In silico pharmacology最新文献

{"title":"Targeting SAM-dependent methyltransferase in <i>Mycobacterium avium</i> complex (MAC) with natural products: ADMET and computational profiling.","authors":"Anindita Banerjee, Saubashya Sur","doi":"10.1007/s40203-026-00710-8","DOIUrl":"10.1007/s40203-026-00710-8","url":null,"abstract":"<p><p>The <i>Mycobacterium avium</i> complex (MAC) comprises non-tuberculous mycobacteria that cause respiratory infections in vulnerable humans and diseases in animals. Treating these infections is problematic owing to the persistence of MAC inside hosts, antibiotic resistance, and adverse side effects. SAM-dependent methyltransferase is a key enzyme altering lipids and metabolites, as well as regulates cell wall permeability and virulence. Specifically, the ability of SAM-dependent methyltransferase to modify mycolic acid has made it a drug target for fighting persistent infections. To prevent the increasing MAC infections, targeting virulent genes and the discovery of novel drugs are necessary. Moreover, because of the limitations of existing therapies, alternative strategies are essential. This in silico analysis emphasised screening natural products, assessing their pharmacokinetic and toxicity properties, molecular docking with the SAM-dependent methyltransferase of MAC, followed by molecular simulations. The intention was to detect lead compounds acting against SAM-dependent methyltransferase. In this regard, eight natural products with suitable ADMET properties were finalised. Artificial intelligence-based modelling of SAM-dependent methyltransferase generated high-quality three-dimensional structures. Their molecular docking with the eight natural products identified docked complexes with binding energies ranging from - 4.7 to -10.3 kcal/mol. Molecular simulations with iMODS confirmed the stability and robustness of the docking complexes. Notably, demethoxycurcumin (-10.3 kcal/mol) and bisdemethoxycurcumin (-10.2 kcal/mol) exhibited superior binding affinities with the SAM-dependent methyltransferase of <i>M. avium</i> 104. These were the top compounds targeting SAM-dependent methyltransferase. This research provided evidence for drug target identification, although further experimental validation is required to translate this in silico outcome into clinical use.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1007/s40203-026-00710-8.</p>","PeriodicalId":94038,"journal":{"name":"In silico pharmacology","volume":"14 2","pages":"195"},"PeriodicalIF":0.0,"publicationDate":"2026-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13373148/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148474845","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrative network pharmacology and transcriptomics analysis reveals the multi-target anti-allergic mechanism of ginsenoside Rh1.","authors":"Chao Chen, Yan Li, Yi Wang, Hongshan Yu, Siyu Xu","doi":"10.1007/s40203-026-00705-5","DOIUrl":"10.1007/s40203-026-00705-5","url":null,"abstract":"<p><p>Allergic diseases, characterized by an excessive immune response to allergens, pose a significant global health challenge with limited curative options. Ginsenoside Rh1, a rare ginsenoside derived from ginseng, has shown potential in alleviating allergic inflammation, yet its comprehensive mechanism remains unclear. This study employed an integrated approach combining network pharmacology, molecular docking, molecular dynamics simulations, and transcriptomics analysis to systematically explore the multi-target mechanisms of Rh1 against allergy. A total of 272 potential targets of Rh1 related to allergic reactions were identified. Subsequent protein-protein interaction (PPI) network analysis and molecular docking identified four key targets: ALB, CASP3, NFKB1 and STAT3. Molecular dynamics simulations indicated stable binding interactions between Rh1 and these targets. Functional enrichment analysis revealed that the therapeutic effects were primarily associated with the MAPK signaling pathway, Th17 cell differentiation pathway and PI3K-Akt signaling pathway. To contextualize these predictions within human disease biology, we analyzed public transcriptomic datasets (GSE50223, GSE232127) from allergic patients. This independent analysis showed that the predicted core targets are dysregulated in human allergy and that key pathways such as IL-6/JAK/STAT3 signaling are enriched, underscoring their relevance to Th17/IL-17 axis activation. These findings suggest that ginsenoside Rh1 may mitigate allergic reactions through a multi-target and multi-pathway network, providing a theoretical basis for its development as a promising anti-allergic agent.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1007/s40203-026-00705-5.</p>","PeriodicalId":94038,"journal":{"name":"In silico pharmacology","volume":"14 2","pages":"191"},"PeriodicalIF":0.0,"publicationDate":"2026-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13365283/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148451086","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Therapeutic potential of <i>Leonotis leonurus</i> and <i>Mentha longifolia</i> in depression: insights from network pharmacology and molecular dynamics stimulation-based study.","authors":"Caroline Mooki, Oladunni M Ayodele, Saheed Sabiu, Adeyemi O Aremu, Makhotso Lekhooa","doi":"10.1007/s40203-026-00689-2","DOIUrl":"10.1007/s40203-026-00689-2","url":null,"abstract":"<p><p>Medicinal plants offer promising multi-target therapeutic agents due to their diverse bioactive compounds. This study explored LC-MS profiling, network pharmacology, molecular docking, and molecular dynamics simulation to investigate the potential antidepressant-related mechanisms of <i>Leonotis leonurus</i> and <i>Mentha longifolia</i>. A total of 20 and 15 compounds were identified in <i>L. leonurus</i> and <i>M</i>. <i>longifolia</i>, respectively. Target prediction and overlap analysis revealed 16 and 22 depression-associated targets for each plant. These targets were used to construct protein-protein interaction networks and perform Gene Ontology and KEGG pathway enrichment analyses. For <i>L</i>. <i>leonurus</i>, the key targets included <i>SLC</i> ₆ <i>A</i> ₄, <i>PTGS</i> ₂, <i>MAOA</i>, and <i>MAOB</i> were enriched in serotonergic and dopaminergic synapse pathways, neuroactive ligand-receptor interaction, and <i>PI</i> _<i>3</i> <i>K/Akt</i> signalling, suggesting, suggesting potential involvement in neurotransmission and neuroinflammatory regulation. Molecular docking showed strong interactions of procyanidin B5 and chrysoeriol with <i>SLC</i> ₆ <i>A</i> ₄ and <i>MAOA</i>, respectively, while baicalin demonstrated the most favourable binding affinity (- 39.45 kcal/mol), exceeding that of fluoxetine (- 14.69 kcal/mol), both surpassing fluoxetine's affinity (- 14.69 kcal/mol) to <i>SLC</i> ₆ <i>A</i> ₄. For <i>M. longifolia</i>, targets such as <i>DRD</i> ₄, <i>DRD</i> ₃, <i>GSK</i> ₃ <i>β</i>, <i>COMT</i>, and <i>AKT</i> _<i>1</i> were linked to dopaminergic synapse and neuroactive ligand-receptor pathways. Key compounds, including baicalin, salvianolic acid A, and rosmarinic acid, showed strong binding to <i>DRD</i> ₄, <i>DRD</i> ₃, and <i>GSK</i> ₃ <i>β</i>. Notably, quercetin 3-galactoside exhibited the highest affinity toward <i>DRD</i> ₄ (- 46.74 kcal/mol), outperforming fluoxetine (- 24.91 kcal/mol). Collectively, these findings suggest that both plants may possess antidepressant-related potential through predicted multi-component, multi-target modulation of neurotransmitter systems and neuroinflammatory pathways. However, these findings remain computational and require experimental validation to confirm biological efficacy and therapeutic relevance. This study provides a mechanistic framework to support future pharmacological investigations into the traditional use of these medicinal plants for mental health applications.</p><p><strong>Graphical abstract: </strong></p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1007/s40203-026-00689-2.</p>","PeriodicalId":94038,"journal":{"name":"In silico pharmacology","volume":"14 2","pages":"193"},"PeriodicalIF":0.0,"publicationDate":"2026-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13365280/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148451093","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Phytochemical profiling and in silico evaluation of <i>Ficus racemosa</i> fruit extract as potential α-amylase and α-glucosidase inhibitors.","authors":"Ananta Swargiary, Debojani Narzary, Bilima Brahma","doi":"10.1007/s40203-026-00703-7","DOIUrl":"10.1007/s40203-026-00703-7","url":null,"abstract":"<p><p>Diabetes mellitus is a chronic metabolic disorder characterized by persistent hyperglycemia. <i>Ficus racemosa</i> is a widely used ethnomedicinal plant with known antidiabetic and antioxidant properties. The present study investigated the antidiabetic potential of the plant using LC-MS-based phytochemical profiling, molecular docking, molecular dynamics simulation (MDS), and MM-PBSA analysis. LC-MS analysis of the diethyl ether extract of <i>F. racemosa</i> identified 56 bioactive compounds. Molecular docking analysis showed phytocompound usambarensine as the best-performing ligand against both α-amylase (- 10.8 kcal/mol) and α-glucosidase (- 9.6 kcal/mol). van der Waals interactions were the most predominant forces contributing to protein-ligand binding, followed by H-bonds. MDS was performed to investigate the stability and interaction dynamics of α-amylase and α-glucosidase complexes with the test ligand and the reference inhibitor acarbose. Docking results indicated comparatively higher predicted binding affinities for the test ligand (- 10.8 and - 9.6 kcal/mol) than acarbose (- 8.1 and - 7.2 kcal/mol) against α-amylase and α-glucosidase, respectively. However, MDS suggested comparatively greater dynamic stability for the acarbose complexes. RMSD and RMSF analyses indicated higher structural flexibility in the apo proteins, whereas ligand-bound systems exhibited reduced fluctuations, suggesting ligand-induced stabilization. The radius of gyration remained stable throughout the simulation, indicating preserved structural compactness of the enzymes. H-bond and H-bond occupancy analyses demonstrated persistent interactions with favorable donor-acceptor geometry. Furthermore, principal component analysis revealed broader conformational sampling in apo proteins and more compact clusters in ligand-bound complexes. Center-of-mass analysis also confirmed stable ligand-enzyme interactions. Overall, the results suggest potential stable interactions between the phytocompound and both target enzymes.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1007/s40203-026-00703-7.</p>","PeriodicalId":94038,"journal":{"name":"In silico pharmacology","volume":"14 2","pages":"192"},"PeriodicalIF":0.0,"publicationDate":"2026-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13365076/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148451048","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rational design of a multi-epitope vaccine for hand, foot, and mouth disease: an in silico perspective.","authors":"Sunil Desai, Sneha Dokhale, Shine Devarajan, Mugdha Pathak","doi":"10.1007/s40203-026-00695-4","DOIUrl":"10.1007/s40203-026-00695-4","url":null,"abstract":"<p><p>Hand, Foot, and Mouth Disease (HFMD) presents a serious public health concern, especially in children below five years of age and is predominantly caused by Coxsackievirus A16 (CV-A16) and Enterovirus 71 (EV-A71). Despite the availability of supportive treatments and strain-specific protection offered by existing monovalent vaccines, there is an urgent need for a broadly effective, widely accessible multivalent vaccine. This study implements reverse vaccinology to design a multiepitope vaccine targeting key immunogenic regions of CV-A6, CV-A16 and EV-A71. From 18,278 VP1 capsid protein sequences, redundancy was eliminated using CD-HIT (90% identity threshold), yielding 4,309 non-redundant sequences. Further screening for antigenic potential, non-allergenicity, non-toxicity, resulted in 306 qualified candidates for epitope prediction analysis. Highly immunogenic B-cell (BCPred score > 0.8, specificity > 75%), CTL (MHC-I binding IC50 < 200 nM), and HTL (MHC-II binding IC50 < 200 nM) epitopes were predicted from these sequences and integrated into four chimeric vaccine constructs. Among these the Vaccine 4 (V4) construct exhibited optimal structural stability. Molecular docking of the V4 construct with human Toll-Like Receptor 4 (TLR4) revealed a strong complex with a ClusPro-weighted score of -801.3 kcal/mol. Molecular dynamics simulations over 120 ns showed V4-TLR4 complex stabilization with RMSD values of 0.3-0.4 nm. C-ImmSim immune simulation predicted a predominant Th1/Th17 immune response, characterized by robust B-cell activation with peak IgG1 antibody titres, progressive memory B-cell formation, and effective antigen clearance upon repeated exposure. Epitopes of the designed construct projected a broad global HLA coverage (99.06%), including 92.71% in India. The V4 construct was codon-optimized for expression in E. coli achieving a Codon Adaptation Index (CAI) of 0.95. This computationally validated V4 multi-epitope vaccine candidate offers a promising, cross-protective strategy against major HFMD-causing enteroviruses, providing a robust preclinical framework that warrants subsequent experimental validation.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1007/s40203-026-00695-4.</p>","PeriodicalId":94038,"journal":{"name":"In silico pharmacology","volume":"14 2","pages":"194"},"PeriodicalIF":0.0,"publicationDate":"2026-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13365281/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148451113","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Insilico study to unveil the characteristics of pseudoRab GTPases in pathogenic protozoan parasites: <i>Entamoeba histolytica</i>.","authors":"Mrinalini Roy, Kinjal Desai, Zeel Parmar, Tarini Rajput, Jaikee Kumar Singh, Sanket Kaushik, Sandeep Kumar Srivastava, Anupam Jyoti, Vijay Kumar Srivastava","doi":"10.1007/s40203-026-00692-7","DOIUrl":"10.1007/s40203-026-00692-7","url":null,"abstract":"<p><p><i>Entamoeba histolytica (Eh</i>) is a parasite that utilizes atypical vesicular transport system supported by a huge repertoire of pseudoRab GTPases, to cause amoebic liver abscesses. We have identified 57 pseudoRab GTPases and classified them into 3 classes: 17 Class i enzymes considered GDP-locked enzymes due to low affinity for GTP, 20 Class ii enzymes have attenuated or lost GTPase ability, thus considered GTP-locked; Class iii houses 20 functional enzymes. Evolutionary analysis corroborated the G-motif based classification instead of whole sequence because they house large variations. The evolutionary direction cannot be determined, indicating the possibility of simultaneous emergence of the paralogs of the classical Rab GTPase in <i>Eh.</i> The possible evolutionary mechanisms include gene duplication, domain duplication, and subtle substitutions during recombination events. In-depth Molecular dynamic (MD) simulation provided insight into the dynamic behaviour of the non-canonical Rab members. It suggests that Class i member <i>Eh</i>RabX31 may have lost affinity to GTP due to the distorted binding pocket formed by divergent G4 motif (AKxD) and remains GDP-locked. However, class ii member <i>Eh</i>RabX10 that shows stable GTP binding, may remain GTP-locked due to divergent G3 motif (DTxDM) abrogating GTP hydrolysis capacity. Furthermore, <i>Eh</i>RabX10 showed conformation changes in silico wherein Switch II changed conformations to bind to GTP. This pioneering study has provided insights into a family of viable drug candidates owing to their roles in <i>Eh</i> pathology and their uniqueness that makes them specific to target <i>Eh</i>.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1007/s40203-026-00692-7.</p>","PeriodicalId":94038,"journal":{"name":"In silico pharmacology","volume":"14 2","pages":"190"},"PeriodicalIF":0.0,"publicationDate":"2026-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13356131/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148431701","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Computational design and validation of a multi-epitope subunit vaccine against the neglected parasite <i>blastocystis</i> sp.","authors":"Amirtesh Raghuram, Gayathri Mahalingam","doi":"10.1007/s40203-026-00660-1","DOIUrl":"10.1007/s40203-026-00660-1","url":null,"abstract":"<p><p><i>Blastocystis</i> sp. is a neglected, globally prevalent intestinal parasite infecting over one billion people with no available vaccine. This study describes an immunoinformatics framework for developing a multi-epitope subunit vaccine against α-L-fucosidase from <i>Blastocystis</i> sp. Immunogenic B-cell and T-cell epitopes were identified through systematic prediction and rigorous allergenicity, toxicity, and human homology screening. Epitopes were assembled into a vaccine with human β-defensin-3 as an N-terminal adjuvant. The vaccine displayed favorable physicochemical properties including optimal molecular weight (~ 38 kDa), stability index (< 40) and negative GRAVY score. Population coverage analysis achieved 97.13% global coverage with 24.75 epitope-HLA hits per individual and a PC90 of 14.42. Structural validation of predicted 3D structure using Ramachandran analysis (99.7% residues in favored regions) and ProSA-web evaluation (Z-score: - 5.07) confirmed high-quality tertiary structure. Molecular docking revealed extensive binding with TLR-4, MHC Class I, and MHC Class II receptors, with interface areas of 1379-2198 Ų and 13-19 hydrogen bonds per complex. VD-MM/GBSA analysis reported favorable binding energies (- 295 to - 370 kcal/mol), while NMA confirmed appropriate dynamic flexibility for biological activity. Immune simulations predicted robust humoral and Th1-biased cellular responses with sustained IgG/IgM antibody production and maintained immune homeostasis. In silico cloning into pET-28a( +) showed optimal codon adaptation (CAI: 0.97) and GC content (53.31%), providing a pathway toward experimental validation of the first Blastocystis vaccine.</p><p><strong>Graphical abstract: </strong></p>","PeriodicalId":94038,"journal":{"name":"In silico pharmacology","volume":"14 2","pages":"187"},"PeriodicalIF":0.0,"publicationDate":"2026-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13356106/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148431712","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrated in silico pharmacology of <i>Pleurotus ostreatus</i>-derived bioactive compounds targeting EGFR using network pharmacology and molecular.","authors":"Supriya Maurya, Saba Ehsan, Anupriya Chaudhary, Shivanand Yadav, Mohan P Singh","doi":"10.1007/s40203-026-00690-9","DOIUrl":"10.1007/s40203-026-00690-9","url":null,"abstract":"<p><p>Cancer remains a major global health challenge, demanding the development of novel and mechanism-based therapeutic strategies. In the present study, an integrated computational approach involving network pharmacology, molecular docking, ADMET profiling, and molecular dynamics simulations was employed to investigate the anticancer potential of bioactive compounds derived from the mushroom <i>Pleurotus ostreatus</i>. Nine compounds with favourable predicted pharmacokinetic and toxicological properties were identified, yielding 138 potential cancer-related targets. Protein-protein interactions (PPIs) network analysis revealed 15 key hub genes, including CASP3, EGFR, ESR1, HSP90AA1, PPARG, MDM2, PARP1, SRC, PIK3CA, RELA, JAK2, PTGS2, GSK3B, PIK3R1, and TLR4, which are associated with several cancer types such as breast, colorectal, liver, and lung cancers. Functional enrichment analysis indicated the involvement of these targets in multiple cancer-related signaling pathways. Among these hub genes, EGFR emerged as a central therapeutic target due to its high network connectivity and involvement in multiple cancer-associated signaling pathways related to proliferation, survival, metastasis, and therapeutic resistance. Its prominent position within the interaction network further supports its potential as a key target for anticancer intervention. Molecular docking analysis demonstrated that lovastatin showed a strong predicted binding affinity toward EGFR, suggesting possible inhibitory potential. Molecular dynamics simulations further supported the stability of the lovastatin-EGFR complex. In addition, ADMET analysis indicated favourable drug-likeness and safety-related properties for the selected compounds. Overall, this study provides a systems-level computational investigation of <i>Pleurotus ostreatus</i>-derived compounds and their potential interactions with cancer-associated targets. However, these findings are based on computational predictions and require further experimental validation to confirm their biological and therapeutic relevance.</p><p><strong>Graphical abstract: </strong></p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1007/s40203-026-00690-9.</p>","PeriodicalId":94038,"journal":{"name":"In silico pharmacology","volume":"14 2","pages":"188"},"PeriodicalIF":0.0,"publicationDate":"2026-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13356229/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148431695","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Generative AI in antibody engineering: emerging concepts and translational bottlenecks in lung cancer.","authors":"Xiaohong An, Fangfang Li, Chao Xia, Yanqi Li, Haonan Li, Fei Xie","doi":"10.1007/s40203-026-00701-9","DOIUrl":"10.1007/s40203-026-00701-9","url":null,"abstract":"<p><p>The discovery of biotherapeutics is increasingly being driven by generative artificial intelligence (generative AI), marking a paradigm shift from random combinatorial screening to structure-based computational design. Within the field of non-small cell lung cancer (NSCLC), therapeutic development is persistently challenged by biophysical barriers, particularly those associated with neoantigens derived from intracellular oncogenic proteins (e.g., KRAS G12C), conformationally dynamic drug-resistant variants (e.g., EGFR), and structurally complex transmembrane receptors (e.g., CXCR4). Potential pathways for programmable epitope targeting are now being offered by emerging models based on diffusion and multimodal architectures (such as RFdiffusion and Chroma). In this narrative review, the core mechanisms and recent advancements of generative AI in antibody scaffold generation, sequence-structure co-evolution, and the early-stage screening of multi-parameter developability (e.g., solubility, viscosity, and immunogenicity) are evaluated. The utilization of computational methods to address challenging targets is analyzed, and the significant translational gap remaining between algorithmic confidence and clinically relevant biological fidelity is explored. Structural hallucinations, the absence of glycosylation and membrane lipid environment characterizations in training datasets, and binding-function discordance are identified as the primary current technical barriers. Ultimately, the translation of generative AI into clinical oncology will depend on the deep integration of \"lab-in-the-loop\" platforms, a paradigm where computational physical priors are continuously calibrated by high-throughput experimental data, progressively bridging the gap between in silico design and in vivo efficacy.</p>","PeriodicalId":94038,"journal":{"name":"In silico pharmacology","volume":"14 2","pages":"189"},"PeriodicalIF":0.0,"publicationDate":"2026-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13356224/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148431680","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analgesic activity of <i>Costus igneus</i> and identification of candidate bioactive constituents.","authors":"Palash Chandra Roy, Annesha Majumder, Uzzal Chondra","doi":"10.1007/s40203-026-00694-5","DOIUrl":"10.1007/s40203-026-00694-5","url":null,"abstract":"<p><strong>Abstract: </strong>This study investigated the analgesic activity of <i>Costus igneus</i> and sought to identify candidate phytochemical constituents associated with the observed biological activity through combined computational and experimental evaluation. Chemical profiling identified 160 putative constituents from the 70% methanolic leaf extract, from which eighteen compounds were prioritized following pharmacokinetic and toxicity screening. Comparative molecular interaction analysis highlighted two compounds, 5,8-dimethyl-1,4,6,7-tetrahydronaphthalene-1 (CI11) and R-limonene (CI14), for further characterization. Among the prioritized candidates, CI11 showed comparatively consistent interaction patterns across pain-related targets. Docking scores reached - 6.3 kcal mol^-1 against cyclooxygenase-1, - 6.9 kcal mol^-1 against cyclooxygenase-2, and - 7.5 kcal mol^-1 against the µ-opioid receptor, values approaching those of the corresponding reference compounds within each target system. Interaction analysis suggested contributions from both hydrogen bonding and hydrophobic stabilization, including contacts with residues CYS36 and ASN34 in cyclooxygenase-1, GLN396, ASP393, and THR394 in cyclooxygenase-2, and TYR148 within the µ-opioid receptor model. R-limonene displayed a more hydrophobic interaction profile and generally lower binding performance. DFT predicted spectroscopic and electronic characterization of CI11 and CI14 was performed after docking-based prioritization to examine structural features associated with interaction behavior. In vivo evaluation using the acetic acid-induced writhing model demonstrated significant analgesic activity of the extract, producing 48.8% inhibition at 300 mg kg^-1 (<i>p</i> < 0.001). Viewed in context, the findings identify CI11 as a candidate bioactive constituent and suggest that the analgesic activity of <i>Costus igneus</i> may involve multiple nociception-related pathways, although compound-specific and mechanistic validation remains necessary.</p><p><strong>Graphical abstract: </strong></p>","PeriodicalId":94038,"journal":{"name":"In silico pharmacology","volume":"14 2","pages":"185"},"PeriodicalIF":0.0,"publicationDate":"2026-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13337964/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148407564","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}