to their ability to form several stabilizing interactions within the active site of the enzyme. Both compounds establish hydrogen bonds with key catalytic residues and are stabilized by extensive hydrophobic contacts deep inside the binding pocket. As shown in Figure 2, interactions with residues such as Ile14, Phe58, Cys59, and Gly44, which are frequently involved in DHFR inhibitor binding, play an important role in maintaining this stability. The presence of hydroxyl groups facilitates hydrogen bond formation, whereas the prenyl side chains contribute additional hydrophobic anchoring. These structural characteristics align well with established structure–activity relationship findings, indicating that prenylated flavonoids often exhibit enhanced binding performance due to increased lipophilicity and improved interactions with the target site [14]. Superimposition analysis (Figure 3) showed that artocarpin and cycloartocarpin adopted binding orientations that closely resembled those of chloroquine. Both compounds occupy similar regions within the active site and display comparable π–π stacking and hydrophobic interactions with the residues. This strong spatial overlap suggests that they may inhibit the enzyme through a similar mechanism, supporting the possibility that these compounds disrupt dihydrofolate reduction that a key process required for synthesis of nucleic acid in Plasmodium . Artocarpanone and cyanomaclurin exhibited lower binding free energy and also fewer stabilizing interactions with the PfDHFR-TS active site. Their binding conformations showed little spatial overlap with the reference ligand and were superficially positioned within the catalytic cavity. Their lower anticipated inhibitory potential is likely caused by their decreased hydrophobic surface area and decreased availability of hydrogen-bonding capabilities. Density Functional Theory (DFT) Density Functional Theory (DFT) calculations were conducted to systematically evaluate the electronic structures and reactivity profiles of chloroquine and the four principal compounds derived from Artocarpus heterophyllus , namely, artocarpin, cycloartocarpin, artocarpanone, and cyanomaclurin. The energies of the highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) were examined, along with the resulting HOMO–LUMO energy gap (ΔE). These quantum chemical parameters are widely recognized as key indicators of molecular stability, electronic reactivity, and propensity of compounds to engage in intermolecular interactions with biological targets. DFT parameter of chloroquine and A. heterophyllus compounds are presented in Table 2. Table 2. DFT results compound Total energy (a.u) Momen Dipol (Debye) electronic Energy Gap (ΔE) HOMO LUMO Chloroquine (positive control) -1326.032 4.937 -0.198 -0.315 0.117 Artocarpin -1458.906 5.686 -0.184 -0.311 0.127 Cycloartocarpin -1457.712 6.619 -0.194 -0.304 0.110 Artocarpanone -1069.466 3.332 -0.171 -0.308 0.137 Cyanomaclurin -1030.129 1.086 -0.154 -0.304 0.150 DFT analysis revealed distinct differences in the electronic characteristics of the examined compounds. Among the A. heterophyllus derivatives, cycloartocarpin exhibited the smallest HOMO–LUMO energy gap (0.110), followed closely by artocarpin (0.127). A reduced energy gap is commonly associated with increased electronic reactivity and enhanced molecular polarizability, indicating a greater propensity for these compounds to engage in charge transfer interactions with biological macromolecules. This electronic behavior may contribute to the favorable interaction profiles observed in subsequent molecular docking analyses [15] . The comparatively low HOMO–LUMO energy gaps (ΔE) observed for artocarpin and cycloartocarpin reflect favorable electronic properties consistent with their strong binding affinities identified in molecular docking analyses. This concordance suggests a meaningful relationship between electronic reactivity and binding efficiency, thereby strengthening the rationale for considering these compounds as potential PfDHFR-TS inhibitors [16]. However, artocarpanone and cyanomaclurin exhibited relatively larger energy gaps, indicating greater molecular stability but diminished electronic reactivity, which may underlie their comparatively weaker docking interactions. The visualization of the frontier molecular orbitals (Figure 4) revealed that the HOMO distributions of artocarpin and cycloartocarpin were predominantly localized on oxygen-containing functional groups, particularly hydroxyl moieties. Therefore, these regions are likely to act as electron-donating sites during ligand–protein interactions. In contrast, the LUMO distributions were primarily delocalized over the aromatic frameworks and prenylated substituents, indicating their potential role as electron-accepting regions when interacting with electrophilic residues within the enzyme active site. The observed spatial distributions of the HOMO and LUMO orbitals were consistent with the interaction patterns identified in the molecular docking simulations, in which the hydroxyl functional groups predominantly contributed to hydrogen bond formation, whereas the prenyl substituents enhanced the hydrophobic interactions within the PfDHFR-TS active site. This concordance between the electronic features derived from DFT analysis and docking interaction profiles reinforces the robustness and reliability of in silico predictions. Molecular Electrostatic Potential (MEP) Molecular Electrostatic Potential (MEP) analysis was performed to characterize the charge distribution and electrostatic properties of chloroquine and the four compounds derived from Artocarpus heterophyllus . MEP mapping offers important insights into molecular regions that are predisposed to electrophilic or nucleophilic interactions, thereby providing a mechanistic understanding of how these compounds recognize and interact with protein targets [17]. As depicted in Figure 5, all evaluated compounds exhibited distinct regions of negative electrostatic potential, predominantly localized around the oxygen atoms, particularly those associated with hydroxyl and carbonyl functional groups. These electron-rich regions are characteristic of sites capable of acting as hydrogen-bond acceptors and are therefore likely to play a key role in stabilizing interactions with amino acid residues within the PfDHFR-TS active-site. Conversely, regions of positive electrostatic potential were primarily distributed over hydrogen-rich alkyl chains and aromatic moieties, indicating electron-deficient areas that may participate in complementary electrostatic interactions during ligand–protein-binding. All the analyzed compounds exhibited well-defined regions of negative electrostatic potential, predominantly localized around the oxygen atoms, particularly those associated with hydroxyl and carbonyl functional groups [18]. These electron-rich regions represent potential hydrogen-bond acceptor sites and are therefore likely to contribute significantly to stabilizing interactions with amino acid residues within the PfDHFR-TS active site. Conversely, regions of positive electrostatic potential were primarily distributed over hydrogen-rich alkyl chains and aromatic moieties, indicating electron-deficient areas that may participate in complementary electrostatic interactions during ligand–protein-binding. Artocarpin and cycloartocarpin exhibited well-defined regions of negative electrostatic potential predominantly localized around their hydroxyl functional groups, in agreement with the strong hydrogen-bonding interactions observed in the molecular docking simulations. The presence of prenyl substituents contributed to regions of relatively neutral to mildly positive electrostatic potential, which may favor hydrophobic interactions within the enzyme-binding pocket. This combination of complementary electrostatic and hydrophobic characteristics is likely to enhance both binding complementarity and complex stability. Table 3 are presented the electrostatic features derived from MEP analysis. Table 3. Electrostatic features based on MEP analysis Compounds Predominant Negative Potential Regions Predominant Positive Potential Regions Key functional Groups involved Chloroquine Nitrogen atom Alkyl chain Amine group Artocarpin Oxygen atom Aromatic region Hydroxyl group Cycloartocarpin Oxygen atom Aromatic region Hydroxyl group Artocarpanone Oxygen atom Aromatic region Carbonyl and hydroxyl group Cyanomaclurin Oxygen atom Aromatic region Multiple hydroxyl group Artocarpanone and cyanomaclurin exhibited broader but less distinctly localized regions of negative electrostatic potential, indicating a more evenly distributed electron density across their molecular frameworks. Although these electrostatic features remain compatible with hydrogen bond formation, the less concentrated potential distribution may partially account for their comparatively weaker binding affinities relative to artocarpin and cycloartocarpin. Absortption, Distribution, Metabolism, Excretion (ADME) In silico ADME analysis was performed to systematically evaluate the pharmacokinetic characteristics and drug-likeness of artocarpin, cycloartocarpin, artocarpanone, and cyanomaclurin. Assessing these parameters is essential for estimating the translational viability of bioactive compounds beyond their target-binding performance. The predicted ADME profiles are summarized in Table 4. All four compounds exhibited high predicted oral bioavailability and favorable gastrointestinal absorption, indicating suitable permeability for oral administration. Compliance with Lipinski’s rule of five further supports the classification of these compounds as drug-like molecules. Moreover, key physicochemical parameters, including molecular weight and lipophilicity, were within acceptable ranges, suggesting a balanced profile between aqueous solubility and membrane permeability [19]. Table 4. Drug-likeness and ADMET Parameter Result Chloroquine Artocarpin Cycloartocarpin Artocarpanone Cyanomaclurin Lipinski Yes Yes Yes Yes Yes Molecular weight (g/mol) 319.18 436.50 434.48 302.28 288.25 H -bond acceptor 3 6 6 6 6 H -bond donor 1 3 2 3 4 Log P 4.733 4.14 4.31 2.01 1.25 TPSA (Å) 28.16 100.13 89.13 96.22 99.38 Ghose No Yes Yes Yes Yes Veber Yes Yes Yes Yes Yes Egan Yes Yes Yes Yes Yes Muegge Yes No No Yes Yes Human Intestinal Absorption (HIA) 0 0.081 0.052 0.006 0 Caco-2 permeability (log cm/s) -4.981 -5.146 -5.098 -4.989 -6.048 P-glycoprotein inhibitor 0.088 0.978 0.654 0.798 0.013 P-glycoprotein substrate 0.849 0.029 0.035 0.032 0.934 F20% 0.001 0.904 0.93 0.011 0.57 F30% 0 0.99 0.989 0.666 0.98 Plasma Protein Binding (PPB) (%) 49.61 96.994 97.912 91.82 91.499 Blood-Brain Barrier Penetration (BBB) 0.961 0 0 0.005 0.041 Volume distribution (L/kg) 1.076 0.238 0.053 0.058 0.143 Fraction unbound (Fu)(%) 56.319 3.036 2.093 9.118 9.994 CYP1A2 substrate 0.093 0 0.157 0.964 0.05 CYP1A2 inhibitor 0 0.481 0.748 0.998 0 CYP2C19 substrate 0.732 0.988 0.913 0.005 0.537 CYP2C19 inhibitor 0 1.0 0.996 0.996 0.097 CYP2C9 substrate 0 0.009 0.092 0.893 1.0 CYP2C9 inhibitor 0 1.0 0.994 0.907 0.02 CYP2D6 substrate 0.374 0,074 0,009 0,955 0,707 CYP2D6 inhibitor 0.006 0.017 0.008 0.618 0 CYP3A4 substrate 0 0.716 0.97 0.802 0 CYP3A4 inhibitor 0 0.834 0.98 0.955 0 Half time (t1/2) 0.561 1.574 1.236 1.657 2.643 Clearance (mL/min/kg) 5.666 2.28 4.601 2.841 7.719 Human hepatotoxicity (H-HT) 0.727 0.693 0.831 0.611 0.653 hERG blockers 0.958 0.085 0.132 0.119 0.138 Rat oral acute toxicity 0.796 0.537 0.371 0.564 0.436 AMES toxicity 0.512 0.34 0.483 0.679 0,.88 Drug Induced Liver Injury (DILI) 0525 0.717 0.932 0.499 0.503 Carcinogencity 0.204 0.359 0.732 0.672 0.371 All four compounds were predicted to exhibit moderate to high levels of acute oral toxicity in the rat model, along with an associated risk of hepatotoxicity and carcinogenicity. These results indicate that, despite their promising antimalarial potential, as suggested by molecular docking and electronic structure analyses, the safety profiles of these compounds may present substantial challenges for their direct advancement as therapeutic agents. Prediction of toxicity value for all compounds are listed in Table 5. Table 5. Toxicity prediction Compound LD 50 To xicity class Hepatoto xicity Chloroquine 750 nmg/kg Class 4 low toxicity Inactive (0,65) Artocarpin 4000 mg/kg Class 5 Very low toxicity Inactive (0,68) Cycloartocarpin 475 mg/kg Class 4 low toxicity Inactive (0,67) Artocarpanone 2000 mg/kg Class 4 low toxicity Inactive (0,71) Cyanomaclurin 2500 mg/kg Class 5 Very low toxicity Inactive (0,80) The prediction of hepatotoxicity deserves particular attention, given the central role of the liver in drug metabolism and detoxification processes. Compounds with hepatotoxic potential may accumulate in liver tissue or be converted into reactive metabolites, ultimately causing cellular damage in the liver. This concern is supported by the low predicted clearance values observed in the ADME analysis, which suggests prolonged systemic exposure and, consequently, an increased likelihood of toxicity [20]. Although these toxicity concerns are important, they do not necessarily rule out further developments. Many biologically active natural products initially exhibit safety liabilities that can be reduced through structural refinement, targeted modification of functional groups, or appropriate formulation approaches. Artocarpin and cycloartocarpin, which exhibited the most favorable binding affinities and electronic characteristics, represent promising lead scaffolds for developing safer and more selective antimalarial derivatives. Cardiotoxicity Prediction Cardiotoxicity, defined as drug-induced damage to cardiac tissue, represents a major challenge in pharmaceutical development and is a leading cause of late-stage drug attrition during both preclinical and clinical evaluation. Because interference with cardiac electrophysiology can result in life-threatening arrhythmias, cardiotoxicity remains one of the most serious and closely monitored adverse effects in new drug candidates [21]. The cardiac safety profile of the studied compounds was therefore evaluated using the PRED-hERG model, and the results are summarized in Table 6. This computational model provides a reliable assessment of a compound’s likelihood to interact with the hERG potassium channel, a key regulator of cardiac repolarization. By predicting hERG liability, this analysis offers important insight into the potential cardiac risks associated with the investigated chemical entities. This classification provides an estimate of the likelihood that the tested compounds may inhibit the hERG channel, an event that can trigger potentially life-threatening cardiac arrhythmias. The reliability of each prediction is indicated by the “Confidence (%)” value reported by the model. In addition, the “Applicability Domain” parameter is critical for interpreting these results, as it reflects whether a compound falls within the chemical space on which the model was trained. Notably, cycloartocarpin and cyanomaclurin listed in Table 4 lie outside the model’s applicability domain, which introduces a degree of uncertainty and suggests that the predictions should be interpreted with caution. The predicted cardiotoxic profiles of ligands are summarized in Table 4, including their confidence scores, applicability domains, potency classifications, and associated reliability within those domains. As cardiotoxicity reflects a compound’s potential to disrupt normal cardiac function or cause myocardial injury, it represents a critical safety concern in drug discovery and development. Chloroquine, used as a reference compound, was predicted to be a hERG blocker with exceptional reliability (99.5 %), corroborating its well-established cardiotoxic potential. The model designated chloroquine within the applicability domain, reflecting a high degree of confidence in this prediction [22]. The predicted IC₅₀ value of 5.579 further corroborates its robust interaction with the hERG channel, aligning with clinical findings of QT prolongation and arrhythmogenic risk associated with chloroquine treatment. Artocarpin, cycloartocarpin, and artocarpanone were all anticipated to be non-inhibitors of the hERG channel. Cycloartocarpin had the highest confidence, with a binary reliability of 95.76%, followed by artocarpanone (77.74 %) and artocarpin (76.27 %). Significantly, all three substances were categorized within the applicability domain, signifying that their chemical characteristics reside within the validated prediction space of the model and that their anticipated safety profiles are dependable. Their anticipated IC₅₀ values (5.192–5.327) were marginally lower than those of chloroquine, indicating diminished or less functionally significant interactions with the hERG channel. Conclusions This study demonstrates that flavonoids derived from Artocarpus heterophyllus, specifically artocarpin and cycloartocarpin, exhibit significant in silico inhibitory efficacy against Plasmodium falciparum DHFR-TS. Combined molecular docking and quantum chemistry investigations showed that the enzyme's active site had good binding affinities, electronic reactivity and complementary interaction patterns. Predicting cardiotoxicity showed that neither chemical was a hERG blocker, which means that they are safer for the heart than chloroquine. Although moderate toxicity risks are expected, these constraints can be addressed through logical structure optimization. In summary, these results suggest that artocarpin and cycloartocarpin are promising candidates for further research and the development of antimalarial drugs. Declarations Data Availability No datasets were generated or analysed during the current study. Acknowledgment We express out gratitude for the support received from the Ministry of Education, Culture, Research and Technology of the Republic of Indonesia for research funding through Grant No 022/LL17/DT.05.00/ PL/2025 Author Contribution All authors contributed to the research design, collection, analysis, and interpretation of data. The first draft of the manuscript was written by Neni Frimayanti. All authors commented on the previous drafts of the paper. All authors read and approved the final manuscript. Conflict of Interest The authors declare that they have no known competing financial interests or personal relationships that could appear to have influenced the research reported in this paper. References Alghamdi JM, Al-Qahtani AA, Alhamlan FS, Al-Qahtani AA. Recent Advances in the Treatment of Malaria. Pharmaceutics. 2024 Nov 4;16(11):1416. doi: 10.3390/pharmaceutics16111416 Sanyaolu, A., Marinkovic, A., Prakash, S., Balendra, V., Shazley, O., Gardellini, T., Jan, A., Younis, K., Okorie, C., & Izurieta, R. (2025). Emerging Molecular Mechanisms in Malaria Pathogenesis and Novel Therapeutic Approaches: A Focus on P. falciparum Malaria. Biomolecules, 15(7), 1038. https://doi.org/10.3390/biom15071038 Liu X, Zhang Z, Wang J, Wang X, Bi H, Wang M. Recent developments in Artocarpus heterophyllus Lam. (jackfruit) polysaccharides: Nutritional values, structural characteristics and health benefits. Int J Biol Macromol. 2025 May;309(Pt 2):142923. doi: 10.1016/j.ijbiomac.2025.142923 Nansereko, Sophie, and John. H. Muyonga. 2021. “Exploring the Potential of Jackfruit (Artocarpus Heterophyllus Lam)”. Asian Food Science Journal 20 (9):97-117. https://doi.org/10.9734/afsj/2021/v20i930346. Kumar, A., Mishra, A., & Singh, A. (2022). Phytochemistry, pharmacological, medicinal significance of Artocarpus heterophyllus Lam. (Jackfruit). International Journal of Health Sciences , 6 (S5), 6578–6590. https://doi.org/10.53730/ijhs.v6nS5.10134 Biswas P, Roy R, Ghosh K, Nath D, Samadder A, Nandi S. To quest new targets of Plasmodium parasite and their potential inhibitors to combat antimalarial drug resistance. J Parasit Dis. 2024 Dec;48(4):671-722. doi: 10.1007/s12639-024-01687-x. Ouma, R.B.O., Ngari, S.M. & Kibet, J.K. A review of the current trends in computational approaches in drug design and metabolism. Discov Public Health 21, 108 (2024). https://doi.org/10.1186/s12982-024-00229-3 Albratty M, Thangavel N, Chandrasekaran B, Meraya AM, Alhazmi HA, Muthumanickam S, Boomi P, Bhagavan NB, Saleh SF (2024) Benchmarking docking, density functional theory and molecular dynamics studies to assess the aldose reductase inhibitory potential of Trigonella foenum-graecum compounds for managing diabetes-associated complications. Pharmacia 71: 1-10. https://doi.org/10.3897/pharmacia.71.e118949 Tahiroğlu, V., Gören, K. & Bağlan, M. In Silico drug evaluation by molecular docking, ADME studies and DFT calculations of 2-(6-chloro-2-(4-chlorophenyl)imidazo[1,2-a]pyridin-3-yl)-N, N-dipropylacetamide. BMC Pharmacol Toxicol 26, 116 (2025). https://doi.org/10.1186/s40360-025-00958-4 Septama AW, Panichayupakaranant P. Antibacterial assay-guided isolation of active compounds from Artocarpus heterophyllus heartwoods. Pharm Biol. 2015;53(11):1608-13. doi: 10.3109/13880209.2014.996819. Abookleesh, F., Mosa, F. E. S., Barakat, K., & Ullah, A. (2022). Assessing Molecular Docking Tools to Guide the Design of Polymeric Materials Formulations: A Case Study of Canola and Soybean Protein. Polymers , 14 (17), 3690. https://doi.org/10.3390/polym14173690 Işık A, Acar Çevik U, Karayel A, Ahmad I, Patel H, Çelik İ, Gül ÜD, Bayazıt G, Bostancı HE, Koçak A, Özkay Y, Kaplancıklı ZA. Synthesis, DFT Calculations, In Silico Studies, and Antimicrobial Evaluation of Benzimidazole-Thiadiazole Derivatives. ACS Omega. 2024 Apr 9;9(16):18469-18479. doi: 10.1021/acsomega.4c00543. Khan MA, Mutahir S, Jabar G, Wenwei Z, Tariq MA, Almehizia AA, Mustafa M. DFT, Molecular Docking, ADME, and Cardiotoxicity Studies of Persuasive Thiazoles as Potential Inhibitors of the Main Protease of SARS-CoV-2. Chem Biodivers. 2024 Dec;21(12):e202401775. doi: 10.1002/cbdv.202401775 Michel J, Tirado-Rives J, Jorgensen WL. Energetics of displacing water molecules from protein binding sites: consequences for ligand optimization. J Am Chem Soc. 2009 Oct 28;131(42):15403-11. doi: 10.1021/ja906058w. Mumit MA, Pal TK, Alam MA, Islam MA, Paul S, Sheikh MC. DFT studies on vibrational and electronic spectra, HOMO-LUMO, MEP, HOMA, NBO and molecular docking analysis of benzyl-3-N-(2,4,5-trimethoxyphenylmethylene)hydrazinecarbodithioate. J Mol Struct. 2020 Nov 15;1220:128715. doi: 10.1016/j.molstruc.2020.128715. Blankevoort N, Bastante P, Davidson RJ, Salthouse RJ, Daaoub AHS, Cea P, Solans SM, Batsanov AS, Sangtarash S, Bryce MR, Agrait N, Sadeghi H. Exploring the Impact of the HOMO-LUMO Gap on Molecular Thermoelectric Properties: A Comparative Study of Conjugated Aromatic, Quinoidal, and Donor-Acceptor Core Systems. ACS Omega. 2024 Feb 5;9(7):8471-8477. doi: 10.1021/acsomega.3c09760. Noureddine O, Issaoui N, Al-Dossary O. DFT and molecular docking study of chloroquine derivatives as antiviral to coronavirus COVID-19. J King Saud Univ Sci. 2021 Jan;33(1):101248. doi: 10.1016/j.jksus.2020.101248 Martínez-Cifuentes, M., Weiss-López, B. E., Santos, L. S., & Araya-Maturana, R. (2014). Intramolecular Hydrogen Bond in Biologically Active o -Carbonyl Hydroquinones. Molecules , 19 (7), 9354-9368. https://doi.org/10.3390/molecules19079354 Lipinski CA. Lead- and drug-like compounds: the rule-of-five revolution. Drug Discov Today Technol. 2004 Dec;1(4):337-41. doi: 10.1016/j.ddtec.2004.11.007. Kim, Y., Kim, H. & Kim, Y. Advancing hepatotoxicity assessment: current advances and future directions. Toxicol Res. 41, 303–323 (2025). https://doi.org/10.1007/s43188-025-00289-w Mamoshina P, Rodriguez B, Bueno-Orovio A. Toward a broader view of mechanisms of drug cardiotoxicity. Cell Rep Med. 2021 Mar 16;2(3):100216. doi: 10.1016/j.xcrm.2021.100216. Jordaan P, Dumotier B, Traebert M, Miller PE, Ghetti A, Urban L, Abi-Gerges N. Cardiotoxic Potential of Hydroxychloroquine, Chloroquine and Azithromycin in Adult Human Primary Cardiomyocytes. Toxicol Sci. 2021 Apr 12;180(2):356-368. doi: 10.1093/toxsci/kfaa194 Table Table 6 is available in the Supplementary Files section. Additional Declarations No competing interests reported. Supplementary Files Table6.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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1","display":"","copyAsset":false,"role":"figure","size":58435,"visible":true,"origin":"","legend":"\u003cp\u003eSturucture ligand\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8615103/v1/f32d42d89cb0e4d074d89998.png"},{"id":100544394,"identity":"4c9f74af-9636-4edf-85e8-68166bc5441f","added_by":"auto","created_at":"2026-01-19 06:15:43","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":438422,"visible":true,"origin":"","legend":"\u003cp\u003e2D and 3D spatial arrangement for all ligand\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8615103/v1/ddf99b95d214a52abecce28f.png"},{"id":100544393,"identity":"55bbd677-0e88-47ff-a2e6-2d9a64b34a12","added_by":"auto","created_at":"2026-01-19 06:15:43","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":226620,"visible":true,"origin":"","legend":"\u003cp\u003eSuperimposition for chloroquine (green) with (a) artocarpin (red) and (b) cycloartocarpin (yellow)\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8615103/v1/a44a4442d428c13e3ba816e8.png"},{"id":100544398,"identity":"c0301823-a74b-4abb-a90d-fbf0e8244544","added_by":"auto","created_at":"2026-01-19 06:15:43","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":404474,"visible":true,"origin":"","legend":"\u003cp\u003eDFT study of isolated compound from \u003cem\u003eA. heterophyllus\u003c/em\u003e and LUMO HOMO structure\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-8615103/v1/98923904da09ae2106445631.png"},{"id":100544395,"identity":"4b72e87c-1a3f-4b34-b628-19ca98ecb229","added_by":"auto","created_at":"2026-01-19 06:15:43","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":470308,"visible":true,"origin":"","legend":"\u003cp\u003eMolecular electrostatic potential (MEP) maps of the studied compounds\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-8615103/v1/61ba912e90ab1b19b0877a08.png"},{"id":101058847,"identity":"f0a7ab80-6b76-4384-b607-25165a38e4cf","added_by":"auto","created_at":"2026-01-24 23:38:49","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2756700,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8615103/v1/cf9201c1-1196-436f-a12f-1d690e021a0e.pdf"},{"id":100549447,"identity":"0c58a5d4-36e6-4c4a-9247-6aa44b9d9687","added_by":"auto","created_at":"2026-01-19 08:23:20","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":167674,"visible":true,"origin":"","legend":"","description":"","filename":"Table6.docx","url":"https://assets-eu.researchsquare.com/files/rs-8615103/v1/4fd75fe427e372f46ff69177.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Integrated Molecular Docking, DFT, ADME Profiling, and Cardiotoxicity Prediction of Artocarpin, Cycloartocarpin, Artocarpanone and Cyanomaclurin as Potential Antimalarial Agents","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMalaria continues to pose a major global health challenge, with \u003cem\u003ePlasmodium falciparum\u003c/em\u003e responsible for the most severe and deadly infections. Although artemisinin-based combination therapies (ACTs) remain the cornerstone of treatment, the rapid rise in multidrug-resistant Plasmodium strains has significantly undermined their effectiveness [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. This growing problem of resistance highlights the urgent need to discover new antimalarial agents, particularly those with novel mechanisms capable of bypassing existing resistance pathways.\u003c/p\u003e \u003cp\u003eThe tropical plant \u003cem\u003eArtocarpus heterophyllus\u003c/em\u003e (jackfruit) has attracted considerable scientific attention because of its rich phytochemical profile and wide range of biological activities. Several flavonoid derivatives found in its heartwood, namely artocarpin, cycloartocarpin, artocarpanone, and cyanomaclurin, have been reported to exhibit antibacterial, antioxidant, antiviral, and anti-inflammatory effects. Notably, artocarpin also exhibits in vivo antimalarial activity. The structural resemblance of these flavonoids to other compounds known to disrupt \u003cem\u003ePlasmodium\u003c/em\u003e metabolism further supports the possibility that they may serve as promising antimalarial agents [\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOne molecular target of particular interest is the \u003cem\u003ePlasmodium falciparum\u003c/em\u003e dihydrofolate reductase\u0026ndash;thymidylate synthase (PfDHFR-TS), which plays a central role in folate metabolism and nucleotide synthesis, which are vital for parasite survival. Although PfDHFR-TS has long been targeted by antifolate drugs such as pyrimethamine, widespread resistance has greatly reduced their therapeutic value [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Exploring natural compounds that can effectively bind to this enzyme offers a compelling strategy for overcoming resistant strains.\u003c/p\u003e \u003cp\u003eRecent advances in computational chemistry have allowed researchers to investigate potential drug candidates more efficiently using in silico techniques. Molecular docking can predict the strength of binding of a compound to a target protein, whereas Density Functional Theory (DFT) provides insight into the electronic properties and reactivity of the molecule. Molecular Electrostatic Potential (MEP) mapping adds an additional layer of understanding by identifying the regions most likely to interact with the protein\u0026rsquo;s active site [\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. These methods, combined with drug-likeness and ADMET assessments, help evaluate whether a compound has the pharmacokinetic and safety characteristics required for further drug development.\u003c/p\u003e \u003cp\u003eGiven the therapeutic relevance of PfDHFR-TS and the diverse biological activities of \u003cem\u003eArtocarpus\u003c/em\u003e-derived flavonoids, a comprehensive computational study is warranted. This study investigated the antimalarial potential of artocarpin, cycloartocarpin, artocarpanone, and cyanomaclurin using an integrated in silico approach, including molecular docking, DFT calculations, MEP visualization, and ADMET profiling. Through these analyses, we aimed to characterize the binding behavior, electronic features, and pharmacokinetic suitability of these compounds, ultimately identifying promising lead compounds for future antimalarial drug development.\u003c/p\u003e"},{"header":"Research Methodology","content":"\u003cp\u003e\u003cstrong\u003eMolecular Docking\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn this study, four major phytochemical constituents of \u003cem\u003eArtocarpus heterophyllus\u0026nbsp;\u003c/em\u003eartocarpin, cycloartocarpin, artocarpanone, and cyanomaclurin [10] were selected as test ligands, with chloroquine serving as the reference drug. Ligand structures (Table 1) were drawn using ChemDraw Professional 15.0 and energy-minimized in MOE 2024.0901 to obtain optimized three-dimensional conformations. The crystal structure of \u003cem\u003ePlasmodium falciparum\u003c/em\u003e dihydrofolate reductase\u0026ndash;thymidylate synthase (PfDHFR-TS; PDB ID: 1J3I) was retrieved from the RCSB protein data bank and prepared using discovery studio visualizer by removing water molecules and heteroatoms, adding hydrogen atoms, repairing missing residues, and assigning partial charges. The structure was further protonated and energy-minimized in MOE before identifying the active site using Site Finder. Molecular docking was performed in MOE using the triangle matcher placement method and London dG scoring, followed by refinement with GBVI/WSA dG to generate and evaluate 100 binding poses for each ligand [11].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDensity functional theory\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll structures were first drawn and converted into three-dimensional conformations using ChemDraw and MOE, followed by preliminary energy minimization. The optimized geometries were imported into the Gaussian software for quantum chemical analysis. DFT calculations were performed using the B3LYP hybrid functional with the 6-31G(d,p) basis set, which is a widely validated level of theory for evaluating molecular orbitals and electronic descriptors. For each ligand, the highest occupied molecular orbital (HOMO), lowest unoccupied molecular orbital (LUMO), energy gap (\u0026Delta;E), dipole moment, and total electronic energy were obtained to assess their chemical reactivity and stability [12]. Molecular Electrostatic Potential (MEP) maps were subsequently generated from the DFT-optimized geometries using GaussView, allowing the identification of electrophilic and nucleophilic regions relevant to protein binding. These combined parameters, that is, HOMO\u0026ndash;LUMO distribution, energy gap, charge density, and MEP patterns, were used to infer the electronic behavior of each compound and support the interpretation of the molecular docking results.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAbsortption, Distribution, Metabolism, Excretion (ADME)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe pharmacokinetic and toxicity profiles of artocarpin, cycloartocarpin, artocarpanone, and cyanomaclurin were predicted using SwissADME, ADMETlab 3.0, and ProTox 3.0. The SMILES structure of each compound was submitted to SwissADME to evaluate the physicochemical properties, Lipinski compliance, lipophilicity, solubility, gastrointestinal absorption, and blood\u0026ndash;brain barrier permeability. ADMETlab 3.0 was used to estimate pharmacokinetic parameters, including volume of distribution, clearance, CYP450 inhibition potential, and organ-specific toxicity. Acute toxicity (LD\u003csub\u003e50\u003c/sub\u003e) and toxicity class were assessed using ProTox 3.0. All ADME outputs were integrated to determine the drug-likeness and preliminary safety profiles of the compounds as antimalarial candidates\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;Cardiotoxicity Prediction\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePred-hERG was used to evaluate cardiac toxicity using a probability map, prediction, and assurance of all compounds. The Pred-hERG provider aids users, using a fast, practical interface, for acknowledgment of hERG blockers and non-blockers [13].\u003c/p\u003e"},{"header":"Results and Discussion","content":"\u003cp\u003e\u003cstrong\u003eMolecular Docking\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMolecular docking was performed to predict the binding free energy and interaction between four major \u003cem\u003eArtocarpus heterophyllus\u003c/em\u003e compounds i.e. artocarpin, cycloartocarpin, artocarpanone, and cyanomaclurin against the \u003cem\u003ePlasmodium falciparum\u003c/em\u003e DHFR-TS enzyme (PDB ID: 1J3I). Chloroquine was used as positive control. Molecular docking results are presented in table 1. Docking simulations showed that artocarpin and cycloartocarpin has binding free energy of \u0026minus;9.506 and\u0026minus;9.407 kcal/mol, respectively. It were exhibited the strongest binding free energy toward PfDHFR-TS. Their values were notably better than those of artocarpanone and cyanomaclurin and were comparable or slightly superior to those of chloroquine. These findings indicate that the two prenylated flavonoids may have significant inhibitory potential against the DHFR domain, making them promising candidates for further antimalarial exploration.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1.\u0026nbsp;\u003c/strong\u003e Docking results\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"930\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13.5338%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLigand\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.12245%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBinding free energy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5.6928%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRMSD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.30397%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHydrogen bond\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.59291%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHydrophobic interaction\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.87433%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVan der Waals interaction\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38.3459%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOther interaction\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.5338%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eBinding Factor\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13.5338%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eChloroquine\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.12245%;\"\u003e\n \u003cp\u003e-8.465\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5.6928%;\"\u003e\n \u003cp\u003e1.154\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.30397%;\"\u003e\n \u003cp\u003ePhe58. Leu40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.59291%;\"\u003e\n \u003cp\u003eLys49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.87433%;\"\u003e\n \u003cp\u003e\u003cu\u003eAsp54\u003c/u\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38.3459%;\"\u003e\n \u003cp\u003eAla16, \u003cu\u003eCys15\u003c/u\u003e, Gly44, Gly165, Gly166, \u003cu\u003eIle14\u003c/u\u003e, Ile112, Ile164, Leu46, Met55, Pro113, Ser108, Ser111, Tyr170, Val45 \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.5338%;\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13.5338%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCpd1\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(\u003cem\u003eArtocarpin\u003c/em\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.12245%;\"\u003e\n \u003cp\u003e-9.506\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5.6928%;\"\u003e\n \u003cp\u003e1.596\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.30397%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePhe58,\u003cu\u003eAsp54\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.59291%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLys49\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.87433%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cu\u003eAsp54\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38.3459%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAla16, \u003cu\u003eCys15\u003c/u\u003e,\u0026nbsp;\u003c/strong\u003eGly41\u003cstrong\u003e, Gly44, Gly165, Gly166, \u003cu\u003eIle14\u003c/u\u003e, Ile112, Ile164, Leu40, Leu46, Met55, Pro113, Ser108, Ser111, Val45,\u0026nbsp;\u003c/strong\u003eVal195\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.5338%;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13.5338%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCpd2\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(\u003cem\u003eCycloartocarpin\u003c/em\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.12245%;\"\u003e\n \u003cp\u003e-9.407\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5.6928%;\"\u003e\n \u003cp\u003e1.635\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.30397%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLeu46, Ser111\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.59291%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLys49\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.87433%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cu\u003eAsp54\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38.3459%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAla16, \u003cu\u003eCys15\u003c/u\u003e, Gly44, Gly165, Gly166, \u003cu\u003eIle14\u003c/u\u003e, Ile112, Ile164, Leu40, Met55, Phe58, Ser108,\u0026nbsp;\u003c/strong\u003eThr107\u003cstrong\u003e,\u0026nbsp;\u003c/strong\u003eThr185\u003cstrong\u003e,\u0026nbsp;\u003c/strong\u003eTrp48\u003cstrong\u003e,\u0026nbsp;\u003c/strong\u003eTyr57\u003cstrong\u003e, Tyr170, Val45\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.5338%;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13.5338%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCpd3\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(\u003cem\u003eArtocarpanone\u003c/em\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.12245%;\"\u003e\n \u003cp\u003e-7.525\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5.6928%;\"\u003e\n \u003cp\u003e0.880\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.30397%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cu\u003eAsp54\u003c/u\u003e\u003c/strong\u003e\u003cstrong\u003e, Gly165\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.59291%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLys49\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.87433%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cu\u003eAsp54\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38.3459%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAla16, \u003cu\u003eCys15\u003c/u\u003e, Gly166, \u003cu\u003eIle14\u003c/u\u003e, Ile164, Leu40, Leu46, Met55, Phe58, Ser108,\u0026nbsp;\u003c/strong\u003eThr185\u003cstrong\u003e,\u0026nbsp;\u003c/strong\u003eTrp48\u003cstrong\u003e,\u0026nbsp;\u003c/strong\u003eTyr57\u003cstrong\u003e, Tyr170\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.5338%;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13.5338%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCpd4\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(\u003cem\u003eCyanomaclurin\u003c/em\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.12245%;\"\u003e\n \u003cp\u003e-6.777\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5.6928%;\"\u003e\n \u003cp\u003e0.843\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.30397%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePhe58\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.59291%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6.87433%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cu\u003eAsp54\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38.3459%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAla16, \u003cu\u003eCys15\u003c/u\u003e, Gly44, Gly165, Gly166, \u003cu\u003eIle14\u003c/u\u003e, Ile112, Ile164, Leu40, Leu46, Met55, Ser108, Ser111,\u0026nbsp;\u003c/strong\u003eSer167\u003cstrong\u003e, Tyr170,\u0026nbsp;\u003c/strong\u003eVal195\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.5338%;\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBold \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;: The amino acid residues interacting with Cpd1\u0026ndash;Cpd4 are identical to those interacting with the positive control\u003c/p\u003e\n\u003cp\u003eUnderline \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;: catalytic triad\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe strong binding free energy observed for artocarpin and cycloartocarpin can be attributed to their ability to form several stabilizing interactions within the active site of the enzyme. Both compounds establish hydrogen bonds with key catalytic residues and are stabilized by extensive hydrophobic contacts deep inside the binding pocket. As shown in Figure 2, interactions with residues such as Ile14, Phe58, Cys59, and Gly44, which are frequently involved in DHFR inhibitor binding, play an important role in maintaining this stability. The presence of hydroxyl groups facilitates hydrogen bond formation, whereas the prenyl side chains contribute additional hydrophobic anchoring. These structural characteristics align well with established structure\u0026ndash;activity relationship findings, indicating that prenylated flavonoids often exhibit enhanced binding performance due to increased lipophilicity and improved interactions with the target site [14].\u003c/p\u003e\n\u003cp\u003eSuperimposition analysis (Figure 3) showed that artocarpin and cycloartocarpin adopted binding orientations that closely resembled those of chloroquine. Both compounds occupy similar regions within the active site and display comparable \u0026pi;\u0026ndash;\u0026pi; stacking and hydrophobic interactions with the residues. This strong spatial overlap suggests that they may inhibit the enzyme through a similar mechanism, supporting the possibility that these compounds disrupt dihydrofolate reduction that a key process required for synthesis of nucleic acid in \u003cem\u003ePlasmodium\u003c/em\u003e.\u003c/p\u003e\n\u003cp\u003eArtocarpanone and cyanomaclurin exhibited lower binding free energy and also fewer stabilizing interactions with the PfDHFR-TS active site. Their binding conformations showed little spatial overlap with the reference ligand and were superficially positioned within the catalytic cavity. Their lower anticipated inhibitory potential is likely caused by their decreased hydrophobic surface area and decreased availability of hydrogen-bonding capabilities.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDensity Functional Theory (DFT)\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDensity Functional Theory (DFT) calculations were conducted to systematically evaluate the electronic structures and reactivity profiles of chloroquine and the four principal compounds derived from \u003cem\u003eArtocarpus heterophyllus\u003c/em\u003e, namely, artocarpin, cycloartocarpin, artocarpanone, and cyanomaclurin. The energies of the highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) were examined, along with the resulting HOMO\u0026ndash;LUMO energy gap (\u0026Delta;E). These quantum chemical parameters are widely recognized as key indicators of molecular stability, electronic reactivity, and propensity of compounds to engage in intermolecular interactions with biological targets. DFT parameter of \u0026nbsp;chloroquine and \u003cem\u003eA. heterophyllus\u003c/em\u003e compounds are presented in Table 2.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2.\u0026nbsp;\u003c/strong\u003e DFT results\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"576\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 131px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ecompound\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal energy\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(a.u)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMomen Dipol\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(Debye)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 182px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eelectronic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEnergy Gap\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(\u0026Delta;E)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHOMO\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLUMO\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003eChloroquine\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(positive control)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e-1326.032\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e4.937\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e-0.198\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e-0.315\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.117\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003eArtocarpin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e-1458.906\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e5.686\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e-0.184\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e-0.311\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.127\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003eCycloartocarpin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e-1457.712\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e6.619\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e-0.194\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e-0.304\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.110\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003eArtocarpanone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e-1069.466\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e3.332\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e-0.171\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e-0.308\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.137\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 131px;\"\u003e\n \u003cp\u003eCyanomaclurin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e-1030.129\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e1.086\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e-0.154\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e-0.304\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.150\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eDFT analysis revealed distinct differences in the electronic characteristics of the examined compounds. Among the \u003cem\u003eA. heterophyllus\u003c/em\u003e derivatives, cycloartocarpin exhibited the smallest HOMO\u0026ndash;LUMO energy gap (0.110), followed closely by artocarpin (0.127). A reduced energy gap is commonly associated with increased electronic reactivity and enhanced molecular polarizability, indicating a greater propensity for these compounds to engage in charge transfer interactions with biological macromolecules. This electronic behavior may contribute to the favorable interaction profiles observed in subsequent molecular docking analyses [15] .\u003c/p\u003e\n\u003cp\u003eThe comparatively low HOMO\u0026ndash;LUMO energy gaps (\u0026Delta;E) observed for artocarpin and cycloartocarpin reflect favorable electronic properties consistent with their strong binding affinities identified in molecular docking analyses. This concordance suggests a meaningful relationship between electronic reactivity and binding efficiency, thereby strengthening the rationale for considering these compounds as potential PfDHFR-TS inhibitors [16]. However, artocarpanone and cyanomaclurin exhibited relatively larger energy gaps, indicating greater molecular stability but diminished electronic reactivity, which may underlie their comparatively weaker docking interactions.\u003c/p\u003e\n\u003cp\u003eThe visualization of the frontier molecular orbitals (Figure 4) revealed that the HOMO distributions of artocarpin and cycloartocarpin were predominantly localized on oxygen-containing functional groups, particularly hydroxyl moieties. Therefore, these regions are likely to act as electron-donating sites during ligand\u0026ndash;protein interactions. In contrast, the LUMO distributions were primarily delocalized over the aromatic frameworks and prenylated substituents, indicating their potential role as electron-accepting regions when interacting with electrophilic residues within the enzyme active site.\u003c/p\u003e\n\u003cp\u003eThe observed spatial distributions of the HOMO and LUMO orbitals were consistent with the interaction patterns identified in the molecular docking simulations, in which the hydroxyl functional groups predominantly contributed to hydrogen bond formation, whereas the prenyl substituents enhanced the hydrophobic interactions within the PfDHFR-TS active site. This concordance between the electronic features derived from DFT analysis and docking interaction profiles reinforces the robustness and reliability of in silico predictions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMolecular Electrostatic Potential (MEP)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMolecular Electrostatic Potential (MEP) analysis was performed to characterize the charge distribution and electrostatic properties of chloroquine and the four compounds derived from \u003cem\u003eArtocarpus heterophyllus\u003c/em\u003e. MEP mapping offers important insights into molecular regions that are predisposed to electrophilic or nucleophilic interactions, thereby providing a mechanistic understanding of how these compounds recognize and interact with protein targets [17].\u003c/p\u003e\n\u003cp\u003eAs depicted in Figure 5, all evaluated compounds exhibited distinct regions of negative electrostatic potential, predominantly localized around the oxygen atoms, particularly those associated with hydroxyl and carbonyl functional groups. These electron-rich regions are characteristic of sites capable of acting as hydrogen-bond acceptors and are therefore likely to play a key role in stabilizing interactions with amino acid residues within the PfDHFR-TS active-site. Conversely, regions of positive electrostatic potential were primarily distributed over hydrogen-rich alkyl chains and aromatic moieties, indicating electron-deficient areas that may participate in complementary electrostatic interactions during ligand\u0026ndash;protein-binding.\u003c/p\u003e\n\u003cp\u003eAll the analyzed compounds exhibited well-defined regions of negative electrostatic potential, predominantly localized around the oxygen atoms, particularly those associated with hydroxyl and carbonyl functional groups [18]. These electron-rich regions represent potential hydrogen-bond acceptor sites and are therefore likely to contribute significantly to stabilizing interactions with amino acid residues within the PfDHFR-TS active site. Conversely, regions of positive electrostatic potential were primarily distributed over hydrogen-rich alkyl chains and aromatic moieties, indicating electron-deficient areas that may participate in complementary electrostatic interactions during ligand\u0026ndash;protein-binding.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eArtocarpin and cycloartocarpin exhibited well-defined regions of negative electrostatic potential predominantly localized around their hydroxyl functional groups, in agreement with the strong hydrogen-bonding interactions observed in the molecular docking simulations. The presence of prenyl substituents contributed to regions of relatively neutral to mildly positive electrostatic potential, which may favor hydrophobic interactions within the enzyme-binding pocket. This combination of complementary electrostatic and hydrophobic characteristics is likely to enhance both binding complementarity and complex stability. Table 3 are presented the electrostatic features derived from MEP analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3.\u0026nbsp;\u003c/strong\u003eElectrostatic features based on MEP analysis\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCompounds\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003ctable border=\"0\" cellspacing=\"3\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003ePredominant Negative Potential Regions\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003ctable border=\"0\" cellspacing=\"3\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003ePredominant Positive Potential Regions\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cdiv align=\"center\"\u003e\n \u003ctable border=\"0\" cellspacing=\"3\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eKey functional\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cstrong\u003eGroups involved\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eChloroquine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eNitrogen atom\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eAlkyl chain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eAmine group\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eArtocarpin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eOxygen atom\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eAromatic region\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eHydroxyl group\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eCycloartocarpin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eOxygen atom\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eAromatic region\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eHydroxyl group\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eArtocarpanone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eOxygen atom\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eAromatic region\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eCarbonyl and hydroxyl group\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eCyanomaclurin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eOxygen atom\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eAromatic region\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003eMultiple hydroxyl group\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eArtocarpanone and cyanomaclurin exhibited broader but less distinctly localized regions of negative electrostatic potential, indicating a more evenly distributed electron density across their molecular frameworks. Although these electrostatic features remain compatible with hydrogen bond formation, the less concentrated potential distribution may partially account for their comparatively weaker binding affinities relative to artocarpin and cycloartocarpin.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAbsortption, Distribution, Metabolism, Excretion (ADME)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn silico ADME analysis was performed to systematically evaluate the pharmacokinetic characteristics and drug-likeness of artocarpin, cycloartocarpin, artocarpanone, and cyanomaclurin. Assessing these parameters is essential for estimating the translational viability of bioactive compounds beyond their target-binding performance. The predicted ADME profiles are summarized in Table 4.\u003c/p\u003e\n\u003cp\u003eAll four compounds exhibited high predicted oral bioavailability and favorable gastrointestinal absorption, indicating suitable permeability for oral administration. Compliance with Lipinski\u0026rsquo;s rule of five further supports the classification of these compounds as drug-like molecules. Moreover, key physicochemical parameters, including molecular weight and lipophilicity, were within acceptable ranges, suggesting a balanced profile between aqueous solubility and membrane permeability [19].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4.\u0026nbsp;\u003c/strong\u003e Drug-likeness and ADMET\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eParameter\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 464px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eResult\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003eChloroquine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003eArtocarpin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003eCycloartocarpin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003eArtocarpanone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 97px;\"\u003e\n \u003cp\u003eCyanomaclurin\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003eLipinski\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003eMolecular weight (g/mol)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e319.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e436.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e434.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e302.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e288.25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003eH\u003cem\u003e-bond acceptor\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003eH\u003cem\u003e-bond donor\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003eLog P\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e4.733\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e4.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e4.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e2.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e1.25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003eTPSA (\u0026Aring;)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e28.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e100.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e89.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e96.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e99.38\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003eGhose\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003eVeber\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003eEgan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003eMuegge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003eHuman Intestinal Absorption (HIA)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e0.081\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e0.052\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003eCaco-2 permeability\u0026nbsp;(log cm/s)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e-4.981\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e-5.146\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e-5.098\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e-4.989\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e-6.048\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003eP-glycoprotein\u0026nbsp;inhibitor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e0.088\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e0.978\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e0.654\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e0.798\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003eP-glycoprotein substrate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e0.849\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e0.029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e0.035\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e0.032\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e0.934\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003eF20%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e0.904\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e0.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e0.57\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003eF30%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e0.989\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e0.666\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 160px;\"\u003e\n \u003cp\u003ePlasma Protein\u0026nbsp;Binding (PPB) (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e49.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e96.994\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e97.912\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e91.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e91.499\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 160px;\"\u003e\n \u003cp\u003eBlood-Brain Barrier\u0026nbsp;Penetration\u0026nbsp;(BBB)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e0.961\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e0.041\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 160px;\"\u003e\n \u003cp\u003eVolume distribution\u0026nbsp;(L/kg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e1.076\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e0.238\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e0.053\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e0.058\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e0.143\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 160px;\"\u003e\n \u003cp\u003eFraction\u0026nbsp;unbound\u0026nbsp;(Fu)(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e56.319\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e3.036\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e2.093\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e9.118\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e9.994\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 160px;\"\u003e\n \u003cp\u003eCYP1A2 substrate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e0.093\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e0.157\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e0.964\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 160px;\"\u003e\n \u003cp\u003eCYP1A2\u0026nbsp;inhibitor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e0.481\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e0.748\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e0.998\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 160px;\"\u003e\n \u003cp\u003eCYP2C19 substrate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e0.732\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e0.988\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e0.913\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e0.537\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 160px;\"\u003e\n \u003cp\u003eCYP2C19 inhibitor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e0.996\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e0.996\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e0.097\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 160px;\"\u003e\n \u003cp\u003eCYP2C9 substrate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e0.092\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e0.893\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 160px;\"\u003e\n \u003cp\u003eCYP2C9 inhibitor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e0.994\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e0.907\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 160px;\"\u003e\n \u003cp\u003eCYP2D6 substrate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e0.374\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e0,074\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e0,009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e0,955\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e0,707\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 160px;\"\u003e\n \u003cp\u003eCYP2D6 inhibitor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e0.017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e0.618\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 160px;\"\u003e\n \u003cp\u003eCYP3A4 substrate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e0.716\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e0.802\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 160px;\"\u003e\n \u003cp\u003eCYP3A4 inhibitor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e0.834\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e0.955\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 160px;\"\u003e\n \u003cp\u003eHalf time (t1/2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e0.561\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e1.574\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e1.236\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e1.657\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e2.643\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 160px;\"\u003e\n \u003cp\u003eClearance (mL/min/kg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e5.666\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e2.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e4.601\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e2.841\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e7.719\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 160px;\"\u003e\n \u003cp\u003eHuman hepatotoxicity\u0026nbsp;(H-HT)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e0.727\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e0.693\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e0.831\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e0.611\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e0.653\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 160px;\"\u003e\n \u003cp\u003ehERG blockers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e0.958\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e0.085\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e0.132\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e0.119\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e0.138\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 160px;\"\u003e\n \u003cp\u003eRat\u0026nbsp;oral\u0026nbsp;acute toxicity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e0.796\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e0.537\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e0.371\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e0.564\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e0.436\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 160px;\"\u003e\n \u003cp\u003eAMES toxicity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e0.512\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e0.483\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e0.679\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e0,.88\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 160px;\"\u003e\n \u003cp\u003eDrug\u0026nbsp;Induced\u0026nbsp;Liver Injury (DILI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e0525\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e0.717\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e0.932\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e0.499\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e0.503\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 160px;\"\u003e\n \u003cp\u003eCarcinogencity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e0.204\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e0.359\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e0.732\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e0.672\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e0.371\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAll four compounds were predicted to exhibit moderate to high levels of acute oral toxicity in the rat model, along with an associated risk of hepatotoxicity and carcinogenicity. These results indicate that, despite their promising antimalarial potential, as suggested by molecular docking and electronic structure analyses, the safety profiles of these compounds may present substantial challenges for their direct advancement as therapeutic agents. Prediction of toxicity value for all compounds are listed in Table 5.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5.\u0026nbsp;\u003c/strong\u003eToxicity prediction\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"631\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCompound\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 159px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLD\u003c/strong\u003e\u003cstrong\u003e\u003csub\u003e50\u003c/sub\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTo\u003c/strong\u003e\u003cstrong\u003exicity class\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHepatoto\u003c/strong\u003e\u003cstrong\u003exicity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003eChloroquine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 159px;\"\u003e\n \u003cp\u003e750 nmg/kg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003eClass 4\u003c/p\u003e\n \u003cp\u003elow toxicity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003eInactive (0,65)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003eArtocarpin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 159px;\"\u003e\n \u003cp\u003e4000\u0026nbsp;mg/kg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003eClass 5\u003c/p\u003e\n \u003cp\u003eVery low toxicity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003eInactive (0,68)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003eCycloartocarpin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 159px;\"\u003e\n \u003cp\u003e475\u0026nbsp;mg/kg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003eClass 4\u003c/p\u003e\n \u003cp\u003elow toxicity\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003eInactive (0,67)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003eArtocarpanone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 159px;\"\u003e\n \u003cp\u003e2000 mg/kg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003eClass 4\u003c/p\u003e\n \u003cp\u003elow toxicity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003eInactive (0,71)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 122px;\"\u003e\n \u003cp\u003eCyanomaclurin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 159px;\"\u003e\n \u003cp\u003e2500 mg/kg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 161px;\"\u003e\n \u003cp\u003eClass\u0026nbsp;5\u003c/p\u003e\n \u003cp\u003eVery low toxicity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003eInactive (0,80)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eThe prediction of hepatotoxicity deserves particular attention, given the central role of the liver in drug metabolism and detoxification processes. Compounds with hepatotoxic potential may accumulate in liver tissue or be converted into reactive metabolites, ultimately causing cellular damage in the liver. This concern is supported by the low predicted clearance values observed in the ADME analysis, which suggests prolonged systemic exposure and, consequently, an increased likelihood of toxicity [20].\u003c/p\u003e\n\u003cp\u003eAlthough these toxicity concerns are important, they do not necessarily rule out further developments. Many biologically active natural products initially exhibit safety liabilities that can be reduced through structural refinement, targeted modification of functional groups, or appropriate formulation approaches. Artocarpin and cycloartocarpin, which exhibited the most favorable binding affinities and electronic characteristics, represent promising lead scaffolds for developing safer and more selective antimalarial derivatives.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCardiotoxicity Prediction\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCardiotoxicity, defined as drug-induced damage to cardiac tissue, represents a major challenge in pharmaceutical development and is a leading cause of late-stage drug attrition during both preclinical and clinical evaluation. Because interference with cardiac electrophysiology can result in life-threatening arrhythmias, cardiotoxicity remains one of the most serious and closely monitored adverse effects in new drug candidates [21]. The cardiac safety profile of the studied compounds was therefore evaluated using the PRED-hERG model, and the results are summarized in Table 6.\u003c/p\u003e\n\u003cp\u003eThis computational model provides a reliable assessment of a compound\u0026rsquo;s likelihood to interact with the hERG potassium channel, a key regulator of cardiac repolarization. By predicting hERG liability, this analysis offers important insight into the potential cardiac risks associated with the investigated chemical entities.\u003c/p\u003e\n\u003cp\u003eThis classification provides an estimate of the likelihood that the tested compounds may inhibit the hERG channel, an event that can trigger potentially life-threatening cardiac arrhythmias. The reliability of each prediction is indicated by the \u0026ldquo;Confidence (%)\u0026rdquo; value reported by the model. In addition, the \u0026ldquo;Applicability Domain\u0026rdquo; parameter is critical for interpreting these results, as it reflects whether a compound falls within the chemical space on which the model was trained. Notably, cycloartocarpin and cyanomaclurin listed in Table 4 lie outside the model\u0026rsquo;s applicability domain, which introduces a degree of uncertainty and suggests that the predictions should be interpreted with caution.\u003c/p\u003e\n\u003cp\u003eThe predicted cardiotoxic profiles of ligands are summarized in Table 4, including their confidence scores, applicability domains, potency classifications, and associated reliability within those domains. As cardiotoxicity reflects a compound\u0026rsquo;s potential to disrupt normal cardiac function or cause myocardial injury, it represents a critical safety concern in drug discovery and development.\u003c/p\u003e\n\u003cp\u003eChloroquine, used as a reference compound, was predicted to be a hERG blocker with exceptional reliability (99.5 %), corroborating its well-established cardiotoxic potential. The model designated chloroquine within the applicability domain, reflecting a high degree of confidence in this prediction [22]. The predicted IC₅₀ value of 5.579 further corroborates its robust interaction with the hERG channel, aligning with clinical findings of QT prolongation and arrhythmogenic risk associated with chloroquine treatment.\u003c/p\u003e\n\u003cp\u003eArtocarpin, cycloartocarpin, and artocarpanone were all anticipated to be non-inhibitors of the hERG channel. Cycloartocarpin had the highest confidence, with a binary reliability of 95.76%, followed by artocarpanone (77.74 %) and artocarpin (76.27 %). Significantly, all three substances were categorized within the applicability domain, signifying that their chemical characteristics reside within the validated prediction space of the model and that their anticipated safety profiles are dependable. Their anticipated IC₅₀ values (5.192\u0026ndash;5.327) were marginally lower than those of chloroquine, indicating diminished or less functionally significant interactions with the hERG channel.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis study demonstrates that flavonoids derived from Artocarpus heterophyllus, specifically artocarpin and cycloartocarpin, exhibit significant in silico inhibitory efficacy against Plasmodium falciparum DHFR-TS. Combined molecular docking and quantum chemistry investigations showed that the enzyme's active site had good binding affinities, electronic reactivity and complementary interaction patterns. Predicting cardiotoxicity showed that neither chemical was a hERG blocker, which means that they are safer for the heart than chloroquine. Although moderate toxicity risks are expected, these constraints can be addressed through logical structure optimization. In summary, these results suggest that artocarpin and cycloartocarpin are promising candidates for further research and the development of antimalarial drugs.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo datasets were generated or analysed during the current study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe express out gratitude for the support received from the Ministry of Education, Culture, Research and Technology of the Republic of Indonesia for research funding through Grant No 022/LL17/DT.05.00/ PL/2025\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors contributed to the research design, collection, analysis, and interpretation of data. The first draft of the manuscript was written by Neni Frimayanti. All authors commented on the previous drafts of the paper. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of 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 appear to have influenced the research reported in this paper.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAlghamdi JM, Al-Qahtani AA, Alhamlan FS, Al-Qahtani AA. Recent Advances in the Treatment of Malaria. Pharmaceutics. 2024 Nov 4;16(11):1416. doi: 10.3390/pharmaceutics16111416\u003c/li\u003e\n\u003cli\u003eSanyaolu, A., Marinkovic, A., Prakash, S., Balendra, V., Shazley, O., Gardellini, T., Jan, A., Younis, K., Okorie, C., \u0026amp; Izurieta, R. (2025). Emerging Molecular Mechanisms in Malaria Pathogenesis and Novel Therapeutic Approaches: A Focus on P. falciparum Malaria. Biomolecules, 15(7), 1038. https://doi.org/10.3390/biom15071038\u003c/li\u003e\n\u003cli\u003eLiu X, Zhang Z, Wang J, Wang X, Bi H, Wang M. Recent developments in Artocarpus heterophyllus Lam. (jackfruit) polysaccharides: Nutritional values, structural characteristics and health benefits. Int J Biol Macromol. 2025 May;309(Pt 2):142923. doi: 10.1016/j.ijbiomac.2025.142923\u003c/li\u003e\n\u003cli\u003eNansereko, Sophie, and John. H. Muyonga. 2021. \u0026ldquo;Exploring the Potential of Jackfruit (Artocarpus Heterophyllus Lam)\u0026rdquo;. \u003cem\u003eAsian Food Science Journal\u003c/em\u003e 20 (9):97-117. https://doi.org/10.9734/afsj/2021/v20i930346.\u003c/li\u003e\n\u003cli\u003eKumar, A., Mishra, A., \u0026amp; Singh, A. (2022). Phytochemistry, pharmacological, medicinal significance of Artocarpus heterophyllus Lam. (Jackfruit). \u003cem\u003eInternational Journal of Health Sciences\u003c/em\u003e, \u003cem\u003e6\u003c/em\u003e(S5), 6578\u0026ndash;6590. https://doi.org/10.53730/ijhs.v6nS5.10134\u003c/li\u003e\n\u003cli\u003eBiswas P, Roy R, Ghosh K, Nath D, Samadder A, Nandi S. To quest new targets of \u003cem\u003ePlasmodium\u003c/em\u003e parasite and their potential inhibitors to combat antimalarial drug resistance. J Parasit Dis. 2024 Dec;48(4):671-722. doi: 10.1007/s12639-024-01687-x.\u003c/li\u003e\n\u003cli\u003eOuma, R.B.O., Ngari, S.M. \u0026amp; Kibet, J.K. A review of the current trends in computational approaches in drug design and metabolism. Discov Public Health 21, 108 (2024). https://doi.org/10.1186/s12982-024-00229-3\u003c/li\u003e\n\u003cli\u003eAlbratty M, Thangavel N, Chandrasekaran B, Meraya AM, Alhazmi HA, Muthumanickam S, Boomi P, Bhagavan NB, Saleh SF (2024) Benchmarking docking, density functional theory and molecular dynamics studies to assess the aldose reductase inhibitory potential of \u003cem\u003eTrigonella foenum-graecum\u003c/em\u003e compounds for managing diabetes-associated complications. Pharmacia 71: 1-10. https://doi.org/10.3897/pharmacia.71.e118949\u003c/li\u003e\n\u003cli\u003eTahiroğlu, V., G\u0026ouml;ren, K. \u0026amp; Bağlan, M. In Silico drug evaluation by molecular docking, ADME studies and DFT calculations of 2-(6-chloro-2-(4-chlorophenyl)imidazo[1,2-a]pyridin-3-yl)-N, N-dipropylacetamide. BMC Pharmacol Toxicol 26, 116 (2025). https://doi.org/10.1186/s40360-025-00958-4\u003c/li\u003e\n\u003cli\u003eSeptama AW, Panichayupakaranant P. Antibacterial assay-guided isolation of active compounds from Artocarpus heterophyllus heartwoods. Pharm Biol. 2015;53(11):1608-13. doi: 10.3109/13880209.2014.996819. \u003c/li\u003e\n\u003cli\u003eAbookleesh, F., Mosa, F. E. S., Barakat, K., \u0026amp; Ullah, A. (2022). Assessing Molecular Docking Tools to Guide the Design of Polymeric Materials Formulations: A Case Study of Canola and Soybean Protein. \u003cem\u003ePolymers\u003c/em\u003e, \u003cem\u003e14\u003c/em\u003e(17), 3690. https://doi.org/10.3390/polym14173690\u003c/li\u003e\n\u003cli\u003eIşık A, Acar \u0026Ccedil;evik U, Karayel A, Ahmad I, Patel H, \u0026Ccedil;elik İ, G\u0026uuml;l \u0026Uuml;D, Bayazıt G, Bostancı HE, Ko\u0026ccedil;ak A, \u0026Ouml;zkay Y, Kaplancıklı ZA. Synthesis, DFT Calculations, \u003cem\u003eIn Silico\u003c/em\u003e Studies, and Antimicrobial Evaluation of Benzimidazole-Thiadiazole Derivatives. ACS Omega. 2024 Apr 9;9(16):18469-18479. doi: 10.1021/acsomega.4c00543.\u003c/li\u003e\n\u003cli\u003eKhan MA, Mutahir S, Jabar G, Wenwei Z, Tariq MA, Almehizia AA, Mustafa M. DFT, Molecular Docking, ADME, and Cardiotoxicity Studies of Persuasive Thiazoles as Potential Inhibitors of the Main Protease of SARS-CoV-2. Chem Biodivers. 2024 Dec;21(12):e202401775. doi: 10.1002/cbdv.202401775\u003c/li\u003e\n\u003cli\u003eMichel J, Tirado-Rives J, Jorgensen WL. Energetics of displacing water molecules from protein binding sites: consequences for ligand optimization. J Am Chem Soc. 2009 Oct 28;131(42):15403-11. doi: 10.1021/ja906058w.\u003c/li\u003e\n\u003cli\u003eMumit MA, Pal TK, Alam MA, Islam MA, Paul S, Sheikh MC. DFT studies on vibrational and electronic spectra, HOMO-LUMO, MEP, HOMA, NBO and molecular docking analysis of benzyl-3-N-(2,4,5-trimethoxyphenylmethylene)hydrazinecarbodithioate. J Mol Struct. 2020 Nov 15;1220:128715. doi: 10.1016/j.molstruc.2020.128715.\u003c/li\u003e\n\u003cli\u003eBlankevoort N, Bastante P, Davidson RJ, Salthouse RJ, Daaoub AHS, Cea P, Solans SM, Batsanov AS, Sangtarash S, Bryce MR, Agrait N, Sadeghi H. Exploring the Impact of the HOMO-LUMO Gap on Molecular Thermoelectric Properties: A Comparative Study of Conjugated Aromatic, Quinoidal, and Donor-Acceptor Core Systems. ACS Omega. 2024 Feb 5;9(7):8471-8477. doi: 10.1021/acsomega.3c09760.\u003c/li\u003e\n\u003cli\u003eNoureddine O, Issaoui N, Al-Dossary O. DFT and molecular docking study of chloroquine derivatives as antiviral to coronavirus COVID-19. J King Saud Univ Sci. 2021 Jan;33(1):101248. doi: 10.1016/j.jksus.2020.101248\u003c/li\u003e\n\u003cli\u003eMart\u0026iacute;nez-Cifuentes, M., Weiss-L\u0026oacute;pez, B. E., Santos, L. S., \u0026amp; Araya-Maturana, R. (2014). Intramolecular Hydrogen Bond in Biologically Active \u003cem\u003eo\u003c/em\u003e-Carbonyl Hydroquinones. \u003cem\u003eMolecules\u003c/em\u003e, \u003cem\u003e19\u003c/em\u003e(7), 9354-9368. https://doi.org/10.3390/molecules19079354\u003c/li\u003e\n\u003cli\u003eLipinski CA. Lead- and drug-like compounds: the rule-of-five revolution. Drug Discov Today Technol. 2004 Dec;1(4):337-41. doi: 10.1016/j.ddtec.2004.11.007. \u003c/li\u003e\n\u003cli\u003eKim, Y., Kim, H. \u0026amp; Kim, Y. Advancing hepatotoxicity assessment: current advances and future directions. Toxicol Res. 41, 303\u0026ndash;323 (2025). https://doi.org/10.1007/s43188-025-00289-w\u003c/li\u003e\n\u003cli\u003eMamoshina P, Rodriguez B, Bueno-Orovio A. Toward a broader view of mechanisms of drug cardiotoxicity. Cell Rep Med. 2021 Mar 16;2(3):100216. doi: 10.1016/j.xcrm.2021.100216. \u003c/li\u003e\n\u003cli\u003eJordaan P, Dumotier B, Traebert M, Miller PE, Ghetti A, Urban L, Abi-Gerges N. Cardiotoxic Potential of Hydroxychloroquine, Chloroquine and Azithromycin in Adult Human Primary Cardiomyocytes. Toxicol Sci. 2021 Apr 12;180(2):356-368. doi: 10.1093/toxsci/kfaa194\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Table","content":"\u003cp\u003eTable 6 is available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"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":"Malaria, Artocarpus heterophyllus, Molecular Docking, DFT, ADMET study","lastPublishedDoi":"10.21203/rs.3.rs-8615103/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8615103/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe escalating resistance of \u003cem\u003ePlasmodium falciparum\u003c/em\u003e to existing antimalarial treatments necessitates the identification of novel medicines with enhanced efficacy and safety. This study utilized a comprehensive in silico approach to assess the potential of four flavonoids from \u003cem\u003eArtocarpus heterophyllus\u003c/em\u003e \u0026icirc;.e. artocarpin, cycloartocarpin, artocarpanone, and cyanomaclurin as inhibitors of \u003cem\u003eP. falciparum\u003c/em\u003e dihydrofolate reductase\u0026ndash;thymidylate synthase (PfDHFR-TS). Molecular docking demonstrated that artocarpin and cycloartocarpin displayed enhanced binding affinities and advantageous interaction patterns compared to chloroquine. Density functional theory and molecular electrostatic potential investigations corroborated their increased electronic reactivity and binding compatibility. ADME profiling demonstrated satisfactory drug-likeness properties; however, cardiotoxicity prediction revealed artocarpin and cycloartocarpin as non-hERG blockers, unlike chloroquine. Despite the anticipated mild toxicity hazards, the comprehensive computational data underscore artocarpin and cycloartocarpin as prospective lead scaffolds for subsequent optimization. These findings provide a compelling justification for the experimental validation and rational design of safer antimalarial medicines derived from \u003cem\u003eA. heterophyllus.\u003c/em\u003e\u003c/p\u003e","manuscriptTitle":"Integrated Molecular Docking, DFT, ADME Profiling, and Cardiotoxicity Prediction of Artocarpin, Cycloartocarpin, Artocarpanone and Cyanomaclurin as Potential Antimalarial Agents","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-19 06:15:38","doi":"10.21203/rs.3.rs-8615103/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":"ea232b2d-eb6d-4bf7-9ec1-a8cff9ef2f3b","owner":[],"postedDate":"January 19th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-01-24T23:38:26+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-19 06:15:38","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8615103","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8615103","identity":"rs-8615103","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}