Current computer-aided drug design最新文献

{"title":"Identifying Novel Inhibitors for Dengue NS2B-NS3 Protease by Combining Topological similarity, Molecular Dynamics, MMGBSA and SiteMap Analysis.","authors":"Sheikh Murtuja, Mohd Usman Mohd Siddique, Kumar Pratyush Srivastava, Yogeeta O Agarwal, Sakshi Wagh, Sabina Yasmin, Azim Ansari, Mohd Sayeed Shaikh, Md Saquib Hasnain, Sameer N Goyal","doi":"10.2174/0115734099329789240905141013","DOIUrl":"https://doi.org/10.2174/0115734099329789240905141013","url":null,"abstract":"<p><strong>Introduction: </strong>DENV NS2B-NS3 protease inhibitors were designed based upon the reference molecule, 4-(1,3-dioxoisoindolin-2-yl)-N-(4-ethylphenyl) benzenesulfonamide, reported by our team with the aim to optimize lead compound via rational approach. Top five best scoring molecules with zinc ids ZINC23504872, ZINC48412318, ZINC00413269, ZINC13998032 and ZINC75249613 bearing 'pyrimidin-4(3H)-one' basic scaffold have been identified as a promising candidate against DENV protease enzyme.</p><p><strong>Methods: </strong>The shape and electrostatic complementary between identified HITs and reference molecules were found to be Tanimotoshape 0.453, 0.690, 0.680, 0.685 & 0.672 respectively and Tanimotoelectrostatic 0.211, 0.211, 0.441, 0.442, 0.442 and 0.442 respectively. The molecular docking studies suggested that the identified HITs displayed the good interactions with active site residues and lower binding energies. The stability of docked complexes was assessed by MD simulations studies. The RMSD values of protein backbone (1.6779, 3.1563, 3.3634, 3.3893 & 3.0960 Å) and protein backbone RMSF values (1.0126, 1.0834, 1.0890, 0.9974 & 1.0080 Å respectively) for all top five HITs were stable and molecules did not fluctuate from the active pocket during entire 100ns MD run.</p><p><strong>Results: </strong>The druggability Dscore below 1 indicate the tightly binding of ligand at the active site. Dscore for ZINC23504872 was found to be 1.084 while for the second class of compounds ZINC48412318, ZINC00413269, ZINC13998032 and ZINC75249613, 0.503, 0.484, 0.487 and 0.501 Dscores were observed. In-silico ADMET calculations suggested that all five HITs were possessed the drug likeliness properties and did not violate the Lipinski's rule of five.</p><p><strong>Conclusion: </strong>Summing up, these in-silico generated data suggested that the identified molecules bearing pyrimidin-4(3H)-one would be promising scaffold for DENV protease inhibitors. However, experimental results are needed to prove the obtained results.</p>","PeriodicalId":93961,"journal":{"name":"Current computer-aided drug design","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142549641","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":"Discovery of Two GSK3β Inhibitors from Sophora flavescens Ait. using Structure-based Virtual Screening and Bioactivity Evaluation.","authors":"Dabo Pan, Yong Zeng, Dewen Jiang, Yonghao Zhang, Mingkai Wu, Yaxuan Huang, Minzhen Han, Xiao-Jie Jin","doi":"10.2174/0115734099321878241011104241","DOIUrl":"https://doi.org/10.2174/0115734099321878241011104241","url":null,"abstract":"<p><strong>Objective: </strong>Kushen (Sophora flavescens Ait.) has a long history of medicinal use in China due to its medicinal values, such as antibacterial, antiviral, and anti-inflammatory. Rapid discovery of the components and the medicinal effects exerted by Kushen will help elucidate the science of Kushen in curing diseases. GSK3β (glycogen synthase kinase-3 beta) is a protein kinase with a wide range of physiological functions, such as antibacterial, antiviral, and anti-inflammatory. The discovery of inhibitors targeting GSK3β from Kushen was not only helpful for the rapid discovery of the components responsible for the efficacy of Kushen but also important for the development of novel drugs.</p><p><strong>Methods: </strong>In this study, the chemical composition of Kushen was extracted from the TMSCP database. Molecular docking, GSK3β enzyme assay, and molecular dynamics simulations were used to discover the GSK3β inhibitors from the chemical composition of Kushen.</p><p><strong>Results: </strong>A total of 113 chemical compositions of Kushen were extracted from the TMSCP database. Molecular docking indicated that 15 chemical compositions of Kushen scored better than -8 kcal/mol against GSK3β. GSK3β enzyme assay demonstrated several inhibitory activities of kushenol I and kushenol F with IC50 values of 7.53 ± 2.55 μM and 4.96 ± 1.29 μM, respectively. Molecular dynamics simulations were used to reveal the interactions of kushenol I and kushenol F with GSK3β from structural and energetic perspectives.</p><p><strong>Conclusion: </strong>Kushenol I and kushenol F could be the material basis for the antibacterial, antiviral, and anti-inflammatory properties of Kushen.</p>","PeriodicalId":93961,"journal":{"name":"Current computer-aided drug design","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142549640","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":"Berberine Ameliorates High-fat-induced Insulin Resistance in HepG2 Cells by Modulating PPARs Signaling Pathway.","authors":"Lingxiao Zhang, Chenghao Yang, Xinyue Ding, Hui Zhang, Yuling Luan, Yueer Tang, Zongjun Liu","doi":"10.2174/0115734099330183241008071642","DOIUrl":"https://doi.org/10.2174/0115734099330183241008071642","url":null,"abstract":"<p><strong>Background: </strong>Berberine (BBR), also known as berberine hydrochloride, was isolated from the rhizomes of the Coptis chinensis. Studies have reported that BBR plays an important role in glycolipid metabolism, including insulin (IR). The targets, and molecular mechanisms of BBR against hyperlipid-induced IR is worthy to be further studied.</p><p><strong>Material and methods: </strong>The related targets of BBR were identified via Pharmmapper database and relevant targets of diabetes were obtained through GeneCards and Online Mendelian Inheritance in Man (OMIM) database. The common targets were employed with the STRING database and visualized with the protein-protein interactions (PPI) network. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis was performed to explore the biological progress and pathways. In vitro, human hepatocellular carcinomas (HepG2) cell was used as experimental cell line, and an insulin resistant HepG2 cell model (IR-HepG2) was constructed using free fatty acid induction. After intervention with BBR, glucose consumption and uptake in HepG2 cells were observed. Molecular docking was used to test the interaction between BBR and key targets, and real-time fluorescence quantitative PCR was used to detect the regulatory effect of BBR on related targets.</p><p><strong>Results: </strong>262 overlapped targets were extracted from BBR and diabetes. In the KEGG enrichment analysis, the peroxisome proliferator activated receptor (PPAR) signaling pathway was included. In vitro experiments, BBR can significantly increase sugar consumption and uptake in IR HepG2 cells, while PPAR inhibitors can weaken the effect of BBR on IR-HepG2.</p><p><strong>Conclusion: </strong>The PPAR signaling pathway is one of the important pathways for BBR to improve high-fat-induced insulin resistance in HepG2 cells.</p>","PeriodicalId":93961,"journal":{"name":"Current computer-aided drug design","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142483986","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":"Discovery of Novel PTP1B Inhibitors by High-throughput Virtual Screening.","authors":"Abhijit Debnath, Anjna Rani, Rupa Mazumder, Avijit Mazumder, Rajesh Kumar Singh, Shalini Sharma, Shikha Srivastava, Hema Chaudhary, Rashmi Mishra, Navneet Khurana, Jahanvi Sanchitra, Sk Ashif Jan","doi":"10.2174/0115734099278007241004105500","DOIUrl":"https://doi.org/10.2174/0115734099278007241004105500","url":null,"abstract":"<p><strong>Aim: </strong>To Discover novel PTP1B inhibitors by high-throughput virtual screening Background: Type 2 Diabetes is a significant global health concern. According to projections, the estimated number of individuals affected by the condition will reach 578 million by the year 2030 and is expected to further increase to 700 million deaths by 2045. Protein Tyrosine Phosphatase 1B is an enzymatic protein that has a negative regulatory effect on the pathways involved in insulin signaling. This regulatory action ultimately results in the development of insulin resistance and the subsequent elevation of glucose levels in the bloodstream. The proper functioning of insulin signaling is essential for maintaining glucose homeostasis, whereas the disruption of insulin signaling can result in the development of type 2 diabetes. Consequently, we sought to utilize PTP1B as a drug target in this investigation.</p><p><strong>Objective: </strong>The purpose of our study was to identify novel PTP1B inhibitors as a potential treatment for managing type 2 diabetes.</p><p><strong>Methods: </strong>To discover potent PTP1B inhibitors, we have screened the Maybridge HitDiscover database by SBVS. Top hits have been passed based on various drug-likeness rules, toxicity predictions, ADME assessment, Consensus Molecular docking, DFT, and 300 ns MD Simulations.</p><p><strong>Results: </strong>Two compounds have been identified with strong binding affinity at the active site of PTP1B along with drug-like properties, efficient ADME, low toxicity, and high stability.</p><p><strong>Conclusion: </strong>The identified molecules could potentially manage T2DM effectively by inhibiting PTP1B, providing a promising avenue for therapeutic strategies.</p>","PeriodicalId":93961,"journal":{"name":"Current computer-aided drug design","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142483987","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 Mechanism of Centipeda minima in Treating Nasopharyngeal Carcinoma Based on Network Pharmacology.","authors":"Can Huang, Xiaolin Liu, Weimo Wang, Zhen Guo","doi":"10.2174/0115734099305631240930054417","DOIUrl":"https://doi.org/10.2174/0115734099305631240930054417","url":null,"abstract":"<p><strong>Background: </strong>Centipeda minima (CM) is a traditional Chinese herbal medicine used for the treatment of sinusitis and rhinitis, and it possesses anti-cancer properties. However, the mechanism of CM in the treatment of nasopharyngeal carcinoma (NPC) remains unclear.</p><p><strong>Objective: </strong>This study aimed to explore the mechanism of CM in the treatment of NPC using a network pharmacology approach.</p><p><strong>Methods: </strong>The active components and targets of CM and NPC were screened using TCMSP, SwissTarget, and GeneCards database. The association between CM components and NPC targets or pathways was analyzed using String, Cytoscape 3.9.1, David 6.7, and AutoDock Vina. The Sangerbox platform was used to conduct differential expression and Kaplan-Meier survival analysis of core genes.</p><p><strong>Results: </strong>We identified 17 active compounds of CM and 146 corresponding targeted proteins in NPC. These targets may modulate pathways in cancer, PI3K-Akt, apoptosis, prolactin, relaxin, and TNF signaling. The top 5 core genes of the PPI network were found to be AKT1, STAT3, CASP3, EGFR, and SRC, which may be the main targets of CM in treating NPC. Molecular docking confirmed the binding energies of quercetin with CASP3, 8-Hydroxy-9,10-diisobutyryloxythymol with AKT1, and plenolin with AKT1, which were particularly low, suggesting robust and stable interactions. The expression levels of AKT1, CASP3, EGFR, SRC, MMP9, CCND1, and PTGS2 were significantly higher in head and neck squamous cell carcinoma (HNSC) samples compared to normal samples. In addition, the hub genes could predict the prognosis of HNSC as the Kaplan-Meier survival curve showed that patients with lower expressions of AKT1, STAT3, CASP3, EGFR, MMP9, ESR1, PTGS2, and PPARG had better overall survival.</p><p><strong>Conclusion: </strong>By conducting a network pharmacology approach, we revealed the main ingredients, key targets, and regulatory pathways of Centipeda minima in the treatment of NPC.</p>","PeriodicalId":93961,"journal":{"name":"Current computer-aided drug design","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142483988","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 Potential Mechanisms of Danshen for the Treatment of Ulcerative Colitis based on Serum Pharmacochemistry, Gene Expression Profiling, and Network Pharmacology: Regulation of Cell Apoptosis and Inflammatory Response.","authors":"Run-Xiang Zhai, Meng-Yu Wang, Hai-Tao Du, Chun-Xiao Yan, Zi-Wei Li, Kuo Xu, Hui Li, Xian-Jun Fu, Xia Ren","doi":"10.2174/0115734099318174240926103444","DOIUrl":"https://doi.org/10.2174/0115734099318174240926103444","url":null,"abstract":"<p><strong>Background: </strong>As a traditional Chinese medicine, Danshen shows potential efficacy for treating ulcerative colitis (UC). However, the bioactive components and mode of action were unclear.</p><p><strong>Aim of this study: </strong>This paper uses a combination of network pharmacology, serum medicinal chemistry, and gene expression profiling to clarify its possible molecular mechanism of action and material basis.</p><p><strong>Methods: </strong>Ultra-high performance liquid chromatography-mass spectrometry (UPLC-MS) was utilized to analyze the herbal components and metabolites from the serum of Danshen-treated mice. Gene expression profiles were applied to construct a database of Danshen action targets. Then, active ingredient-target-biological functional module networks were constructed to analyze the mechanism of action. Molecular docking has further confirmed the possibility of its components to the targets.</p><p><strong>Results: </strong>As a result, 193 common targets between 1684 Danshen-related DEGs and 1492 UC targets were determined as the potential targets for Danshen in treatment with UC. Serum pharmacochemistry and target prediction showed that 22 components in serum acted on 777 targets. Intersection with common targets yielded 46 core targets, and an active ingredienttarget- biological functional module network was constructed for analysis. Network prediction and molecular docking results showed that the main action modules were inflammatory response and cell apoptosis, which mainly acted on targets SRC, RELA, HSP90AA1, CTNNB1, STAT3, and CASP3. The main components of Danshen intervention in UC were predicted to include Catechol, 3,9-Dimethoxypterocarpan, 8-Prenylnaringenin, Isoferulic acid, Salvianolic acid C, and Danshensu.</p><p><strong>Conclusion: </strong>The present study provides a scientific foundation for further explicating the mechanisms of Danshen against UC.</p>","PeriodicalId":93961,"journal":{"name":"Current computer-aided drug design","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142402440","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":"Decoding the Knacks of Ellagitannin Lead Compounds to Treat Nonalcoholic Fatty Liver Disease using Computer-aided Drug Designing.","authors":"Hina Shahid, Muhammad Ibrahim, Wadi B Alonazi, Zhanyou Chi","doi":"10.2174/0115734099325555240927054614","DOIUrl":"https://doi.org/10.2174/0115734099325555240927054614","url":null,"abstract":"<p><strong>Background: </strong>The prevalence of nonalcoholic fatty liver disease (NAFLD) is increasing globally, impacting individuals in Western nations and rapid growing in Asian countries due to sedentary lifestyles; thus, NAFLD has emerged as a significant worldwide health concern. Presently, lifestyle changes represent the primary approach to managing NAFLD.</p><p><strong>Methods: </strong>This research aimed to identify the potential drug targets for treating NAFLD through comprehensive in silico computational analysis. These include the prediction of the three-dimensional structure of the protein, the prediction of inhibitors by PubChem and ZINC, molecular docking by Autodcok, pharmacophore modeling, molecular dynamics simulation by the OPLS_2005 force field, and the orthorhombic box solvent model Intermolecular Interaction Potential 3 Points Transferable to the selected compound. The toxicity of the lead compounds was analyzed through AdmetSAR software.</p><p><strong>Results: </strong>The protein associated with the PNPLA3 gene, whose overall three-dimensional structure was 95% accurate, were retrieved following inhibitor selection via PubChem and ZINC. Among the selected inhibitors and docked compounds with ID 10033935 (ellagitannin) showed a minimum E-Score of -17.266. In docking and pharmacophore modeling the compound ellagitannin shows promise as a potential drug candidate. Moreover, the molecular dynamics and structural stability of the protein-ligand complex were evaluated with several metrics such as as root mean square fluctuation and root mean square deviation and resulted in the stability not only of PNPLA3-10033935 (ellagitannin) but also of compound PNPLA3-71448940 and PNPLA3-5748394 complexed proteins at 400 ns with very slight variation.</p><p><strong>Conclusion: </strong>Overall, ellagitannin was identified as the best druggable target with the best therapeutics profile. The findings of our study can pave the way for the development of a new drug against NALFD.</p>","PeriodicalId":93961,"journal":{"name":"Current computer-aided drug design","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142396225","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 Discovery of Leptukalins, The New Potassium Channel Blockers from the Iranian Scorpion, Hemiscorpius Lepturus.","authors":"Maryam Khalili-Salmasi, Ahmad Nazarian, Amir Amirkhani, Hasan Mirzahoseini, Kamran Pooshang Bagheri","doi":"10.2174/0115734099309285240912113303","DOIUrl":"https://doi.org/10.2174/0115734099309285240912113303","url":null,"abstract":"<p><strong>Background: </strong>Blocking Kv 1.2 and Kv 1.3 potassium channels using scorpion venom- derived toxins holds potential therapeutic value. These channels are implicated in autoimmune diseases such as neurodegenerative diseases, multiple sclerosis, rheumatoid arthritis, and type 1 diabetes.</p><p><strong>Objective: </strong>The present work aims at the discovery and in silico activity analysis of potassium channel blockers (KTxs) from the cDNA library derived from the venom gland of Iranian scorpion Hemiscorpius lepturus (H. lepturus).</p><p><strong>Methods: </strong>The sequence regarding potassium channel blockers were extracted based on Gene Ontology for H. lepturus venom gland. Homology analyses, superfamily, family, and evolutionary signatures of H. lepturus KTxs (H.L KTxs) were determined by using BLASTP, COBALT, PROSITE, and InterPro servers. The predicted 3D structures of H.L KTxs were superimposed against their homologs to predict structure activity relationship. Molecular docking analysis was also performed to predict the binding affinity of H.L KTxs to Kv 1.2 and Kv 1.3 channels. Finally, the toxicity was predicted.</p><p><strong>Results: </strong>Seven H.L KTxs, designated as Leptukalin, were extracted from the cDNA library of H. lepturus venom gland. Homology analyses proved that they can act as potassium channel blockers and they belong to the superfamily and family of Scorpion Toxin-like and Short-chain scorpion toxins, respectively. Structural alignment results confirmed the activity of H.L KTxs. Binding affinity of all H.L KTxs to Kv 1.2 and Kv 1.3 channels ranged from -4.4 to -5.5 and -4 to -5.7 Kcal/mol, respectively. In silico toxicity assay showed that Leptukalin 3, Leptukalin 5, and Leptukalin 7 were non-toxic.</p><p><strong>Conclusion: </strong>Three non-toxic KTxs, Leptukalin 3, 5, and 7, were successfully discovered from the cDNA library of H. lepturus venom gland. Gathering all data together, the discovered peptides are promising potassium channel blockers. Accordingly, Leptukalin 3, 5, and 7 could be suggested for complementary in vitro studies and mouse model of autoimmune diseases.</p>","PeriodicalId":93961,"journal":{"name":"Current computer-aided drug design","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142335056","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":"Hybrid Class Balancing Approach for Chemical Compound Toxicity Prediction.","authors":"Felipe Santiago-Gonzalez, Jose L Martinez-Rodriguez, Carlos García-Perez, Alfredo Juárez-Saldivar, Hugo E Camacho-Cruz","doi":"10.2174/0115734099315538240909101737","DOIUrl":"https://doi.org/10.2174/0115734099315538240909101737","url":null,"abstract":"<p><strong>Introduction: </strong>Computational methods are crucial for efficient and cost-effective drug toxicity prediction. Unfortunately, the data used for prediction is often imbalanced, resulting in biased models that favor the majority class. This paper proposes an approach to apply a hybrid class balancing technique and evaluate its performance on computational models for toxicity prediction in Tox21 datasets.</p><p><strong>Methods: </strong>The process begins by converting chemical compound data structures (SMILES strings) from various bioassay datasets into molecular descriptors that can be processed by algorithms. Subsequently, Undersampling and Oversampling techniques are applied in two different schemes on the training data. In the first scheme (Individual), only one balancing technique (Oversampling or Undersampling) is used. In the second scheme (Hybrid), the training data is divided according to a ratio (e.g., 90-10), applying a different balancing technique to each proportion. We considered eight resampling techniques (four Oversampling and four Undersampling), six molecular descriptors (based on MACCS, ECFP, and Mordred), and five classification models (KNN, MLP, RF, XGB and SVM) over 10 bioassay datasets to determine the configurations that yield the best performance.</p><p><strong>Results: </strong>We defined three testing scenarios: without balancing techniques (baseline), Individual, and Hybrid. We found that using the ENN technique in the MACCS-MLP combination resulted in a 10.01% improvement in performance. The increase for ECFP6-2048 was 16.47% after incorporating a combination of the SMOTE (10%) and RUS (90%) techniques. Meanwhile, using the same combination of techniques, MORDRED-XGB showed the most significant increase in performance, achieving a 22.62% improvement.</p><p><strong>Conclusion: </strong>Integrating any of the class balancing schemes resulted in a minimum of 10.01% improvement in prediction performance compared to the best baseline configuration. In this study, Undersampling techniques were more appropriate due to the significant overlap among samples. By eliminating specific samples from the predominant class that are close to the minority class, this overlap is greatly reduced.</p>","PeriodicalId":93961,"journal":{"name":"Current computer-aided drug design","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142335055","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":"Mechanisms Underlying the Protective Effects of Obeticholic Acid-Activated FXR in Valproic Acid-Induced Hepatotoxicity via Network Pharmacology, Molecular Docking, and Molecular Dynamics Simulations.","authors":"Ya'nan Chen, Jingkai Zhou, Shansen Xu, Lei Wang","doi":"10.2174/0115734099324138240823041016","DOIUrl":"https://doi.org/10.2174/0115734099324138240823041016","url":null,"abstract":"<p><strong>Background: </strong>Valproic acid (VPA)-induced hepatotoxicity is among the most common and severe adverse drug reactions, limiting its clinical application. Recent studies have suggested that activating the farnesoid X receptor (FXR) could be a promising therapeutic approach to alleviate VPA-induced hepatotoxicity; however, related research remains limited.</p><p><strong>Objective: </strong>This study aims to comprehensively investigate the mechanisms underlying FXR activation by obeticholic acid (OCA) for the treatment of VPA-induced hepatotoxicity.</p><p><strong>Methods: </strong>Network pharmacology was performed to identify potential targets and pathways underlying the amelioration of VPA-induced hepatotoxicity by OCA. The identified pathways were validated through GEO data analysis, and the affinities between OCA and potential key targets were predicted using molecular docking as well as molecular dynamics simulations.</p><p><strong>Results: </strong>A total of 462 targets associated with VPA-induced hepatotoxicity and 288 targets of OCA were identified, with 81 shared targets. KEGG pathway and GO enrichment analysis indicated that the effect of OCA on VPA-induced hepatotoxicity primarily involved lipid metabolism, as well as oxidative stress and inflammation. The results from GEO data analysis, molecular docking, and molecular dynamics simulations revealed a close association between bile secretion, the PPAR signaling pathway, and the treatment of VPA-induced hepatotoxicity by OCA.</p><p><strong>Conclusion: </strong>Our findings suggest that OCA exhibits potential therapeutic efficacy against VPAinduced hepatotoxicity through multiple targets and pathways, thereby highlighting the therapeutic potential of FXR as a target for treating VPA-induced hepatotoxicity.</p>","PeriodicalId":93961,"journal":{"name":"Current computer-aided drug design","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142127728","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}