Current computer-aided drug design最新文献

{"title":"Computational Study of Antimicrobial Peptides for Promising Therapeutic Applications Against Methicillin-resistant Staphylococcus Aureus.","authors":"Priyanka Sinoliya, Pooran Singh Solanki, Ravi Ranjan Kumar Niraj, Vinay Sharma","doi":"10.2174/0115734099285473240101111303","DOIUrl":"https://doi.org/10.2174/0115734099285473240101111303","url":null,"abstract":"<p><strong>Background: </strong>Methicillin-resistant Staphylococcus aureus (MRSA) is a causative agent for multiple drug-resistant diseases and is a prime health concern. Currently, antibiotics like vancomycin, daptomycin, fluoroquinolones, linezolid, fifth-generation cephalosporin and others are available in the market for the treatment of MRSA infection.</p><p><strong>Methods: </strong>With the increasing prevalence of drug-resistant cases, researchers are actively investigating alternative strategies to combat MRSA, including the exploration of peptide therapeutics. This study employed computational methods to prospect for potential Antimicrobial Peptides (AMPs).</p><p><strong>Results: </strong>A total of One hundred and fifty antimicrobial peptides were explored based on physicochemical properties. The results showed that Clavanin B was the most appropriate candidate. Molecular Docking and Molecular Dynamics Simulation results showed the protein-peptide interaction of the MRSA target proteins, Penicillin Binding Protein 2a and Panton-Valentine Leukocidin Toxin, with the Antimicrobial Peptide Clavanin B.</p><p><strong>Conclusion: </strong>Currently, the antimicrobial peptide database highlights Clavanin B's role as an anti-HIV peptide. Moreover, this investigation proposes Clavanin B as a viable repurposed drug for treating MRSA, underscoring its potential deployment in the management of MRSA infections.</p>","PeriodicalId":93961,"journal":{"name":"Current computer-aided drug design","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139479683","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 Mechanism Analysis of the Effect of Hederagenin Combined with L-OHP on Chemosensitivity of AGS/L-OHP Based on Network Pharmacology.","authors":"Hongyue Tang, Chao Wang, Chenhao Xing, Guoxin Liang, Chang Guo, Xin Liu, YanJie Li, Mingming Zhang","doi":"10.2174/0115734099270389240104050955","DOIUrl":"https://doi.org/10.2174/0115734099270389240104050955","url":null,"abstract":"<p><strong>Aims and objectives: </strong>This study aimed to evaluate the pharmacological mechanism of Hederagenin (HD) combined with oxaliplatin (L-OHP) in treating gastric cancer (GC) through network pharmacology combined with experimental verification.</p><p><strong>Material and methods: </strong>Network pharmacology methods were used to screen potential targets for HD, L-OHP, and GC-related targets from public databases, and the intersection of the three gene sets was taken. Cross genes were analyzed through protein-protein interaction (PPI) networks to predict core targets, and related pathways were predicted through GO and KEGG enrichment analysis. The experimental results were verified by the in vitro experiments. HD was applied on AGS/L-OHP cells, and then cellular chemosensitivity and the expressions of P-gp, Survivin, Bcl-2, p-Akt, and p-PI3K genes were detected. Wound assay and Transwell Chamber assay were employed to detect the effect of HD on AGS/L-OHP cells. Nude mice xenograft models transfected using AGS/L-OHP cells were also treated with HD in order to verify the results. The size and weight of the tumor, as well as the expressions of P-gp, Survivin, Bcl-2, p- Akt and p-PI3K genes, were also measured.</p><p><strong>Results: </strong>KEGG analysis showed that the anti-gastric cancer effect of HD was mediated mainly by PI3K-Akt signaling pathways. The PI3K-Akt signaling pathway containing more enriched genes may play a greater role in anti-gastric cancer. It was observed that for AGS/L-OHP cells jointly treated with HD and L-OHP, their activity, migration and invasion were significantly lower than those treated only using HD or L-OHP group. Moreover, expressions of p-Akt, p- PI3K, Bcl-2, P-gp, and Survivin for the HD+L-OHP group decreased significantly. Results of the in vivo experiments showed that the sizes and weights of tumors in the HD+L-OHP group were the lowest compared to the HD group and L-OHP group.</p><p><strong>Conclusion: </strong>Our findings suggest that HD may reduce the resistance of AGS/L-OHP cells to LOHP by regulating the PI3K/Akt signaling pathway.</p>","PeriodicalId":93961,"journal":{"name":"Current computer-aided drug design","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139513500","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":"Exploration of Pharmacological Mechanisms of Dapagliflozin against Type 2 Diabetes Mellitus through PI3K-Akt Signaling Pathway based on Network Pharmacology Analysis and Deep Learning Technology.","authors":"Jie Wu, Yufan Chen, Shuai Shi, Junru Liu, Fen Zhang, Xingxing Li, Xizhi Liu, Guoliang Hu, Yang Dong","doi":"10.2174/0115734099274407231207070451","DOIUrl":"https://doi.org/10.2174/0115734099274407231207070451","url":null,"abstract":"<p><strong>Background: </strong>Dapagliflozin is commonly used to treat type 2 diabetes mellitus (T2DM). However, research into the specific anti-T2DM mechanisms of dapagliflozin remains scarce.</p><p><strong>Objective: </strong>This study aimed to explore the underlying mechanisms of dapagliflozin against T2DM.</p><p><strong>Methods: </strong>Dapagliflozin-associated targets were acquired from CTD, SwissTargetPrediction, and SuperPred. T2DM-associated targets were obtained from GeneCards and DigSee. VennDiagram was used to obtain the overlapping targets of dapagliflozin and T2DM. GO and KEGG analyses were performed using clusterProfiler. A PPI network was built by STRING database and Cytoscape, and the top 30 targets were screened using the degree, maximal clique centrality (MCC), and edge percolated component (EPC) algorithms of CytoHubba. The top 30 targets screened by the three algorithms were intersected with the core pathway-related targets to obtain the key targets. DeepPurpose was used to evaluate the binding affinity of dapagliflozin with the key targets.</p><p><strong>Results: </strong>In total, 155 overlapping targets of dapagliflozin and T2DM were obtained. GO and KEGG analyses revealed that the targets were primarily enriched in response to peptide, membrane microdomain, protein serine/threonine/tyrosine kinase activity, PI3K-Akt signaling pathway, MAPK signaling pathway, and AGE-RAGE signaling pathway in diabetic complications. AKT1, PIK3CA, NOS3, EGFR, MAPK1, MAPK3, HSP90AA1, MTOR, RELA, NFKB1, IKBKB, ITGB1, and TP53 were the key targets, mainly related to oxidative stress, endothelial function, and autophagy. Through the DeepPurpose algorithm, AKT1, HSP90AA1, RELA, ITGB1, and TP53 were identified as the top 5 anti-targets of dapagliflozin.</p><p><strong>Conclusion: </strong>Dapagliflozin might treat T2DM mainly by targeting AKT1, HSP90AA1, RELA, ITGB1, and TP53 through PI3K-Akt signaling.</p>","PeriodicalId":93961,"journal":{"name":"Current computer-aided drug design","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139418828","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":"In-silico Design, ADMET Screening, Prime MM-GBSA Binding Free Energy Calculation and MD Simulation of Some Novel Phenothiazines as 5HT6R Antagonists Targeting Alzheimer's Disease.","authors":"Prema V, Meena A, Ramalakshmi N","doi":"10.2174/0115734099282836231212064925","DOIUrl":"https://doi.org/10.2174/0115734099282836231212064925","url":null,"abstract":"<p><strong>Background: </strong>Alzheimer's disease is a type of dementia that affects neuronal function, leading to a decline in cognitive functions. Serotonin-6 (5HT6) receptors are implicated in the etiology of neurological diseases. 5HT6 receptor antagonists act as anti-dementia agents.</p><p><strong>Pdb id: </strong>7YS6 represents a membrane protein, and amplification and overexpression of this protein are associated with Alzheimer's disease. Coumarin-fused phenothiazines are significant anti-Alzheimer's agents due to their inhibitory activity on the Serotonin- 6 receptor.</p><p><strong>Objectives: </strong>Numerous previously unreported Coumarin-substituted Phenothiazines [A2 to A50] were designed using in-silico methods to evaluate their 5HT6 receptor antagonistic activity. Molecular modeling techniques were employed to study the ligands [A2 to A50] in interaction with the Serotonin-6 receptor (PDB ID: 7YS6) using Schrödinger Suite 2019-4.</p><p><strong>Methods: </strong>Molecular modeling studies of the designed ligands [A2 to A50] were conducted using the Glide module. In-silico ADMET screening was performed using the QikProp module, and binding free energy calculations were carried out using the Prime MM-GBSA module within the Schrödinger Suite. The binding affinity of the designed ligands [A2 to A50] towards 5HT6 receptors was determined based on Glide scores. Subsequently, ligand A31 underwent a 100 ns molecular dynamics simulation using the Desmond module of Schrödinger Suite 2020-1, which is based in New York, NY.</p><p><strong>Results: </strong>The majority of the designed ligands exhibited strong hydrogen bonding interactions and hydrophobic associations with the serotonin-6 receptor, which hinder its activity. These ligands achieved remarkable Glide scores within the range of -4.2859 to -7.7128, in comparison to reference standards such as Idalopirdine (-7.78149), Intepirdine (-5.20103), Latrepirdine (-5.54853), and the co-crystallized ligand (-7.02889). In-silico ADMET properties for these ligands fell within the recommended values for drug-likeness. It is worth noting that the MM-GBSA binding free energy of the most potent inhibitor was positive, indicating a strong binding interaction. Additionally, the dynamic behavior of the protein (7YS6)-ligand (A31) complex was studied by subjecting ligand A31 to a 100 ns molecular dynamics simulation.</p><p><strong>Conclusion: </strong>The results of this study reveal strong evidence supporting the potential of coumarin- substituted phenothiazine derivatives as effective Serotonin-6 receptor antagonists. Ligands [A2 to A50], which exhibited noteworthy Glide scores, hold promise for significant anti- Alzheimer activity. Further in-vitro and in-vivo investigations are warranted to explore and confirm their therapeutic potential.</p>","PeriodicalId":93961,"journal":{"name":"Current computer-aided drug design","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139418829","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":"PyComp: A Versatile Tool for Efficient Data Extraction, Conversion, and Management in High-throughput Virtual Drug Screening.","authors":"Mohsen Sisakht, Mohammad Keyvanloo Shahrestanaki, Jafar Fallahi, Vahid Razban","doi":"10.2174/0115734099274495231218150611","DOIUrl":"https://doi.org/10.2174/0115734099274495231218150611","url":null,"abstract":"<p><strong>Background: </strong>Virtual screening (VS) is essential for analyzing potential drug candidates in drug discovery. Often, this involves the conversion of large volumes of compound data into specific formats suitable for computational analysis. Managing and processing this wealth of information, especially when dealing with vast numbers of compounds in various forms, such as names, identifiers, or SMILES strings, can present significant logistical and technical challenges.</p><p><strong>Methods: </strong>To streamline this process, we developed PyComp, a software tool using Python's PyQt5 library, and compiled it into an executable with Pyinstaller. PyComp provides a systematic way for users to retrieve and convert a list of compound names, IDs (even in a range), or SMILES strings into the desired 3D format.</p><p><strong>Results: </strong>PyComp greatly enhances the efficiency of data extraction, conversion, and storage processes involved in VS. It searches for similar compounds coupled with its ability to handle misidentified compounds and offers users an easy-to-use, customizable tool for managing largescale compound data. By streamlining these operations, PyComp allows researchers to save significant time and effort, thus accelerating the pace of drug discovery research.</p><p><strong>Conclusion: </strong>PyComp effectively addresses some of the most pressing challenges in highthroughput VS: efficient management and conversion of large volumes of compound data. As a user-friendly, customizable software tool, PyComp is pivotal in improving the efficiency and success of large-scale drug screening efforts, paving the way for faster discovery of potential therapeutic compounds.</p>","PeriodicalId":93961,"journal":{"name":"Current computer-aided drug design","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139405696","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":"In Silico Study on Natural Chemical Compounds from Citric Essential Oils as Potential Inhibitors of an Omicron (BA.1) SARS-CoV-2 Mutants' Spike Glycoprotein.","authors":"Olha Ovchynnykova, Jordhan D Booth, Trey M Cocroft, Kostyantyn M Sukhyy, Karina Kapusta","doi":"10.2174/0115734099275132231213055138","DOIUrl":"10.2174/0115734099275132231213055138","url":null,"abstract":"<p><strong>Background: </strong>SARS-CoV-2's remarkable capacity for genetic mutation enables it to swiftly adapt to environmental changes, influencing critical attributes, such as antigenicity and transmissibility. Thus, multi-target inhibitors capable of effectively combating various viral mutants concurrently are of great interest.</p><p><strong>Objective: </strong>This study aimed to investigate natural compounds that could unitedly inhibit spike glycoproteins of various Omicron mutants. Implementation of various in silico approaches allows us to scan a library of compounds against a variety of mutants in order to find the ones that would inhibit the viral entry disregard of occurred mutations.</p><p><strong>Methods: </strong>An extensive analysis of relevant literature was conducted to compile a library of chemical compounds sourced from citrus essential oils. Ten homology models representing mutants of the Omicron variant were generated, including the latest 23F clade (EG.5.1), and the compound library was screened against them. Subsequently, employing comprehensive molecular docking and molecular dynamics simulations, we successfully identified promising compounds that exhibited sufficient binding efficacy towards the receptor binding domains (RBDs) of the mutant viral strains. The scoring of ligands was based on their average potency against all models generated herein, in addition to a reference Omicron RBD structure. Furthermore, the toxicity profile of the highest-scoring compounds was predicted.</p><p><strong>Results: </strong>Out of ten built homology models, seven were successfully validated and showed to be reliable for In Silico studies. Three models of clades 22C, 22D, and 22E had major deviations in their secondary structure and needed further refinement. Notably, through a 100 nanosecond molecular dynamics simulation, terpinen-4-ol emerged as a potent inhibitor of the Omicron SARS-CoV-2 RBD from the 21K clade (BA.1); however, it did not show high stability in complexes with other mutants. This suggests the need for the utilization of a larger library of chemical compounds as potential inhibitors.</p><p><strong>Conclusion: </strong>The outcomes of this investigation hold significant potential for the utilization of a homology modeling approach for the prediction of RBD's secondary structure based on its sequence when the 3D structure of a mutated protein is not available. This opens the opportunities for further advancing the drug discovery process, offering novel avenues for the development of multifunctional, non-toxic natural medications.</p>","PeriodicalId":93961,"journal":{"name":"Current computer-aided drug design","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139099417","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}