Current computer-aided drug design最新文献

{"title":"Molecular Generation, QSAR, and Molecular Dynamic Simulation Studies for Virtual Screening of DNA Polymerase Theta Inhibitors.","authors":"Zijian Qin, Lei Liu, Mohan Gao, Wei Feng, Changjiang Huang, Wei Liu","doi":"10.2174/0115734099305142240508051830","DOIUrl":"https://doi.org/10.2174/0115734099305142240508051830","url":null,"abstract":"<p><strong>Aims: </strong>The machine learning-based QSAR modeling procedure, molecular generations, and molecular dynamic simulations were applied to virtually screen the DNA polymerase theta inhibitors.</p><p><strong>Background: </strong>The DNA polymerase theta (Polθ or POLQ) is an attractive target for treatments of homologous recombination deficient (such as BRCA deficient) cancers. There are no approved drugs for targeting POLQ, and only one inhibitor is in Phase Ⅱclinical trials; thus, it is necessary to develop novel POLQ inhibitors.</p><p><strong>Objectives: </strong>To build machine learning models that predict the bioactivities of POLQ inhibitors. To build molecular generation models that generate diverse molecules. To virtually screen the generated molecules by the machine learning models. To analyze the binding modes of the screening results by molecular dynamic simulations.</p><p><strong>Methods: </strong>In the present work, 325 inhibitors with POLQ polymerase domain bioactivities were Collected. Two machine learning methods, random forest and deep neural network, were used for building the ligand- and structure-based quantitative structure-activity relationship (QSAR) models. The substructure replacement-based method and transfer learning-based deep recurrent neural network method were used for molecular generations. Molecular docking and consensus QSAR models were carried out for virtual screening. The molecular dynamic simulations and MM/GBSA binding free energy calculation and decomposition were used to further analyze the screening results.</p><p><strong>Results: </strong>The MCC values of the best ligand- and structure-based consensus QSAR models reached 0.651 and 0.361 for the test set, respectively. The machine learning-based docking scores had better-predicted ability to distinguish the highly and weakly active poses than the original docking scores. The 96490 molecules were generated by both molecular generation methods, and 10 molecules were retained by virtual screening. Four favorable interactions were concluded by molecular dynamic simulations.</p><p><strong>Conclusion: </strong>We hope that the screening results and the binding modes are helpful for designing the highly active POLQ polymerase inhibitors and the models of the molecular design workflow can be used as reliable tools for drug design.</p>","PeriodicalId":93961,"journal":{"name":"Current computer-aided drug design","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141082963","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Flavonoids and Organic Acids Affect Phase II Metabolism based on the Regulation of UGT1A1 Expression and Function.","authors":"Lin Zhang, Xuerong Zhang, Caiyan Wang","doi":"10.2174/0115734099300793240509103320","DOIUrl":"https://doi.org/10.2174/0115734099300793240509103320","url":null,"abstract":"<p><strong>Background: </strong>Exogenous substances modulate metabolism by regulating the expression and function of UDP-glycosyltransferases (UGTs). However, the exact mechanism in the intestine was rarely understood. Herein, we explored the effects of representative flavonoids and organic acids on the regulation of UGT1A1.</p><p><strong>Methods: </strong>MTT assays and western blot analysis were used to explore the effect of polyphenols. X-ray diffraction was used to reveal the catalytic mechanisms of UGTs.</p><p><strong>Results: </strong>MTT assays showed that these compounds basically had no cytotoxicity, even in concentrations up to 200 μM. Then, through western blot assays, UGT1A1 expression was increased after being treated with liquiritigenin and caffeic acid. Furthermore, liquiritigenin and caffeic acid enhanced the nuclear translocation of Nrf2. Moreover, a 2.5-Å crystal structure of the complex containing UGTs C-terminal domain and organic acid was solved, and the UDPGA binding pocket could be occupied by organic acid, suggesting the enzyme activity might be impaired by organic acid.</p><p><strong>Conclusion: </strong>Above all, liquiritigenin and caffeic acid maintained the metabolism balance by upregulating the expression of UGT1A1 via Nrf2 activation and inhibiting the enzyme activity in Caco-2 cells.</p>","PeriodicalId":93961,"journal":{"name":"Current computer-aided drug design","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141066539","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fluorinated Diaryl Sulfonamides: Molecular Modeling, Synthesis, and <i>In Vitro</i> Validation as New CETP Inhibitors.","authors":"Reema Abu Khalaf, Azhar Shalluf, Maha Habash","doi":"10.2174/0115734099268407230927113905","DOIUrl":"10.2174/0115734099268407230927113905","url":null,"abstract":"<p><strong>Background: </strong>Hyperlipidemia, a cardiovascular disease risk factor, is characterized by a rise in low-density lipoprotein (LDL), triglycerides and total cholesterol, and a decrease in high-density lipoprotein (HDL). Cholesteryl ester transfer protein (CETP) enables the transfer of cholesteryl ester from HDL to LDL and very low-density lipoprotein.</p><p><strong>Objectives: </strong>CETP inhibition is a promising approach to prevent and treat cardiovascular diseases. By inhibiting lipid transport activity, it increases HDL levels and decreases LDL levels.</p><p><strong>Materials and method: </strong>Herein, diaryl sulfonamides 6a-6g and 7a-7g were prepared, and the structure of these compounds was fully determined using different spectroscopic techniques.</p><p><strong>Results: </strong>These compounds underwent biological evaluation <i>in vitro</i> and showed different inhibitory activities against CETP; 100% inhibitory activity was observed for compounds 7a-7g, while activities of compounds 6a-6g ranged up to 42.6% at 10 μM concentration. Pharmacophore mapping agreed with the bioassay results where the four aromatic ring compounds 7a-7g possessed higher fit values against Hypo4/8 and the shape-complemented Hypo4/8 in comparison to compounds 6a-6g.</p><p><strong>Conclusion: </strong>Docking of the synthesized compounds using libdock and ligandfit engines revealed that compounds 7a-7g formed п-п stacking and hydrophobic interactions with the binding pocket, while compounds 6a-6g missed these hydrophobic interactions with amino acids Leu206, Phe265, and Phe263.</p>","PeriodicalId":93961,"journal":{"name":"Current computer-aided drug design","volume":" ","pages":"987-997"},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49686537","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"<i>In-silico</i> Investigation of Ginseng Phytoconstituents as Novel Therapeutics Against MAO-A.","authors":"Diksha Choudhary, Rajwinder Kaur, Nidhi Rani, Thakur Gurjeet Singh, Bhupinder Kumar","doi":"10.2174/0115734099266270230925090023","DOIUrl":"10.2174/0115734099266270230925090023","url":null,"abstract":"<p><strong>Background: </strong>Ginseng (<i>Panax ginseng</i>) is a herb of medicinal and nutritional importance. Ginseng has been used since ancient times for the treatment of numerous ailments as it has many therapeutic properties. Several phytoconstituents are present in <i>Panax ginseng</i> that possess a variety of beneficial pharmacological properties.</p><p><strong>Objective: </strong>To explore the potential of phytoconstituents of <i>Panax ginseng</i> in the treatment of depression, a molecular modeling technique was utilized targeting monoamine oxidase-A (MAO-A).</p><p><strong>Methods: </strong>A total of sixty-one phytoconstituents of ginseng were drawn with the help of ChemBioDraw Ultra 12.0 software and PDBs for MAO-A enzyme were retrieved from the RCSB PDB database. The prepared ligands were screened for MAO-A properties using the software Molegro Virtual Docker (MVD 2010.4.1.0). All the prepared ligands were evaluated for drug-likeliness properties using Swiss ADME.</p><p><strong>Results: </strong>Among the docking studies of 60 Ginseng phytochemicals including one standard, 15 phytoconstituents with the highest dock score and better binding interactions were selected further for absorption, distribution, metabolism and excretion (ADME) studies. Stachyose (-227.287, 17 interactions), Raffinose (-222.157, 14 interactions), and Ginsenoside Rg1 (-216.593, 10 interactions) were found to possess better interactions as compared to Clorgyline taken as a standard drug.</p><p><strong>Conclusion: </strong>Stachyose was found to be the most potent inhibitor of MAO-A enzyme under investigation and can be a potential lead molecule for the development of newer phytochemical-based treatment of depression.</p>","PeriodicalId":93961,"journal":{"name":"Current computer-aided drug design","volume":" ","pages":"711-722"},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41184573","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring the Molecular Mechanism of Niuxi-Mugua Formula in Treating Coronavirus Disease 2019 <i>via</i> Network Pharmacology, Computational Biology, and Surface Plasmon Resonance Verification.","authors":"Wei Wang, Xu Cao, Yi-Nan Cao, Lian-Lian Liu, Shu-Ling Zhang, Wen-Ying Qi, Jia-Xin Zhang, Xian-Zhao Yang, Xiao-Ke Li, Xiao-Bin Zao, Yong-An Ye","doi":"10.2174/0115734099272592231004170422","DOIUrl":"10.2174/0115734099272592231004170422","url":null,"abstract":"<p><strong>Background: </strong>In China, Niuxi-Mugua formula (NMF) has been widely used to prevent and treat coronavirus disease 2019 (COVID-19). However, the mechanism of NMF for treating COVID-19 is not yet fully understood.</p><p><strong>Objective: </strong>This study aimed to explore the potential mechanism of NMF for treating COVID- 19 by network pharmacology, computational biology, and surface plasmon resonance (SPR) verification.</p><p><strong>Materials and methods: </strong>The NMF-compound-target network was constructed to screen the key compounds, and the Molecular Complex Detection (MCODE) tool was used to screen the preliminary key genes. The overlapped genes (OGEs) and the preliminary key genes were further analyzed by enrichment analysis. Then, the correlation analysis of immune signatures and the preliminary key genes was performed. Molecular docking and molecular dynamic (MD) simulation assays were applied to clarify the interactions between key compounds and key genes. Moreover, the SPR interaction experiment was used for further affinity kinetic verification.</p><p><strong>Results: </strong>Lipid and atherosclerosis, TNF, IL-17, and NF-kappa B signaling pathways were the main pathways of NMF in the treatment of COVID-19. There was a positive correlation between almost the majority of immune signatures and all preliminary key genes. The key compounds and the key genes were screened out, and they were involved in the main pathways of NMF for treating COVID-19. Moreover, the binding affinities of most key compounds binding to key genes were good, and IL1B-Quercetin had the best binding stability. SPR analysis further demonstrated that IL1B-Quercetin showed good binding affinity.</p><p><strong>Conclusion: </strong>Our findings provided theoretical grounds for NMF in the treatment of COVID-19.</p>","PeriodicalId":93961,"journal":{"name":"Current computer-aided drug design","volume":" ","pages":"1113-1129"},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49686536","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Computer-aided Design of Wide-spectrum Coronavirus Helicase NSP13 Cage Inhibitors: A Molecular Modelling Approach.","authors":"Vadim Shiryaev, Yuri Klimochkin","doi":"10.2174/0115734099247900231016055626","DOIUrl":"10.2174/0115734099247900231016055626","url":null,"abstract":"<p><strong>Background: </strong>The coronavirus helicase NSP13 plays a critical role in its life cycle. The found NSP13 inhibitors have been tested only in vitro but they definitely have the potential to become antiviral drugs. Thus, the search for NSP13 inhibitors is of great importance.</p><p><strong>Objectives: </strong>The goal of the present work was to develop a general approach to the design of ligands of coronaviral NSP13 helicase and to propose on its basis potential inhibitors.</p><p><strong>Methods: </strong>The structure of the NSP13 protein was refined by molecular dynamics and the cavity, responsible for RNA binding, was chosen as the inhibitor binding site. The potential inhibitor structures were identified by molecular docking and their binding was verified by molecular dynamics simulation.</p><p><strong>Results: </strong>A number of potential NSP13 inhibitors were identified and the binding modes and probable mechanism of action of potential inhibitors was clarified.</p><p><strong>Conclusion: </strong>Using the molecular dynamics and molecular docking techniques, we have refined the structure of the coronavirus NSP13 helicase, a number of potential inhibitors, containing cage fragment were proposed and their probable mechanism of action was clarified. The proposed approach is also suitable for the design of ligands interacting with other viral helicases.</p>","PeriodicalId":93961,"journal":{"name":"Current computer-aided drug design","volume":" ","pages":"1027-1041"},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71430434","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimizing the Extraction of Polyphenols from the Bark of <i>Terminalia arjuna</i> and an <i>In-silico</i> Investigation on its Activity in Colorectal Cancer.","authors":"Tathagata Adhikary, Piyali Basak","doi":"10.2174/0115734099264119230925054833","DOIUrl":"10.2174/0115734099264119230925054833","url":null,"abstract":"<p><strong>Background: </strong>The interconnection between different fields of research has gained interest due to its cutting-edge perspectives in solving scientific problems. <i>Terminalia arjuna</i> is indigenously used in India for curing several diseases, and its pharmacological activities are being revisited in recent drug-repurposing research.</p><p><strong>Objectives: </strong>Efficient ultrasound-assisted extraction of phytochemicals from the bark of <i>Terminalia arjuna</i> is highlighted in this study. Following the optimization of the extraction process, the crude hydroethanolic extract is subjected to phytochemical profiling and an <i>in-silico</i> investigation of its anti-cancer properties.</p><p><strong>Materials and methods: </strong>A three-level four-factor Box-Behnken design is exploited to optimize four operational parameters, namely extraction time, ultrasonic power, ethanol concentration (as the extracting solvent) and solute (in g): solvent (in mL) ratio. At the optimum parametric condition, the crude extract is obtained, and its GC-MS analysis is carried out. An analysis of network pharmacology (by constructing and visualizing biological networks using Cytoscape) combined with molecular docking reveals the potential antineoplastic targets of the crude extract.</p><p><strong>Results: </strong>The ANOVA table exhibits the significance, adequacy and reliability of the proposed second-order polynomial model with the R² value of 0.917 and adjusted R² of 0.865. Experimental results portray the significant antioxidant potential of the prepared extract in its crude form. The GC-MS analysis of the crude extract predicts the extracted phytochemicals, while the constructed biological networks highlight its multi-targeted activity in colorectal cancer.</p><p><strong>Conclusion: </strong>The study identifies three phytochemicals <i>viz</i>. luteolin, β-sitosterol and arjunic acid as potent anti-cancer agents and can be extended with <i>in-vitro</i> and <i>in-vivo</i> experiments to validate the <i>in-silico</i> results, thus establishing lead phytochemicals in multi-targeted colorectal cancer therapies.</p>","PeriodicalId":93961,"journal":{"name":"Current computer-aided drug design","volume":" ","pages":"653-665"},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41242537","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identify Diabetes-related Targets based on ForgeNet_GPC.","authors":"Bin Yang, Linlin Wang, Wenzheng Bao","doi":"10.2174/0115734099258183230929173855","DOIUrl":"10.2174/0115734099258183230929173855","url":null,"abstract":"<p><strong>Background: </strong>Research on potential therapeutic targets and new mechanisms of action can greatly improve the efficiency of new drug development.</p><p><strong>Aims: </strong>Polygenic genetic diseases, such as diabetes, are caused by the interaction of multiple gene loci and environmental factors.</p><p><strong>Objectives: </strong>In this study, a disease target identification algorithm based on protein recognition is proposed.</p><p><strong>Materials and methods: </strong>In this method, the related and unrelated targets are collected from literature databases for treating diabetes. The transcribed proteins corresponding to each target are queried in order to construct a protein dataset. Six protein feature extraction algorithms (AAC, CKSAAGP, DDE, DPC, GAAP, and TPC) are utilized to obtain the feature vectors of each protein, which are merged into the full feature vectors.</p><p><strong>Results: </strong>A novel classifier (forgeNet_GPC) based on forgeNet and Gaussian process classifier (GPC) is proposed to classify the proteins.</p><p><strong>Conclusion: </strong>In forgeNet_GPC, forgeNet is utilized to select the important features, and GPC is utilized to solve the classification problem. The experimental results reveal that forgeNet_GPC performs better than 22 classifiers in terms of ROC-AUC, PR-AUC, MCC, Youden Index, and Kappa.</p>","PeriodicalId":93961,"journal":{"name":"Current computer-aided drug design","volume":" ","pages":"1042-1054"},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139089708","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Synthesis, and <i>In-silico</i> Studies of Indole-chalcone Derivatives Targeting Estrogen Receptor Alpha (ER-α) for Breast Cancer.","authors":"Rahul Charudatta Choudhari, Kamalpreet Kaur, Agnidipta Das, Vikas Jaitak","doi":"10.2174/0115734099263650230926053750","DOIUrl":"10.2174/0115734099263650230926053750","url":null,"abstract":"<p><strong>Background: </strong>Breast cancer is the prominent reason of death in women worldwide, and the cases are increasing day by day. There are many FDA-approved drugs for treating breast cancer. Due to drug resistance, and problems in selectivity, there is a need to develop more effective agents with few side effects. Indole derivatives have demonstrated significant pharmacological potential as anti-breast cancer agents. Further, chalcone derivatives incorporating heterocyclic scaffolds play a significant role in medicine. Indole-chalcone-based compounds offer the potential for improved biological activity and enhanced drug-like properties. It prompted us to explore the synthesis of Indole-Chalcone derivatives targeting estrogen receptor alpha (ER-α) to discover potent anti-breast cancer agents.</p><p><strong>Objectives: </strong>To synthesize indole-chalcone derivatives and study their binding interactions for ER-α protein by molecular docking for breast cancer treatment.</p><p><strong>Methods: </strong>In this study, indole-chalcone derivatives have been synthesized using conventional heating. With the help of Schrodinger software, molecular interaction as well as ADME (Adsorption, Distribution, Metabolism, and Excretion) studies of the compounds were conducted.</p><p><strong>Results: </strong>Among all the synthesized compounds, four compounds (1, 2, 3, and 4) showed better docking scores (-10.24 kcal/mol, -10.15 kcal/mol, -9.40 kcal/mol, -9.29 kcal/mol, respectively) than the standard tamoxifen (-8.43 kcal/mol).</p><p><strong>Conclusion: </strong>From <i>In-silico</i> studies, we can conclude that four compounds from the synthesized series fit into the active site of ER-α. ADME properties of synthesized derivatives were found in the acceptable range. In the future, these compounds can be further explored for biological activity.</p>","PeriodicalId":93961,"journal":{"name":"Current computer-aided drug design","volume":" ","pages":"640-652"},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"54232864","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Molecular Modelling of Resveratrol Derivatives with SIRT1 for the Stimulation of Deacetylase Activity.","authors":"Mozhdeh Zamani, Pooneh Mokarram, Mehdi Jamshidi, Morvarid Siri, Hadi Ghasemi","doi":"10.2174/0115734099258321231003161602","DOIUrl":"10.2174/0115734099258321231003161602","url":null,"abstract":"<p><strong>Background: </strong>Resveratrol is a polyphenol that is found in plants and has been proposed to have a potential therapeutic effect through the activation of SIRT1, which is a crucial member of the mammalian NAD+ -dependent deacetylases. However, how its activity is enhanced toward specific substrates by resveratrol derivatives has not been studied. This study aimed to evaluate the types of interaction of resveratrol and its derivatives with SIRT1 as the target protein, as well as to find out the best ligand with the strangest interaction with SIRT1.</p><p><strong>Materials and methods: </strong>In this study, we employed the extensive molecular docking analysis using AutoDock Vina to comparatively evaluate the interactions of resveratrol derivatives (22 molecules from the ZINC database) as ligands with SIRT1 (PDB ID: 5BTR) as a receptor. The ChemDraw and Chem3D tools were used to prepare 3D structures of all ligands and energetically minimize them by the MM2 force field.</p><p><strong>Results: </strong>The molecular docking and visualizations showed that conformational change in resveratrol derivatives significantly influenced the parameter for docking results. Several types of interactions, including conventional hydrogen bonds, carbon-hydrogen bonds, Pi-donor hydrogen bonds, and Pi-Alkyl, were found via docking analysis of resveratrol derivatives and SIRT1 receptors. The possible activation effect of resveratrol 4'-(6-galloylglucoside) with ZINC ID: ZINC230079516 with higher binding energy score (-46.8608 kJ/mol) to the catalytic domain (CD) of SIRT1 was achieved at the maximum value for SIRT1, as compared to resveratrol and its other derivatives.</p><p><strong>Conclusion: </strong>Finally, resveratrol 4'-(6-galloylglucoside), as a derivative for resveratrol, has stably interacted with the CD of SIRT1 and might be a potential effective activator for SIRT1.</p>","PeriodicalId":93961,"journal":{"name":"Current computer-aided drug design","volume":" ","pages":"943-954"},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41242536","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}