Molecular Diversity最新文献

{"title":"Molecular docking-based design of novel tricyclic tetrahydropyridothienopyrimidinone derivatives as AChE/MAO-B dual inhibitors.","authors":"Juan Zhang, Yue Li, Jia-Dong Shao, Guo Wei, Nai-Yu Zhang, Kong-Kai Zhu, Kai-Ming Wang, Cheng-Shi Jiang, Jia-Hong Wang","doi":"10.1007/s11030-025-11354-9","DOIUrl":"https://doi.org/10.1007/s11030-025-11354-9","url":null,"abstract":"<p><p>The present study describes the design, synthesis, and evaluation of novel tricyclic tetrahydropyridothienopyrimidinone (THPTP) derivatives as dual AChE/MAO-B inhibitors. Building on our previous hit A03, an additional benzyl substituent was added to improve interactions with the peripheral anionic site of AChE and enhance MAO-B binding. The derivatives showed increased inhibitory activities, with compound A03-12 exhibiting significant potency (huAChE: IC₅₀ = 0.14 µM, huMAO-B: IC₅₀ = 0.52 µM). Kinetic studies and molecular simulations revealed distinct binding interactions, supporting its mixed-type AChE inhibition and competitive MAO-B inhibition. Compound A03-12 also demonstrated high metabolic stability, better pharmacokinetic parameters, favorable blood-brain barrier permeability, and low cytotoxicity (CC₅₀ > 100 µM). These results offer a promising chemical template, especially compound A03-12, as a potential lead for designing new anti-AD drugs.</p>","PeriodicalId":708,"journal":{"name":"Molecular Diversity","volume":" ","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145090989","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advancements in antiviral activity of aza-heterocyclic compounds: a review.","authors":"Issam Ameziane El Hassani, Khalid Karrouchi, M'hammed Ansar","doi":"10.1007/s11030-025-11355-8","DOIUrl":"https://doi.org/10.1007/s11030-025-11355-8","url":null,"abstract":"<p><p>Aza-heterocycles serve as privileged scaffolds in antiviral drug discovery due to their versatile chemical tunability and broad-spectrum biological activities. Strategic structural modifications of these pharmacophores have emerged as a powerful approach to optimize therapeutic potential, enabling the development of novel bioactive agents. These nitrogen-containing heterocycles demonstrate remarkable pharmacological diversity, exhibiting efficacy as anti-inflammatory, antimicrobial, antidiabetic, and anticancer compounds, along with enzyme inhibitory and pesticidal properties. This review systematically evaluates 5- and 6-membered aza-heterocyclic systems with established antiviral profiles, highlighting structure-activity relationships. The synthesized insights will advance research in synthetic organic chemistry, medicinal chemistry, and pharmacological development of next-generation therapeutics.</p>","PeriodicalId":708,"journal":{"name":"Molecular Diversity","volume":" ","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145084765","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Discovery of novel Plasmodium falciparum PfDHFR-TS inhibitors from ConMedNP natural compounds: a multi-computational approach.","authors":"Victorien Hermann Haiwang Djefoulna, Maxime Atiya Atiya, Jean Jules Fifen, Jeanet Conradie","doi":"10.1007/s11030-025-11356-7","DOIUrl":"https://doi.org/10.1007/s11030-025-11356-7","url":null,"abstract":"<p><p>The rise of drug-resistant Plasmodium falciparum necessitates novel antimalarial therapies. Leveraging the ConMedNP database, which includes over 3119 natural compounds from Central and West African medicinal plants, this study targets Plasmodium falciparum dihydrofolate reductase-thymidylate synthase (PfDHFR-TS), a vital enzyme for parasite survival. Molecular docking of 2754 compounds revealed a mean binding affinity of <math><mo>-</mo></math>  8.8032 kcal/mol (SD = 1.4 kcal/mol, median = <math><mo>-</mo></math>  8.9 kcal/mol), with 75% outperforming artemether's reference affinity ( <math><mo>-</mo></math>  8.0 kcal/mol). A Random Forest-based RaMQSAR model, trained on the docking data, achieved a test <math><msup><mi>R</mi> <mn>2</mn></msup> </math> of 0.8321 (RMSE: 0.5294 kcal/mol) and reliable cross-validation (mean <math><msup><mi>R</mi> <mn>2</mn></msup> </math> = 0.8461, SD = 0.0460). Validation against 19 known antimalarials showed predicted affinities from <math><mo>-</mo></math>  7.0 to <math><mo>-</mo></math>  10.5 kcal/mol, consistent with docking results. Top performers included RDC0118 ( <math><mo>-</mo></math>  13.5 kcal/mol), RDC0119 ( <math><mo>-</mo></math>  13.4 kcal/mol), and CA0001 ( <math><mo>-</mo></math>  13.0 kcal/mol), all surpassing artemether. ADMET profiling indicated CA0001 and artemether as safer candidates (non-hepatotoxic, low environmental impact), while RDC0118 and RDC0119 exhibited potential mutagenicity and hepatotoxicity risks. MD simulations confirmed structural stability for both, with CA0001 showing compaction and transient H-bonds (0-3). DFT analysis highlighted CA0001's reactivity as a soft electrophile, contrasting with artemether's higher reactivity. This comprehensive approach integrating docking, QSAR, DFT, and MD positions CA0001 as a promising PfDHFR-TS inhibitor alongside artemether, with ConMedNP and predictive models guiding future experimental validation.</p>","PeriodicalId":708,"journal":{"name":"Molecular Diversity","volume":" ","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145074020","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Decoding pH-dependent structural dynamics of CHIKV nsP2 protease: insights from computational antiviral targeting.","authors":"Rubha Shri Gurunathan, Abhirami Rajaram, Selvaraj Chandrabose, Sanjeev Kumar Singh","doi":"10.1007/s11030-025-11343-y","DOIUrl":"https://doi.org/10.1007/s11030-025-11343-y","url":null,"abstract":"<p><p>Chikungunya virus (CHIKV) is a vector-borne disease transmitted primarily through mosquitoes and causes fever, and its pathogenicity is closely linked to the function of non-structural protein 2 (nsP2), which plays a pivotal role in viral replication and host immune modulation. The enzymatic efficiency and structural stability of viral proteases are intensely influenced by environmental pH, which can regulate the active site accessibility and inhibitor binding efficiency. This non-structural protein 2 (nsP2) encompasses an N-terminal RNA helicase and C-terminal cysteine protease linked by the flexible regions. Hence, this study investigates the influence of varying pH conditions on structural flexibility of apo form and holo forms of CHIKV nsP2 protease leveraging of extensive molecular dynamic (MD) simulation and molecular docking. Post-MD superimposition revealed that the active site shifted from Site 2 to Site 1, indicating a conformational reorganization of the binding pocket. This study also evaluated its influence on the interactions with a cysteine protease inhibitor, E-64 and Leupeptin of CHIKV nsP2 protease. Simulation conducted under various pH conditions revealed a notable shift, particularly in the catalytic dyad residues Cys 1013 and His 1083. RMSD, RMSF, radius of gyration, and number of hydrogen bond analyses indicated that both inhibitors exhibited variable binding stabilities, with pronounced fluctuation in loop and β-strand region. Notably, at pH 7 and 8, the β2 strand undergoes a conversion into a loop which could potentially influence the substrate recognition and catalytic activity. Thus, this in silico findings provides critical insights into the dynamic behavior of CHIKV nsP2 protease under various pH and suggests strategies for rational designing of pH-resilient antiviral inhibitors that maintain the efficiency under various physiological conditions.</p>","PeriodicalId":708,"journal":{"name":"Molecular Diversity","volume":" ","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145068865","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Decoding the gut microbiota metabolite-matrix metalloproteinase-3 axis in breast cancer: a multi-omics and network pharmacology study.","authors":"Tangyu Yuan, Jiayin Xing, Pengtao Liu","doi":"10.1007/s11030-025-11351-y","DOIUrl":"https://doi.org/10.1007/s11030-025-11351-y","url":null,"abstract":"<p><p>Breast cancer is a malignant tumor originating from the breast epithelium, and emerging evidence suggests that the gut microbiota influences its development, progression, and treatment, although its role remains underexplored. In this study, we employed an integrative multi-omics framework that combined network pharmacology, machine learning, SHapley Additive exPlanations (SHAP), and single-cell RNA sequencing to systematically investigate key interactions between microbial metabolites and their targets. Core regulators were further validated using Mendelian randomization (MR), while molecular docking was applied to evaluate the binding affinity of candidate metabolites. Matrix metalloproteinase-3 (MMP3) emerged as a central molecule involved in multiple cancer-related signaling pathways, including PI3K-AKT, MAPK, and HIF-1, with promising druggable potential. Eight non-toxic gut microbial metabolites-such as indole-3-propionic acid, glycocholic acid, and 4-hydroxyphenylpyruvate-demonstrated strong binding affinity to MMP3 and favorable pharmacokinetic properties, highlighting a previously unappreciated microbiota-MMP3 axis as a promising avenue for therapeutic intervention in breast cancer. These findings provide a basis for subsequent in vitro and in vivo validation and underscore the translational potential of the identified microbial metabolites, thereby supporting the development of microbiome-derived therapeutic strategies for breast cancer.</p>","PeriodicalId":708,"journal":{"name":"Molecular Diversity","volume":" ","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145058224","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ACP-EPC: an interpretable deep learning framework for anticancer peptide prediction utilizing pre-trained protein language model and multi-view feature extracting strategy.","authors":"Jingwei Lv, Kexin Li, Yike Wang, Junlin Xu, Yajie Meng, Feifei Cui, Leyi Wei, Qingchen Zhang, Zilong Zhang","doi":"10.1007/s11030-025-11352-x","DOIUrl":"https://doi.org/10.1007/s11030-025-11352-x","url":null,"abstract":"<p><p>Cancer remains a major global health challenge, as conventional chemotherapy often causes extensive damage to healthy cells and leads to severe side effects. Anticancer peptides (ACPs) have emerged as a promising therapeutic alternative, capable of selectively targeting and eliminating cancer cells while improving patient quality of life and treatment outcomes. Nevertheless, identifying ACPs through traditional biological experiments is both labor-intensive and time-consuming. To address this limitation, we developed ACP-EPC, a deep learning framework which predicts ACPs directly from protein sequences. ACP-EPC integrates contextual representations from Evolutionary Scale Modeling 2 (ESM-2) with handcrafted physicochemical descriptors and employs a Cross-Attention mechanism for multimodal feature fusion. The model was rigorously evaluated using tenfold cross-validation and two test sets, ACP135 and ACP99, achieving accuracy of 0.935 and 0.984, respectively. These results substantially outperform existing models, underscoring the advantages of combining diverse feature representations. To promote accessibility, we have also deployed ACP-EPC as a publicly available web server at http://www.bioai-lab.com/ACP-EPC .</p>","PeriodicalId":708,"journal":{"name":"Molecular Diversity","volume":" ","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145058231","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Structural insights into TLR4 activation by SARS-CoV-2 spike protein: implications for inflammatory response modulation.","authors":"Priya Prakasam, Thripthi Nagesh Shenoy, Abdul Ajees Abdul Salam, Syed Ibrahim Basheer Ahamed","doi":"10.1007/s11030-025-11347-8","DOIUrl":"10.1007/s11030-025-11347-8","url":null,"abstract":"<p><p>Toll-like receptor 4 (TLR4) in complex with myeloid differentiation factor 2 (MD2) plays a central role in innate immune sensing and inflammatory responses during viral infections. Emerging evidence suggests that viral glycoproteins, including the SARS-CoV-2 spike (S) protein, can aberrantly activate TLR4, contributing to cytokine storms; however, the molecular basis remains unclear. In this study, we investigated the recognition of the SARS-CoV-2 spike protein, in both its monomeric and trimeric forms, by the TLR4/MD2 receptor complex using a comprehensive in silico framework. Protein-protein docking, extended molecular dynamics simulations (500 ns), interaction profiling, principal component analysis, free energy landscape mapping, and binding-affinity calculations were employed. The S1 subunit, particularly the receptor-binding domain (RBD) and N-terminal domain (NTD), emerged as the principal interface for TLR4 and MD2-a novel finding. The spike monomer exhibited stronger and more stable interactions than the trimer, supported by a greater number of hydrogen bonds and salt bridges, lower binding energies, and distinct PCA/energy landscape features. Two N-linked glycosylation sites in the monomer were positioned proximal to the MD2 binding pocket, compared to one in the trimer, suggesting a possible role in modulating receptor activation. Several hotspot residues were also identified as potential therapeutic targets. Collectively, these findings support a model in which the SARS-CoV-2 spike protein engages TLR4/MD2 through domain-specific interactions that may modulate innate immune signalling.</p>","PeriodicalId":708,"journal":{"name":"Molecular Diversity","volume":" ","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145058237","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Synthesis of novel phthalide bearing thiazole, 1,3,4-oxadiazole, and oxime ether groups as potential antifungal agents.","authors":"Yong Li, Taotao Wu, Guobin Chen, Jian He, Yong Zhang, Qin Zhang, Pengfei Zhou, Wenzhang Chen, Lingling Fan","doi":"10.1007/s11030-025-11348-7","DOIUrl":"https://doi.org/10.1007/s11030-025-11348-7","url":null,"abstract":"<p><p>Twenty-eight novel phthalide derivatives incorporating thiazole, 1,3,4-oxadiazole, and oxime ether moieties were designed and synthesized using a pharmacophore hybridization strategy. Bioactivity assays demonstrated that compounds 1b, 1c, 4a, 4b and 4c exhibited moderate to excellent inhibitory activity against several specific fungi. Notably, compound 1b displayed superior antifungal efficacy against F. solani, F. oxysporum, B. dothidea, and V. mali compared to the commercial fungicides hymexazol and boscalid, with EC₅₀ values of 15.0 μg/mL, 10.0 μg/mL, 6.1 μg/mL, and 11.4 μg/mL, respectively. Additionally, compound 1b provided superior protective efficacy against B. dothidea-infected apples compared to boscalid. Preliminary mechanistic studies revealed that compound 1b could exert its antifungal activity by compromising the integrity of the hyphal cell membrane. This study highlights the potential of phthalide derivatives bearing dihalocarbonyl and oxime moieties as effective antifungal agents for controlling plant pathogenic fungi, warranting further investigation in the future.</p>","PeriodicalId":708,"journal":{"name":"Molecular Diversity","volume":" ","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145038880","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Quantum chemical optimization and residue-specific stabilization of CDK20 inhibitors in hepatocellular carcinoma.","authors":"Ahmed I Foudah, Mohammed H Alqarni, Tariq M Aljarba, Talha Jawaid, Osama A Alkhamees, Saud M Alsanad, Khalid I AlHussaini, Aftab Alam","doi":"10.1007/s11030-025-11339-8","DOIUrl":"https://doi.org/10.1007/s11030-025-11339-8","url":null,"abstract":"<p><p>Cyclin-dependent kinase 20 (CDK20), also known as cell cycle-related kinase (CCRK), plays a pivotal role in hepatocellular carcinoma (HCC) progression by regulating β-catenin signaling and promoting uncontrolled proliferation. Despite its emerging significance, selective small-molecule inhibitors of CDK20 remain unexplored. In this study, a known CDK20 inhibitor, ISM042-2-048, was employed as a reference to retrieve structurally similar compounds from the PubChem database using an 85% similarity threshold. Out of 6,235 candidates, the top three compounds (153295720, 145037521, and 163292314) were shortlisted through MTiOpenScreen-based virtual screening. Geometry optimizations using density functional theory (B3LYP/cc-pVDZ) refined each ligand's electronic properties before re-docking against the AlphaFold-derived CDK20 structure. 153295720 exhibited the highest binding affinity (- 11.8 kcal/mol), engaging critical active-site residues such as Met⁸⁴, Lys³³, Ala¹³¹, and Asp¹⁴⁵ through polar and hydrophobic interactions. Molecular dynamics simulations (500 ns) confirmed the complex's structural stability, with 153295720 showing the lowest RMSD and RMSF fluctuations and highly persistent hydrogen bonding. MM/GBSA analysis further supported its superiority, revealing the most favorable binding energy (- 69.09 ± 8.29 kcal/mol), dominated by van der Waals and electrostatic interactions. Free energy landscape analysis revealed a single dominant basin, and superimposition of MD-derived minima with the docked pose yielded an RMSD of 1.464 Å, supporting pose fidelity. Comparatively, the reference compound displayed greater conformational drift and reduced energetic convergence. This integrative computational approach establishes 153295720 as a structurally and dynamically superior inhibitor, capable of stabilizing key catalytic residues of CDK20. These findings provide a rational basis for the biochemical targeting of CDK20 in HCC and highlight residues essential for selective inhibition, paving the way for experimental validation and lead optimization.</p>","PeriodicalId":708,"journal":{"name":"Molecular Diversity","volume":" ","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145028792","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Oral bioavailability property prediction based on task similarity transfer learning.","authors":"Chen Zeng, Chengcheng Xu, Yingxu Liu, Yunya Jiang, Lidan Zheng, Yang Liu, Yanmin Zhang, Yadong Chen, Haichun Liu, Rui Gu","doi":"10.1007/s11030-025-11345-w","DOIUrl":"https://doi.org/10.1007/s11030-025-11345-w","url":null,"abstract":"<p><p>Drug absorption significantly influences pharmacokinetics. Accurately predicting human oral bioavailability (HOB) is essential for optimizing drug candidates and improving clinical success rates. The traditional method based on experiment is a common way to obtain HOB, but the experimental method is time-consuming and costly. Recently, using AI models to predict ADMET properties has become a new and effective method. However, this method has some data dependence problems. To address this issue, we combine physicochemical properties with graph-based deep learning methods to improve HOB prediction, providing an efficient and interpretable alternative to traditional experimental and computational approaches for ADMET property studies in data-scarce scenarios. We propose a similarity-guided transfer learning framework, Task Similarity-guided Transfer Learning based on Molecular Graphs (TS-GTL), which includes a deep learning model, PGnT (pKa Graph-based Knowledge-driven Transformer). PGnT incorporates common molecular descriptors as external knowledge to guide molecular graph representation, leveraging GNNs and Transformer encoders to enhance feature extraction. Additionally, we introduce MoTSE to quantify the similarity between physicochemical properties and HOB. Notably, training with data pretrained model on logD properties showed the best performance in transfer learning. TS-GTL also outperformed machine learning algorithms and deep learning predictive tools, underscoring the critical role of task similarity in transfer learning.</p>","PeriodicalId":708,"journal":{"name":"Molecular Diversity","volume":" ","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145028720","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}