Journal of Computer-Aided Molecular Design最新文献

{"title":"Computer-aided molecular and biological-immune modeling of illicium verum bioactive compounds employing the Egyptian Nile snail Biomphalaria alexandrina as a paradigm.","authors":"Alya Mashaal, Basma M Abou El-Nour, Fatma M Ismail, Eman A Elewa, Eman A Elnoby, Eman B Ebada, Ayaat G Mohammed, Manar F El-Sahmawy, Mariam M Mansour, Nermeen N Khames, Hend M Ghorab, Safaa A Osman, Alshimaa A Elsaid, Maryam M Abd-Alaziz, Asmaa S Zayed, Asmaa A Abo Elqasem","doi":"10.1007/s10822-025-00607-2","DOIUrl":"10.1007/s10822-025-00607-2","url":null,"abstract":"<p><p>In pursuit of sustainable biocontrol strategies, this study explores Illicium verum (star anise) as a dual-action anti-inflammatory/oxidative and molluscicidal agent using Biomphalaria alexandrina, the intermediate host of Schistosoma mansoni, as an eco-relevant in vivo model. Two experimental snail groups were employed: a control group and a treatment group exposed to a sublethal concentration of I. verum extract (LC₁₀ = 315 ppm). Through a combined pipeline of phytochemical profiling, computational simulations, and in vivo assays, we identified flavonoids and phenylpropanoids with potent bioactivity. Molecular docking and ADMET screening highlighted kaempferol, quercetin, and rutin as top ligands, which bind effectively to key snail proteins such as cytochrome c oxidase and actin. In vivo analyses confirmed immunomodulatory effects, and these findings were validated through oxidative/inflammatory biomarker assays, which revealed altered cytokine levels (IFN-γ, IL-2 and IL-6), tissue remodeling, and reduced oxidative stress. Histopathological and immunohistochemical evaluations revealed significant tissue alterations in the digestive gland and head-foot regions of treated snails. Gene and protein interaction networks supported these findings by linking compound action to immune and oxidative regulatory pathways. This integrative study demonstrated that Illicium verum contains bioactive compounds capable of modulating oxidative stress, immune responses, and tissue integrity in B. alexandrina as an animal model. Integrating phytochemical analysis with in silico and molecular simulations offers a powerful approach for understanding and optimizing bioactive compounds. While phytochemical profiling identifies key constituents such as flavonoids and phenylpropanoids, computational tools predict their binding to biological targets, pharmacokinetics, and safety. This combination not only streamlines the discovery of effective and low-toxicity compounds but also clarifies their mechanisms of action at the molecular level, enhancing both the precision and efficiency of experimental validation. These results position star anise as a promising, eco-friendly candidate for the development of novel molluscicidal and anti-inflammatory agents supporting sustainable disease control strategies.</p>","PeriodicalId":621,"journal":{"name":"Journal of Computer-Aided Molecular Design","volume":"39 1","pages":"33"},"PeriodicalIF":3.0,"publicationDate":"2025-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12181124/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144336186","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":"Thermodynamic free energy map for the non-oxidative glycolysis pathways.","authors":"Adittya Pal","doi":"10.1007/s10822-025-00604-5","DOIUrl":"10.1007/s10822-025-00604-5","url":null,"abstract":"<p><p>Designing reaction pathways that maximize the production of a target compound in a given metabolic network is a fundamental problem in systems biology. In this study, we systematically explore the non-oxidative glycolysis metabolic network, guided by the principle that reactions with negative Gibbs free energy differences are thermodynamically favored. We enumerate alternative pathways that implement the net non-oxidative glycolysis reaction, categorized by their length. Our analysis reveals several alternative thermodynamically favorable pathways beyond the experimentally reported ones. Additionally, we identify molecules within the network, such as 3-hydroxypropionic acid, that may have significant potential for further investigation.</p>","PeriodicalId":621,"journal":{"name":"Journal of Computer-Aided Molecular Design","volume":"39 1","pages":"32"},"PeriodicalIF":3.0,"publicationDate":"2025-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12170709/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144300909","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":"DTBA-net: Drug-Target Binding Affinity prediction using feature selection in hybrid CNN model.","authors":"Priya Mishra, Swati Vipsita","doi":"10.1007/s10822-025-00605-4","DOIUrl":"https://doi.org/10.1007/s10822-025-00605-4","url":null,"abstract":"<p><p>In drug discovery, virtual screening and repositioning rely on accurate Drug-Target Binding Affinity (DTBA) prediction to develop effective therapies. However, DTBA prediction remains challenging due to limited annotated datasets, high-dimensional biochemical data, and heterogeneous data sources, including chemical structures, biological sequences, and molecular interactions. These complexities hinder the development of unified deep-learning frameworks. To address these challenges, we propose DTBA-Net, a novel hybrid neural network model that enhances DTBA prediction accuracy and efficiency. DTBA-Net integrates optimal feature selection within a CNN architecture to predict DTBA. Protein sequences and compound structures are processed through a hybrid CNN that includes convolutional layers, a flattened layer, a Modified JAYA Algorithm for optimal feature selection, and dense blocks. The Modified JAYA algorithm selects relevant features, reduces computational overhead, and improves predictive performance. DTBA-Net was evaluated on two benchmark datasets, KIBA and DAVIS. On the DAVIS dataset, DTBA-Net attained an R-squared value of 0.95 and a Mean Absolute Error (MAE) of 0.17. Further validation using the drug Nirmatrelvir resulted in an R-squared value of 0.96, showcasing the model's robustness and scalability. Integrating a hybrid neural network with an optimized feature selection process accelerates model training and enhances prediction accuracy. DTBA-Net demonstrates promising potential for scalable, efficient, and accurate DTBA prediction, facilitating faster and more reliable drug discovery.</p>","PeriodicalId":621,"journal":{"name":"Journal of Computer-Aided Molecular Design","volume":"39 1","pages":"31"},"PeriodicalIF":3.0,"publicationDate":"2025-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144300908","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":"Multitarget neuroprotective effects of β-sitosterol in diabetes-associated neurodegeneration: a coupled experimental/computational study.","authors":"Karishma Sen, Anita Sakarwal, Kamlesh Kumar, Heera Ram, Garima Singh, Vikas Kumar, Anil Panwar, Mukesh Kumar Yadav, Jing-Hua Wang","doi":"10.1007/s10822-025-00609-0","DOIUrl":"https://doi.org/10.1007/s10822-025-00609-0","url":null,"abstract":"<p><p>Diabetes often leads to neurodegenerative complications that complicate treatment. Exploring dietary components with neuroprotective properties could offer new therapeutic avenues. This study aimed to evaluate the neuroprotective potential of β-sitosterol against diabetes-associated neurodegenerative complications using a combined in silico and in vivo approach. β-Sitosterol exhibited significant neuroprotective effects in a diabetic neuropathy model. Compared to sitagliptin, β-sitosterol demonstrated stronger binding affinities to DPP4, acetylcholinesterase, and butyrylcholinesterase, along with more stable molecular dynamics profiles. In vivo, β-sitosterol treatment markedly improved glucose tolerance, insulin sensitivity, lipid profiles, and antioxidant capacity. Histological analysis revealed reduced neurodegenerative changes and enhanced neuronal integrity in the cortex and hippocampus. These findings suggest β-sitosterol as a promising therapeutic agent for managing diabetic neurodegeneration, warranting further research and potential clinical application.</p>","PeriodicalId":621,"journal":{"name":"Journal of Computer-Aided Molecular Design","volume":"39 1","pages":"30"},"PeriodicalIF":3.0,"publicationDate":"2025-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144293077","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":"Structure-guided discovery of microtubule affinity-regulating kinase 4 inhibitory potential of Harmane: towards therapeutic targeting of Alzheimer's disease.","authors":"Afzal Hussain, Md Nayab Sulaimani, Shumayila Khan, Saleha Anwar, Mohammed F Hawwal, Mohamed F Alajmi, Dharmendra Kumar Yadav, Md Imtaiyaz Hassan","doi":"10.1007/s10822-025-00606-3","DOIUrl":"https://doi.org/10.1007/s10822-025-00606-3","url":null,"abstract":"<p><p>Microtubule affinity-regulating kinase (MARK), particularly MARK4, are involved in the pathological phosphorylation of tau, contributing to neurodegenerative diseases and conditions such as cancer, inflammation, and atherosclerosis. The β-carboline family, specifically Harmane, exhibits broad biological activity, including neuroprotective effects. We investigated the inhibitory potential of Harmane against MARK4 using both computational and experimental approaches. The interaction between Harmane and MARK4 was studied using a combination of computational and experimental approaches. Molecular docking was carried out to understand the binding of Harmane to the binding pocket of MARK4, focusing on key interactions. Molecular dynamics simulations further assessed the stability of the MARK4-Harmane complex. Enzyme inhibition assays were conducted to assess Harmane's inhibitory potential on kinase, and a fluorescence quenching assay was complemented to validate the binding affinity of Harmane with MARK4. Molecular docking revealed that Harmane binds to the active site of MARK4, a finding supported by molecular dynamics simulations, demonstrating increased stability of the MARK4-Harmane complex. Structural analysis further highlighted the specificity of this interaction. Enzyme inhibition assays estimated Harmane's IC₅₀ (half-maximal inhibitory concentration) value as 2.72 µM against MARK4, while fluorescence spectroscopy measured a binding constant (Ka) of 0.1 × 10⁵ M^- 1. These results strengthen the idea that Harmane can be a potent MARK4 inhibitor, offering therapeutic promise for neurodegenerative diseases and cancer.</p>","PeriodicalId":621,"journal":{"name":"Journal of Computer-Aided Molecular Design","volume":"39 1","pages":"29"},"PeriodicalIF":3.0,"publicationDate":"2025-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144273901","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":"A systematic insight into glycycoumarin as potential IL-8/topo I inhibitor from natural products collected in Taibai mountain based on the combination of in silico and bioassay.","authors":"Na-Na Tan, Jia Lu, Zhuang-Hong Li, Shi-Ping Zhang, Huan Wang, Jing-Bo Hu, Tian Wang, Jian Xiao, Xiao-Ling Wang, Le Wang","doi":"10.1007/s10822-025-00611-6","DOIUrl":"https://doi.org/10.1007/s10822-025-00611-6","url":null,"abstract":"<p><p>This study aimed to screen IL-8/topo I inhibitors from natural products collected in Taibai mountain and explore the underlying mechanisms. A natural product library of Taibai mountain (NPTM) was first constructed containing 186 compounds. Then, 15 and 6 potential inhibitors were screened using pharmacophore modeling for IL-8 and topo I, respectively. Molecular docking indicated that glycycoumarin was IL-8/topo I inhibitor. A 200 ns molecular dynamics simulation reflected high binding stability and favorable hydrogen bond interaction within glycycoumarin-IL-8/topo I complexes. MM/GBSA calculation showed that the binding free energy was - 12.81 kcal/mol and - 31.20 kcal/mol, and Pro 32 and DT 10 contributed most to glycycoumarin and IL-8, topo I, respectively. SMD simulation demonstrated a stable binding under physiological conditions with energy demands to dissociate from IL-8/topo I. Glycycoumarin decreased IL-8 production in the inflammatory cells, and exhibited obvious topo I inhibition, as well as strong cytotoxicity to three cancer cells. A PPI network revealed that glycycoumarin might work through proteoglycans in cancer (hsa05205) and IL-17 signaling pathway (hsa04657). These results improved current understanding of natural IL-8/topo I inhibitors from Taibai mountain. The combination of in silico and bioassay could provide a new strategy for exploring natural lead compounds against inflammation and cancer.</p>","PeriodicalId":621,"journal":{"name":"Journal of Computer-Aided Molecular Design","volume":"39 1","pages":"28"},"PeriodicalIF":3.0,"publicationDate":"2025-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144257060","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":"Evaluating computational and experimental approaches in early-stage Alzheimer's drug discovery: a systematic review.","authors":"Mahir Azmal, Jibon Kumar Paul, Md Naimul Haque Shohan, A N M Shah Newaz Been Haque, Mohua Mrinmoy, Omar Faruk Talukder, Ajit Ghosh","doi":"10.1007/s10822-025-00610-7","DOIUrl":"https://doi.org/10.1007/s10822-025-00610-7","url":null,"abstract":"<p><p>Alzheimer's disease (AD) represents a significant global health challenge due to its complex pathophysiology and limited therapeutic options. Traditional drug discovery methods have had limited success, highlighting the need for innovative strategies. This systematic review evaluates the role of molecular docking, virtual screening, and molecular dynamics simulations in the early stages of AD drug discovery. This study reviewed 100 studies published between 2000 and 2024, focusing on computational approaches to identify and optimize drug candidates targeting key AD-related proteins, including acetylcholinesterase (AChE), β-secretase (BACE1), and tau. Both natural and synthetic compounds were examined, emphasizing studies integrating in silico methods with in vitro and in vivo validations. AChE was the most frequently targeted protein (23 studies), followed by BACE1 and multi-target approaches. The compounds investigated varied, with 35 studies focusing on natural products (e.g., quercetin, huperzine A) and 54 on synthetic analogs (e.g., tacrine derivatives). Integrating computational and experimental methods enhanced the validation process, providing comprehensive insights into the pharmacodynamics and pharmacokinetics of potential therapeutics. Computational approaches significantly expedite the identification and optimization of AD drug candidates by enabling the rapid screening of extensive compound libraries. These methods, when combined with experimental validations, offer deeper molecular-level insights into drug interactions and mechanisms. However, challenges such as predictive accuracy and data quality remain, necessitating further advancements in computational models and data integration to improve the predictability and effectiveness of AD therapeutics.</p>","PeriodicalId":621,"journal":{"name":"Journal of Computer-Aided Molecular Design","volume":"39 1","pages":"27"},"PeriodicalIF":3.0,"publicationDate":"2025-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144232903","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":"Solvation and formal charge corrections to the Piecewise-Linear Potential.","authors":"Daniel K Gehlhaar, Daniel J Mermelstein","doi":"10.1007/s10822-025-00608-1","DOIUrl":"https://doi.org/10.1007/s10822-025-00608-1","url":null,"abstract":"<p><p>The Piecewise-Linear Potential (PLP) has remained a key scoring function for molecular recognition, especially protein-ligand docking. However, the absence of a solvation model in PLP, combined with a lack of treatment for formal charged atoms, limits the usefulness of PLP for modern docking programs. We describe an extension to the PLP, named the Solvation-Corrected PLP (SCPLP), which adds robust solvation corrections to the PLP without adding the computational burden common with most existing solvation models. The SCPLP includes both protein and ligand solvation effects, as well as support for formal charged groups on both protein and ligand, specialized handling of crystallographic water molecules, and scaling of protein-ligand electrostatic interactions based on their degree of solvent exposure.</p>","PeriodicalId":621,"journal":{"name":"Journal of Computer-Aided Molecular Design","volume":"39 1","pages":"26"},"PeriodicalIF":3.0,"publicationDate":"2025-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144223969","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":"Multi-Omics Analysis of the virulence factors and designing of next-generation multi-epitopes Vaccines against Rickettsia prowazekii: a computer-aided vaccine designing approach","authors":"Fahad M. Alshabrmi","doi":"10.1007/s10822-025-00603-6","DOIUrl":"10.1007/s10822-025-00603-6","url":null,"abstract":"<div><p><i>Rickettsia</i> is a genus of bacteria that are obligate intracellular parasites and are responsible for the febrile diseases known collectively as Rickettsioses. The emergence of antibiotic resistance is an escalating concern and thus developing a vaccine against <i>Rickettsia</i> is of paramount importance due to the significant public health threat posed by these bacteria. Thus, we employed structural vaccinology guided by machine learning algorithms to explore the virulence landscape of <i>Rickettsia prowazekii</i> to design a multi-epitopes-based vaccine (MEVC) that is immunogenic and safe. From a pool of virulence factors, we shortlisted five targets including sca0, sca1, sca4, sca5 and tlyA that were classified as non-allergenic as well as antigenic. The immune epitopes mapping results shortlisted five CTL epitopes, five HTL (IFN+) epitopes and five B cell epitopes as the best choice to design a vaccine construct of 475 amino acids. Various parameters were used to validate the designed MEVC which involved prediction of physiochemical properties, modeling and validation of the 3D structure, interaction with the immune receptors such as TLR2 (Toll-like receptor) and TLR4. Moreover, all-atoms simulation and binding free energy (BFE) results revealed a stable and favorable dynamic properties determined by these complexes. Jcat revealed that the improved sequence exhibits a GC content of 48.14% and a CAI (Codon Adaptation Index) value of 1.0. We used a multi-dose criterion at different time intervals i.e., 1st, 84th and 170th day to understand the immune potential of our constructed vaccine. The results provide a comprehensive overview of immune factors that ensure effective antigen memory cells generation after each injection, as predicted by the in silico pipeline. However, limitations in current algorithms particularly their inability to fully account for HLA polymorphism and the lack of experimental and clinical validation remain major shortcomings of the study. These issues should be addressed in future research to support the development of a robust immune response against <i>Rickettsia</i> infections.</p></div>","PeriodicalId":621,"journal":{"name":"Journal of Computer-Aided Molecular Design","volume":"39 1","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144135314","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":"Targeting multiple pathways with virtual screening to identify the multi-target agent for Alzheimer’s disease treatment","authors":"Pitchayakarn Takomthong,&nbsp;Pornthip Waiwut,&nbsp;Chantana Boonyarat","doi":"10.1007/s10822-025-00602-7","DOIUrl":"10.1007/s10822-025-00602-7","url":null,"abstract":"<div><p>Alzheimer’s disease (AD) is a chronic neurodegenerative disorder characterized by progressive memory loss, posing a significant risk, particularly within aging populations. Effective treatments to prevent or cure AD have remained elusive with current treatments only able to slow disease progression. Moreover, challenges in drug development for AD therapies are a complex pathology. A multi-target agent gained considerable interest over the single therapy in complex diseases, providing possible insights into therapeutic development by simultaneously targeting multiple pathological mechanisms. Virtual screening (VS) is a potent computational tool for identifying potential drug candidates from vast chemical databases, with subsequent molecular docking providing detailed insights into ligand-protein interactions. The ZINC database, housing millions of chemical compounds, serves as a valuable resource for screenings. Here, we conducted VS of compounds sourced from the ZINC database to identify potential multi-target AD agents. Through the VS analysis and subsequent in-vitro evaluations, our investigation identified one compound, ZINC006067856 (VS3), as a highly promising hit. This compound exhibited multifaceted actions against key AD pathological features, including cholinesterase inhibition, modulation of amyloid beta (Aβ) aggregation, and promotion of Aβ destabilization. Additionally, VS3 demonstrated neuroprotective effects against hydrogen peroxide-induced cell damage, further highlighting its potential as a comprehensive multi-targeted therapeutic agent for AD. Therefore, our findings suggested that VS3 held promise as a candidate for further preclinical and clinical investigations in the treatment of AD. Further elucidation of its mechanisms of action and comprehensive preclinical evaluations are required to assess its safety, efficacy, and therapeutic potential in improving AD clinical outcomes.</p></div>","PeriodicalId":621,"journal":{"name":"Journal of Computer-Aided Molecular Design","volume":"39 1","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144084901","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}