Journal of Computer-Aided Molecular Design最新文献

{"title":"Molecular dynamics simulations reveal mechanistic insights into aptamer-induced structural rearrangements in viral capsid proteins.","authors":"Chen Fei Low, Norazli Ghadin, Muhamad Arif Mohamad Jamali","doi":"10.1007/s10822-025-00633-0","DOIUrl":"10.1007/s10822-025-00633-0","url":null,"abstract":"<p><p>Macrobrachium rosenbergii nodavirus is a major viral pathogen responsible for white tail disease in giant freshwater prawn aquaculture, leading to significant economic losses. In this study, a truncated DNA aptamer, TrAptm-1 was investigated for its binding properties against both monomeric and trimeric forms of the MrNV capsid proteins. Molecular dynamics simulations coupled with MM/PBSA binding free energy calculations revealed that TrAptm-1 exhibited a higher binding affinity to the trimeric capsid protein (-153.95 ± 6.74 kcal/mol) compared to the monomeric form (-120.77 ± 2.46 kcal/mol). TrAptm-1 binding induced significant conformational changes and structural rearrangements in the capsid protein, highlighted the antiviral potential of TrAptm-1 to interfere with the capsid protein self-assembly process. The observed structural changes demonstrated the importance of the oligomeric state in aptamer-capsid protein interactions, emphasizing that extended simulations up-to microseconds are required to capture the slow conformational rearrangements characteristic of large oligomeric protein complexes. These findings provide a molecular basis for the development of aptamer-based antiviral strategies, and the design of biosensor for early detection of MrNV in aquaculture settings.</p>","PeriodicalId":621,"journal":{"name":"Journal of Computer-Aided Molecular Design","volume":"39 1","pages":"57"},"PeriodicalIF":3.0,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12287205/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144688533","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Anti-inflammatory potential of Grewialin from Grewia optiva: insights from molecular docking, ADMET, DFT, and in-vitro studies.","authors":"Wali Ullah, Ghias Uddin, Abdur Rauf, Muhammad Umer Khan, Zuneera Akram, Chaudhry Ahmed Shabbir, Abdulhakeem S Alamri, Walaa F Alsanie, Marcello Iriti","doi":"10.1007/s10822-025-00632-1","DOIUrl":"https://doi.org/10.1007/s10822-025-00632-1","url":null,"abstract":"<p><p>Grewia optiva, a medicinal plant native to northern Pakistan, has traditionally been valued for managing pain and inflammation. Among its bioactive constituents, Grewialin, a compound isolated from the stem bark, has garnered attention as a promising candidate for anti-inflammatory drug development. This study aimed to evaluate the anti-inflammatory potential of Grewialin using a combination of in-silico and in-vitro approaches, focusing on its effects on lipoxygenase (LOX) and neutrophil respiratory burst activity. Furthermore, the pharmacological and toxicological profiles of Grewialin were assessed to support its potential as a lead compound. Structure-based virtual screening identified Grewialin as a potential LOX inhibitor. Molecular docking studies revealed a significant binding score of -6.874 kcal/mol, indicating strong interactions with the active site of the LOX enzyme (5-LOX). ADMET profiling demonstrated its favourable pharmacokinetic and toxicological properties, while density functional theory (DFT) calculations highlighted its balanced electrophilic and nucleophilic properties, reflecting its chemical stability and reactivity. Experimental validation through in vitro assays confirmed Grewialin's potent inhibitory activity against LOX, with an IC50 value of 31.9 ± 0.03 µM. Additionally, Grewialin effectively inhibited neutrophil respiratory burst activity, achieving an IC50 of 317.62 ± 0.059 µM, further supporting its anti-inflammatory potential. These findings position Grewialin as a multifaceted anti-inflammatory agent with dual action targeting LOX and neutrophil respiratory burst activity. The combined in-silico and in-vitro results underscore its potential as a lead compound for developing anti-inflammatory drugs. Further research is warranted to explore its therapeutic mechanisms and optimize its efficacy, bridging traditional medicinal knowledge with modern pharmacological advancements. It is worth mentioning, though, that, in line with the aforementioned dual inhibitory profiles, Grewialin also demonstrated moderate potency (LOX and neutrophil respiratory), thus indicating that additional structural optimization or adequate formulation design is necessary to progress it toward therapeutic development. By leveraging the unique properties of Grewialin, this study contributes to the ongoing pursuit of novel, natural compounds for the effective management of inflammatory diseases. This comprehensive evaluation highlights the significance of Grewia optiva as a source of bioactive compounds, emphasizing the need for further exploration into its pharmacological application.</p>","PeriodicalId":621,"journal":{"name":"Journal of Computer-Aided Molecular Design","volume":"39 1","pages":"56"},"PeriodicalIF":3.0,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144688532","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparison study of dominant molecular sequence representation based on diffusion model.","authors":"Yongrui Cui, Dongjing Shan, Qiheng Lu, Beijia Zou, Huali Zhang, Jin Li, Jiashun Mao","doi":"10.1007/s10822-025-00614-3","DOIUrl":"https://doi.org/10.1007/s10822-025-00614-3","url":null,"abstract":"<p><p>In recent years, the emergence of large language models (LLMs), particularly the advent of ChatGPT, has positioned natural language sequence-based representation learning and generative models as the dominant research paradigm in AI for science. Within the domains of drug discovery and computational chemistry, compound representation learning and molecular generation stand out as two of the most significant tasks. Currently, the predominant molecular representation sequences used for molecular characterization and generation include SMILES (Simplified Molecular-Input Line-Entry System), SELFIES (SELF-referencing Embedded Strings), SMARTS (Smiles Arbitrary Target Specification), and IUPAC (International Union of Pure and Applied Chemistry) nomenclature. In the context of AI-assisted drug design, each of these molecular languages has its own strengths and weaknesses, and the granularity of information encoded by different molecular representation forms varies significantly. However, the selection of an appropriate molecular representation as the input format for model training is crucial, yet this issue has not been thoroughly explored. Furthermore, the state-of-the-art models currently employed for molecular generation and optimization are diffusion models. Therefore, this study investigates the characteristics of the four mainstream molecular representation languages within the same diffusion model for training generative molecular sets. First, a single molecule is represented in four different ways through varying methodologies, followed by training a denoising diffusion model using identical parameters. Subsequently, thirty thousand molecules are generated for evaluation and analysis. The results indicate that the four molecular representation languages exhibit both similarities and differences in attribute distribution and spatial distribution; notably, SELFIES and SMARTS demonstrate a high degree of similarity, while IUPAC and SMILES show substantial differences. Additionally, IUPAC's primary advantage lies in the novelty and diversity of generated molecules, whereas SMILES excels in QEPPI and SAscore metrics, with SELFIES and SMARTS performing best on the QED metric. The findings of this research will provide crucial insights into the selection of molecular representations in AI drug design tasks, thereby contributing to enhanced efficiency in drug development.</p>","PeriodicalId":621,"journal":{"name":"Journal of Computer-Aided Molecular Design","volume":"39 1","pages":"54"},"PeriodicalIF":3.0,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144658039","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Design, synthesis, evaluation and molecular modeling of quinazoline derivatives bearing amino acids as small-molecule PD-L1 inhibitors.","authors":"Han Liu, Roufen Chen, Dandan Yuan, Yidan Xing, Xueyan Ding, Xingye Wu, Yali Gao, Junjie Ma","doi":"10.1007/s10822-025-00635-y","DOIUrl":"https://doi.org/10.1007/s10822-025-00635-y","url":null,"abstract":"<p><p>Herein, we reported a series of quinazoline derivatives bearing amino acids by introducing a rigid pyrimidine structure between the 2 and 3-positions of the biphenyl and establishing an ionic interaction with Lys124 of PD-L1. Evaluation of the PD-1/PD-L1 inhibitory activity identified compound 7, which exhibited the most potent inhibitory activity with an IC₅₀ value of 7.21 nM. Molecular docking was performed to demonstrate that the carboxyl group of amino acid in the tail established an ionic interaction with the ε-NH₃⁺ of Lys124, enhancing the binding. Importantly, molecular dynamics study revealed that the nitrogen atom in the nicotinonitrile formed water-mediated interactions with Asn63 of PD-L1, that stabilized the binding of the compound to PD-L1, providing an important and reasonable explanation for the introduction of nicotinonitrile to enhance inhibitory activity. Our study provides valuable guidance for further design of potent quinazoline-based small-molecule PD-L1 inhibitors, and identifies the compound 7 that is a promising lead compound and deserves further investigation.</p>","PeriodicalId":621,"journal":{"name":"Journal of Computer-Aided Molecular Design","volume":"39 1","pages":"55"},"PeriodicalIF":3.0,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144658040","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrated machine learning and deep learning-based virtual screening framework identifies novel natural GSK-3β inhibitors for Alzheimer's disease.","authors":"Ya Zhou, Ben-Rong Mu, Xing-Yi Chen, Li Liu, Qing-Lin Wu, Mei-Hong Lu, Feng-Ling Qiao","doi":"10.1007/s10822-025-00637-w","DOIUrl":"https://doi.org/10.1007/s10822-025-00637-w","url":null,"abstract":"<p><p>Alzheimer's disease (AD) is a progressive neurodegenerative disorder lacking effective therapies. Glycogen synthase kinase-3β (GSK-3β), a key regulator of Aβ aggregation and Tau hyperphosphorylation, has emerged as a promising therapeutic target. Here, we present a novel two-stage virtual screening (VS) framework that integrates an interpretable random forest (RF) model (AUC = 0.99) with a deep learning-based molecular docking platform, KarmaDock (NEF_0.5% = 1.0), to identify potential GSK-3β inhibitors from natural products. The model's interpretability was enhanced using SHAP analysis to uncover key fingerprint features driving activity predictions. A curated natural compound library (n = 25,000) from TCMBank and HERB was constructed under drug-likeness constraints, and validated using multi-level decoy sets. Three compounds derived from Clausena and Psoralea exhibited favorable pharmacokinetic profiles in silico, including blood-brain barrier permeability and low neurotoxicity. Molecular docking, pharmacophore modeling, and molecular dynamics simulations confirmed their stable interactions with critical GSK-3β binding sites. Notably, our approach combines explainability and deep learning to enhance screening accuracy and interpretability, addressing limitations in traditional black-box models. While current findings are computational, they offer theoretical support and provide actionable leads for future experimental validation of natural GSK-3β inhibitors.</p>","PeriodicalId":621,"journal":{"name":"Journal of Computer-Aided Molecular Design","volume":"39 1","pages":"53"},"PeriodicalIF":3.0,"publicationDate":"2025-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144641363","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mechanistic insights into PROTAC-mediated degradation through an integrated framework of molecular dynamics, free energy landscapes, and quantum mechanics: A case study on kinase degraders.","authors":"Ashis Nandy, Kiran Boppana, Samiron Phukan","doi":"10.1007/s10822-025-00630-3","DOIUrl":"https://doi.org/10.1007/s10822-025-00630-3","url":null,"abstract":"<p><p>Targeted protein degradation by proteolysis-targeting chimeras (PROTAC) is dependent on formation and plasticity of ternary complexes enabling ubiquitination. In this study, we employed long-timescale molecular dynamics (MD) simulations, free energy landscape analysis, and quantum mechanical (QM) calculations to investigate the molecular determinants of PROTAC efficacy. Using three model systems (FAK-VHL, BTK-CRBN, and TTK-CRBN), each with three PROTACs of varying potencies, we analyzed a total of nine ternary complexes over 500 ns MD simulations each. Simulation events analysis revealed that potent PROTACs maintain stable and important interactions between the protein of interest (POI) and the E3 ligase, while weaker PROTACs exhibit diminished or no interactions. Conformational dynamics and changes in the interaction patterns between the POI-E3-ligase complexes highlighted the importance of ternary complex plasticity in degradation efficiency. These findings were also supported by the distribution of free energy landscape during simulations. Distributions of the free energy landscape offer insights into the stability of population states and open new avenues for understanding their degradation potential. Additionally, to overcome the limitation of conventional docking models, we highlight the importance of QM and DFT based methods to predict the impact of binding at the E3-ligase site which corelates with the degradation potentials of PROTACs. These insights provide a new computational framework for rational PROTAC design.</p>","PeriodicalId":621,"journal":{"name":"Journal of Computer-Aided Molecular Design","volume":"39 1","pages":"51"},"PeriodicalIF":3.0,"publicationDate":"2025-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144641364","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Protein domain movement involved in binding of belinostat and HPOB as inhibitors of histone deacetylase 6 (HDAC6): a hybrid automated-interactive docking study.","authors":"Georgios Iakovou, L Palmer, A Ganesan, Akio Kitao, Stephen D Laycock, Steven Hayward","doi":"10.1007/s10822-025-00636-x","DOIUrl":"10.1007/s10822-025-00636-x","url":null,"abstract":"<p><p>DockIT is a tool for interactive molecular docking that can model both the local and global conformational response of the receptor to the docking of a ligand based on information from a molecular dynamics simulation. Using DockIT we have investigated the binding process of two histone deacetylase (HDAC) inhibitors to HDAC6: the nonselective approved drug belinostat and the preclinical HPOB. To model HDAC6's conformational response to the binding of the inhibitors we performed a 200-nanosecond explicit-solvent molecular dynamics simulation on HDAC6. Unexpectedly the simulation revealed a domain movement that affects the size and shape of the binding pocket. Using automated docking and a rigid model for the inhibitors, the domain movement continuously adapts the pocket to the presence of the inhibitor. For both inhibitors, an intermediate binding site was found where it was partially inserted, with a hydrogen bond formed between the inhibitor's hydroxamic acid and the Tyr745 side chain. Pushing the inhibitor deeper into the pocket over an energy barrier and re-engaging automated docking, a final binding pose resulted with a root-mean square deviation with its respective crystallographic pose of 1.0 Å for belinostat and 1.4 Å for HPOB. We believe our results mimic substrate recognition by the enzyme, with an initial partial binding of the acetyllysine residue with Tyr745. During binding a relay of hydrogen bonds occurs coordinating the orientation of the cap and the hydroxamic acid inside the pocket. The interaction between the cap and the surface of HDAC6 explains the reason for the hydroxamic acid warhead in HPOB binding in a flipped orientation compared to belinostat.</p>","PeriodicalId":621,"journal":{"name":"Journal of Computer-Aided Molecular Design","volume":"39 1","pages":"52"},"PeriodicalIF":3.0,"publicationDate":"2025-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12263812/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144641365","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"\"Heptadecanol\" a phytochemical multi-target inhibitor of SMYD3 & GFPT2 proteins in non-small cell lung cancer: an in-silico & in-vitro investigation.","authors":"Lokesh Ravi, Pratishtha Jain, Ajith Kumar K, Jeevan Kumar M, Mukti Panda, Harshitha S, Mohammed Abdul Kareem, K Sivani Yelchuri Sai, Ayman Fathima, V Jensha, Adarsh Anurag Rai, Hida Amal Faizal, Shrivats S R, Ankitha Ajith, Derick Yesudas, Vaarruni S, Varshini S, Raksha Shetty, Aditi Jha, Gundlapalli Saradha Janaki, Varsha Hannah George, Stalin Nithaniyal, Mookkandi Palsamy Kesavan, Sajith Ahamed A, Sankara Narayanan A","doi":"10.1007/s10822-025-00627-y","DOIUrl":"https://doi.org/10.1007/s10822-025-00627-y","url":null,"abstract":"<p><p>Understanding the mechanism of action of anticancer agent plays a key role in effective clinical application of natural products. This study aims to identify an anti-cancer phytochemical with multi-target inhibition potential against non-small cell lung cancer. This study employs virtual screening of 8352 phytochemicals by molecular docking (AutoDock Vina & SeeSAR) to identify potential inhibitor of KRas, SMYD3, ALDH1 and GFPT2 proteins. Molecular Dynamics Simulation (Desmond) simulation for extensive 500 ns duration was performed to validate the inhibition potential. Followed by cell biology studies i.e., MTT assay, Flowcytometry and qRT-PCR analysis to confirm the mechanism of action. Molecular Docking and Molecular Dynamics Simulation studies predicted Heptadecanol as potential inhibitor of three drug targets, i.e., KRas, SMYD3 and GFPT2. In-vitro cytotoxicity assay confirmed the anti-cancer cytotoxicity of Heptadecanol with a significant IC₅₀ value of 3.12 µg/ml selectively target cancer cells (A549), without substantial toxicity to non-cancerous cells (L929) with IC₅₀ of > 100 µg/ml. Flowcytometry analysis with Annexin-V and Propedium Iodide staining further confirmed the apoptotic potential of Heptadecanol against A549 cells. qRT-PCR analysis demonstrated a robust increase in GFPT2 (25.6 × fold) and SMYD3 (16.98 × fold) gene expression, that conclusively confirmed the multi-target inhibition potential of Heptadecanol. Results of the study concludes that Heptadecanol is a significant inhibitor of GFPT2 and SMYD3 protein, there by exhibiting selective anti-cancer activity against the investigated non-small cell lung cancer cells. Further in-vivo studies are in demand to quantify the anti-cancer efficacy in a living system.</p>","PeriodicalId":621,"journal":{"name":"Journal of Computer-Aided Molecular Design","volume":"39 1","pages":"49"},"PeriodicalIF":3.0,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144635858","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Therapeutic potency of a developed optimized polyherbal formulation in ameliorating obesity induced inflammation and oxidative stress in Swiss albino mice by targeting PPARγ, insulin receptor and AMPK signalling pathway.","authors":"Pritimoni Das, Manas Das","doi":"10.1007/s10822-025-00625-0","DOIUrl":"https://doi.org/10.1007/s10822-025-00625-0","url":null,"abstract":"<p><p>High fat diet (HFD) induced obesity plays a key role in onset of inflammation, a chronic response of the body to elevated expression of proinflammatory cytokines. Our work emphasized on assessing the therapeutic potency of the polyherbal formulations (PHF), composed of Phyllanthus urinaria and Adhatoda vascia nees by studying the expression pattern of iNOS, pro, anti-inflammatory cytokines, chemokine along with identification of potent anti-inflammatory compounds in HFD induced inflammation in four weeks old (23-25 g bw, n = 6 in triplcates) Swiss albino mice. The findings demonstrated high percentage of free radical scavenging property of PHF, downregulation of expression level of proinflammatory cytokines and chemokines, profound elevation of anti-inflammatory cytokines, anti-oxidant enzymes in both PHF treated groups signifying protection against oxidative stress. In silico study revealed binding energy of Okanin, Vomicine, Granisetron and Pisdic acid - 9.31 kcal/mol, - 8.34 kcal/mol, - 8.10 kcal/mol, - 7.93 kcal/mol respectively with strong protein ligand interaction with inflammatory, lipid marker PPARγ and insulin resistance marker protein receptor INSR. Among other four ligands, Peganine, Coralyne, Soraphen O and 2-hydroxyhexadecanoic acid; Soraphen O and Coralyne showed best binding affinity with INSR (- 6.8 kcal/mol) and PPARγ (- 6.9 kcal/mol) respectively. The evaluation based on network pharmacology, the active ingredients of the PHF for AMPK signalling pathway and protein analysis identified 121 targets. A network of interaction between the eight ligands and known therapeutic targets of INSR and AMPK depicted pharmacological mechanisms of the PHF in inhibition of insulin resistance by activating INSR and AMPK-pathway thus establishing itself as potent alternative drug in treating ailments associated with obesity induced inflammation.</p>","PeriodicalId":621,"journal":{"name":"Journal of Computer-Aided Molecular Design","volume":"39 1","pages":"50"},"PeriodicalIF":3.0,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144635859","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"CoBdock-2: enhancing blind docking performance through hybrid feature selection combining ensemble and multimodel feature selection approaches.","authors":"Sadettin Y Ugurlu","doi":"10.1007/s10822-025-00629-w","DOIUrl":"https://doi.org/10.1007/s10822-025-00629-w","url":null,"abstract":"<p><p>Identifying orthosteric binding sites and predicting small molecule affinities remains a key challenge in virtual screening. While blind docking explores the entire protein surface, its precision is hindered by the vast search space. Cavity detection-guided docking improves accuracy by narrowing focus to predicted pockets, but its effectiveness depends heavily on the quality of cavity detection tools. To overcome these limitations, we developed Consensus Blind Dock (CoBDock), a machine learning-based blind docking method that integrates molecular docking and cavity detection results to enhance binding site and pose prediction. Building on this, CoBDock-2 replaces traditional docking tools by extracting 1D numerical representations from protein, ligand, and interaction structural features, and applying advanced ensemble feature selection techniques. By evaluating 21 feature selection methods across 9,598 features, CoBDock-2 identifies key molecular characteristics of orthosteric binding sites. CoBDock-2 demonstrates consistent improvements over the original CoBDock across benchmark datasets (PDBBind v2020-general, MTi, ADS, DUD-E, CASF-2016), achieving 77% binding site identification accuracy (within 8 Å), 55% ligand pose prediction accuracy (RMSD <math><mo>≤</mo></math> 2 Å), a 19% reduction in the mean distance to ground truth ligands within the binding site, and an 18.5% decrease in the mean pose RMSD. Statistical analysis across the combined benchmark set confirms the significance of these improvements ( <math><mrow><mtext>p</mtext> <mo><</mo> <mn>0.05</mn></mrow> </math> ). Notably, the Weighted Hybrid Feature Selection variant in CoBDock-2 further increases binding site accuracy to 79.8%, demonstrating the benefit of combining multimodel and ensemble feature selection strategies. Variability in predictions also decreased significantly, highlighting enhanced reliability and generalizability. Also, a low-bias hypothetical comparison with a state-of-the-art DiffDock + NMDN method was conducted to position CoBDock-2 relative to modern deep learning-based docking strategies.</p>","PeriodicalId":621,"journal":{"name":"Journal of Computer-Aided Molecular Design","volume":"39 1","pages":"48"},"PeriodicalIF":3.0,"publicationDate":"2025-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144615678","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}