Pub Date : 2026-01-15DOI: 10.1016/j.jmgm.2026.109287
Astrit Tola , Shan Aziz , Dannie Zhabilov , Duane Winkler , Mehmet Candas , Baris Coskunuzer
This study demonstrates the transformative potential of machine learning in drug discovery by integrating comparative protein and ligand analysis with novel topological machine learning methods. Our approach sifts through large chemical libraries to identify promising molecular structures for targeting specific proteins with high precision. While many machine learning models have proven effective on benchmark datasets, we apply these techniques to discover compounds targeting methylcitrate dehydratase (AcnD), the second enzyme in the bacterial propionate catabolism pathway. Propionate catabolism is essential in pathogenic bacteria for utilizing host derived lipids and amino acids. Inefficient removal of propionate can lead to toxic accumulation that threatens bacterial survival, making this pathway a potential antimicrobial target. We translate ligand molecular structures into topological vectors and use tailored topological models to prioritize compounds with characteristics consistent with blocking the AcnD active site. Molecular docking simulations indicate that prioritized compounds interact with key amino acid residues critical to AcnD function. Among these, 2-methylidenebutanedioic acid (itaconic acid, itaconate) ranks highly as a potential molecular scaffold for targeting AcnD. Using bacterial growth assays, we find that itaconate at 29.13 mM completely inhibits the growth of Pseudomonas aeruginosa and Acinetobacter baumannii in carbon rich liquid cultures. These findings reinforce itaconate’s potential as an antimicrobial metabolite and support the hypothesis that it can disrupt bacterial propionate catabolism, potentially by inhibiting AcnD and promoting the accumulation of toxic intermediates. Overall, our study underscores the value of integrating topology based ligand modeling with comparative sequence structure function analysis and docking to identify molecular scaffolds with favorable geometric fit, energy, and interaction profiles, guiding downstream optimization and experimental validation. Our code is available at (https://github.com/AstritTola/Molecular-Compounds-Targeting).
{"title":"Identification of molecular compounds targeting bacterial propionate metabolism with topological machine learning","authors":"Astrit Tola , Shan Aziz , Dannie Zhabilov , Duane Winkler , Mehmet Candas , Baris Coskunuzer","doi":"10.1016/j.jmgm.2026.109287","DOIUrl":"10.1016/j.jmgm.2026.109287","url":null,"abstract":"<div><div>This study demonstrates the transformative potential of machine learning in drug discovery by integrating comparative protein and ligand analysis with novel topological machine learning methods. Our approach sifts through large chemical libraries to identify promising molecular structures for targeting specific proteins with high precision. While many machine learning models have proven effective on benchmark datasets, we apply these techniques to discover compounds targeting methylcitrate dehydratase (AcnD), the second enzyme in the bacterial propionate catabolism pathway. Propionate catabolism is essential in pathogenic bacteria for utilizing host derived lipids and amino acids. Inefficient removal of propionate can lead to toxic accumulation that threatens bacterial survival, making this pathway a potential antimicrobial target. We translate ligand molecular structures into topological vectors and use tailored topological models to prioritize compounds with characteristics consistent with blocking the AcnD active site. Molecular docking simulations indicate that prioritized compounds interact with key amino acid residues critical to AcnD function. Among these, 2-methylidenebutanedioic acid (itaconic acid, itaconate) ranks highly as a potential molecular scaffold for targeting AcnD. Using bacterial growth assays, we find that itaconate at 29.13 mM completely inhibits the growth of <em>Pseudomonas aeruginosa</em> and <em>Acinetobacter baumannii</em> in carbon rich liquid cultures. These findings reinforce itaconate’s potential as an antimicrobial metabolite and support the hypothesis that it can disrupt bacterial propionate catabolism, potentially by inhibiting AcnD and promoting the accumulation of toxic intermediates. Overall, our study underscores the value of integrating topology based ligand modeling with comparative sequence structure function analysis and docking to identify molecular scaffolds with favorable geometric fit, energy, and interaction profiles, guiding downstream optimization and experimental validation. Our code is available at (<span><span>https://github.com/AstritTola/Molecular-Compounds-Targeting</span><svg><path></path></svg></span>).</div></div>","PeriodicalId":16361,"journal":{"name":"Journal of molecular graphics & modelling","volume":"144 ","pages":"Article 109287"},"PeriodicalIF":3.0,"publicationDate":"2026-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145980547","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-14DOI: 10.1016/j.jmgm.2026.109284
Yago Mendes Paes , João L.R. Scaini , Vania R. de Lima , Adriano Velasque Werhli , Pedro Almeida da Silva , José Rafael Bordin , Karina dos Santos Machado
Developing simplified yet representative models of the complex Mycobacterium tuberculosis inner membrane is crucial for advancing Molecular Dynamics of this pathogen. Phosphatidyl-myo-inositol dimannosides (PIM), one of the most abundant lipids in this membrane, provides an ideal basis for such a model. In this study, we proposed a minimal, single-component atomistic PIM bilayer for use in M. tuberculosis research. We validate the model by assessing its ability to reproduce distinct temperature-dependent ordering regimes, with a more ordered, gel-like behavior at 310 K and increased fluidity at 363.15 K, its capacity for spontaneous self-assembly, and its interaction with the native transmembrane efflux pump, Tap (Rv1258c). Our simulations confirm that the model exhibits the correct phase behavior at experimental temperatures and readily self-assembles into an extended lamellar bilayer-like structure. Importantly, the PIM membrane provides a significantly more stable environment for the embedded Tap protein compared to a standard dipalmitoylphosphatidylcholine (DPPC) bilayer. These findings confirm the PIM bilayer as a robust and promising model. It is particularly well suited for investigating the protein–lipid interactions central to multidrug resistance in M. tuberculosis and for exploring phenomena such as the bacterial immunological thermostat.
{"title":"A molecular dynamics study of PIM2 lipid bilayer membranes","authors":"Yago Mendes Paes , João L.R. Scaini , Vania R. de Lima , Adriano Velasque Werhli , Pedro Almeida da Silva , José Rafael Bordin , Karina dos Santos Machado","doi":"10.1016/j.jmgm.2026.109284","DOIUrl":"10.1016/j.jmgm.2026.109284","url":null,"abstract":"<div><div>Developing simplified yet representative models of the complex <em>Mycobacterium tuberculosis</em> inner membrane is crucial for advancing Molecular Dynamics of this pathogen. Phosphatidyl-myo-inositol dimannosides (PIM<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span>), one of the most abundant lipids in this membrane, provides an ideal basis for such a model. In this study, we proposed a minimal, single-component atomistic PIM<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span> bilayer for use in <em>M. tuberculosis</em> research. We validate the model by assessing its ability to reproduce distinct temperature-dependent ordering regimes, with a more ordered, gel-like behavior at 310 K and increased fluidity at 363.15 K, its capacity for spontaneous self-assembly, and its interaction with the native transmembrane efflux pump, Tap (Rv1258c). Our simulations confirm that the model exhibits the correct phase behavior at experimental temperatures and readily self-assembles into an extended lamellar bilayer-like structure. Importantly, the PIM<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span> membrane provides a significantly more stable environment for the embedded Tap protein compared to a standard dipalmitoylphosphatidylcholine (DPPC) bilayer. These findings confirm the PIM<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span> bilayer as a robust and promising model. It is particularly well suited for investigating the protein–lipid interactions central to multidrug resistance in <em>M. tuberculosis</em> and for exploring phenomena such as the bacterial immunological thermostat.</div></div>","PeriodicalId":16361,"journal":{"name":"Journal of molecular graphics & modelling","volume":"144 ","pages":"Article 109284"},"PeriodicalIF":3.0,"publicationDate":"2026-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146029906","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-13DOI: 10.1016/j.jmgm.2026.109279
Muslim Raza , Nurit Haspel , Anu Sharma , Sung Hugh Choi , Xavier De Luna , Jason J. Evans
Neuropilin 1 (NRP1) mediates lung branching angiogenesis and plays a vital role in cancer progression, especially in solid tumors. Its natural ligands, VEGFA and VEGFB, bind to the b1 binding pocket of NRP1 through hydrophilic c-terminus sites. Viral, bacterial and human proteins have evolved to interact with NRP1, facilitating entry into the cell, and therefore probing databases for hydrophilic CendR sequences could be a useful source of potential inhibitors of NRP1. Molecular docking was used to estimate the binding energies of 4185 naturally occurring CendR peptides to the b1 binding pocket of NRP1. The data predicts that proline, alanine, phenylalanine, leucine, tryptophan and tyrosine in the X positions of XXXXRXXR significantly strengthens the binding of the CendR peptides to the b1 binding pocket of NRP1 and that the presence of glutamic acid, lysine and serine tend to negatively impact binding. Three peptides predicted to have strong affinities and three peptides predicted to have weaker affinities were selected for molecular dynamic (MD) simulations. The data confirms that the interactions between the c-terminal arginine of these CendR peptides with several key residues, including Asp320, Thr316, Tyr297, and Tyr353, of the b1 binding site of NRP1 are particularly stable. During the MD simulations the three peptides predicted to be strong binders showed negative average free energies of interaction, while the three peptides predicted to bind more weakly showed positive free energies of interaction, providing validation of the docking results.
{"title":"Evaluation of CendR peptides mined from protein databases as potential inhibitors of neuropilin-1 using an in-silico molecular modeling approach","authors":"Muslim Raza , Nurit Haspel , Anu Sharma , Sung Hugh Choi , Xavier De Luna , Jason J. Evans","doi":"10.1016/j.jmgm.2026.109279","DOIUrl":"10.1016/j.jmgm.2026.109279","url":null,"abstract":"<div><div>Neuropilin 1 (NRP1) mediates lung branching angiogenesis and plays a vital role in cancer progression, especially in solid tumors. Its natural ligands, VEGFA and VEGFB, bind to the b1 binding pocket of NRP1 through hydrophilic c-terminus sites. Viral, bacterial and human proteins have evolved to interact with NRP1, facilitating entry into the cell, and therefore probing databases for hydrophilic CendR sequences could be a useful source of potential inhibitors of NRP1. Molecular docking was used to estimate the binding energies of 4185 naturally occurring CendR peptides to the b1 binding pocket of NRP1. The data predicts that proline, alanine, phenylalanine, leucine, tryptophan and tyrosine in the X positions of XXXXRXXR significantly strengthens the binding of the CendR peptides to the b1 binding pocket of NRP1 and that the presence of glutamic acid, lysine and serine tend to negatively impact binding. Three peptides predicted to have strong affinities and three peptides predicted to have weaker affinities were selected for molecular dynamic (MD) simulations. The data confirms that the interactions between the c-terminal arginine of these CendR peptides with several key residues, including Asp320, Thr316, Tyr297, and Tyr353, of the b1 binding site of NRP1 are particularly stable. During the MD simulations the three peptides predicted to be strong binders showed negative average free energies of interaction, while the three peptides predicted to bind more weakly showed positive free energies of interaction, providing validation of the docking results.</div></div>","PeriodicalId":16361,"journal":{"name":"Journal of molecular graphics & modelling","volume":"144 ","pages":"Article 109279"},"PeriodicalIF":3.0,"publicationDate":"2026-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146010722","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-13DOI: 10.1016/j.jmgm.2026.109280
Yingxuan Huang , W. Eltayeb Ahmed , Muhammad Farhan Hanif , Saba Hanif , Muhammad Imran , Muhammad Kamran Siddiqui
Quantitative structure property relationship(QSPR) has emerged as an indispensable tool for the estimation of physicochemical properties in drug molecules using mathematical and computational methods. Here, we introduce novel reverse degree based topological indices to see their applicability in case of selected antibiotic compounds property prediction. Reliable models to predict properties such as the boiling point, molar refractivity and enthalpy of vaporization exist to correlate molecular structure with experimentally reported physicochemical parameters. We have analyzed structurally different antibiotics with regression models developed in Python and SPSS in order to guarantee the robustness and reproducibility. We note here that predictive measures of cubic regression models seem to perform better, as observed through generally greater correlation coefficients. The results show that the reverse topological indices are efficient for recording structural differences in antibiotic molecules and they can be excellent descriptors for predicting their physical and chemical properties. It also stresses that, the use of reverse degree based descriptors on antibiotic compounds is new, providing a basis for further QSPR modeling for more general drug families. This work is part of a growing trend to study the interfaces between graph theory and cheminformatics where new indices help to improve our understanding over molecular properties with importance for drug design.
{"title":"On QSPR analysis for predicting efficacy of physicochemical properties of antibiotics drugs via topological indices and regression models","authors":"Yingxuan Huang , W. Eltayeb Ahmed , Muhammad Farhan Hanif , Saba Hanif , Muhammad Imran , Muhammad Kamran Siddiqui","doi":"10.1016/j.jmgm.2026.109280","DOIUrl":"10.1016/j.jmgm.2026.109280","url":null,"abstract":"<div><div>Quantitative structure property relationship(QSPR) has emerged as an indispensable tool for the estimation of physicochemical properties in drug molecules using mathematical and computational methods. Here, we introduce novel reverse degree based topological indices to see their applicability in case of selected antibiotic compounds property prediction. Reliable models to predict properties such as the boiling point, molar refractivity and enthalpy of vaporization exist to correlate molecular structure with experimentally reported physicochemical parameters. We have analyzed structurally different antibiotics with regression models developed in Python and SPSS in order to guarantee the robustness and reproducibility. We note here that predictive measures of cubic regression models seem to perform better, as observed through generally greater correlation coefficients. The results show that the reverse topological indices are efficient for recording structural differences in antibiotic molecules and they can be excellent descriptors for predicting their physical and chemical properties. It also stresses that, the use of reverse degree based descriptors on antibiotic compounds is new, providing a basis for further QSPR modeling for more general drug families. This work is part of a growing trend to study the interfaces between graph theory and cheminformatics where new indices help to improve our understanding over molecular properties with importance for drug design.</div></div>","PeriodicalId":16361,"journal":{"name":"Journal of molecular graphics & modelling","volume":"144 ","pages":"Article 109280"},"PeriodicalIF":3.0,"publicationDate":"2026-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145980543","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-13DOI: 10.1016/j.jmgm.2026.109288
Pınar Siyah , Firat Baris Barlas
Cancer is the second leading cause of death globally and remains a priority due to its impact on life quality, treatment complexity, and high costs. To expedite drug development, researchers are increasingly repurposing FDA-approved drugs and clinical candidates, reducing time and costs through in silico methods. In this study, 3235 FDA-approved and clinical molecules were screened for EGFR inhibition, a significant target due to its role in cancer progression and treatment resistance. A pharmacophore model was generated based on erlotinib's co-crystallized structure and quantitative structure-activity relationships. Molecules meeting the pharmacophoric criteria underwent SP and XP docking, with thresholds of −6.00 kcal/mol and −7.00 kcal/mol, respectively, followed by anti-cancer potential analysis via MetaCore/MetaDrug and MD simulations at 1, 10, and 100 ns to assess EGFR-binding stability. For the molecule Ticagrelor, which demonstrated particularly promising results, and Erlotinib cell culture viability assays were conducted across three cell lines—cancerous A549, U87, and healthy BEAS-2B— (IC50) of, 8.2576 μM, 9.4058 μM, and 15.893 μM, respectively for Ticagrelor and 11.708 μM, 12.747 μM and 14.6709 μM, respectively for Erlotinib. In silico results highlight Ticagrelor's significant EGFR-inhibiting potential with enhanced binding stability compared to the reference.
{"title":"Repurposing drugs for EGFR-targeted cancer therapy: An in silico and in vitro study with pharmacophore-based insights","authors":"Pınar Siyah , Firat Baris Barlas","doi":"10.1016/j.jmgm.2026.109288","DOIUrl":"10.1016/j.jmgm.2026.109288","url":null,"abstract":"<div><div>Cancer is the second leading cause of death globally and remains a priority due to its impact on life quality, treatment complexity, and high costs. To expedite drug development, researchers are increasingly repurposing FDA-approved drugs and clinical candidates, reducing time and costs through in silico methods. In this study, 3235 FDA-approved and clinical molecules were screened for EGFR inhibition, a significant target due to its role in cancer progression and treatment resistance. A pharmacophore model was generated based on erlotinib's co-crystallized structure and quantitative structure-activity relationships. Molecules meeting the pharmacophoric criteria underwent SP and XP docking, with thresholds of −6.00 kcal/mol and −7.00 kcal/mol, respectively, followed by anti-cancer potential analysis via MetaCore/MetaDrug and MD simulations at 1, 10, and 100 ns to assess EGFR-binding stability. For the molecule Ticagrelor, which demonstrated particularly promising results, and Erlotinib cell culture viability assays were conducted across three cell lines—cancerous A549, U87, and healthy BEAS-2B— (IC50) of, 8.2576 μM, 9.4058 μM, and 15.893 μM, respectively for Ticagrelor and 11.708 μM, 12.747 μM and 14.6709 μM, respectively for Erlotinib. In silico results highlight Ticagrelor's significant EGFR-inhibiting potential with enhanced binding stability compared to the reference.</div></div>","PeriodicalId":16361,"journal":{"name":"Journal of molecular graphics & modelling","volume":"144 ","pages":"Article 109288"},"PeriodicalIF":3.0,"publicationDate":"2026-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146010770","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Alzheimer's disease is an unavoidable neurological disorder in which the death of brain cells brings on memory loss, cognitive decline, and eventual dementia. There is no recognized treatment for Alzheimer's illness. By the year 2050, it is expected that the global population will witness approximately 100 million cases of Alzheimer's disease (AD). Despite recognizing AD as a formidable illness for over a century, no effective cure has been discovered thus far. Synaptic dysfunction could result from disturbed synaptic calcium handling caused by excessive activation of glutamate receptors, particularly the N-methyl-D-aspartate receptors (NMDARs). Glutamate serves as the brain's primary excitatory neurotransmitter, acting on ionotropic and metabotropic glutamate receptors. In recent years, several pharmacologically active substances derived from plants, animals, and microbes have shown promise in treating AD by focusing on various pathogenic processes. Initially, we used virtual screening to assess natural product-like compounds against NMDA receptors. In this research study, we have screened a natural compound database derived from zinc15. The best candidate was then validated through molecular dynamics simulation (MDS). The results revealed that out of 4221 compounds tested, only 165 showed superior binding interactions compared to native ligands, making them inhibitors for protein. Further analysis using ADMET indicates favorable drug-like properties, particularly for CNS drug-likeness. The MDS results, including RMSD, RMSF, Rg, and residue interactions, indicated a strong and stable association between top molecules and target protein. This confirms that top molecules can effectively remain within the binding pockets of the target proteins, forming stable protein-ligand complexes.
阿尔茨海默病是一种不可避免的神经系统疾病，脑细胞死亡会导致记忆丧失、认知能力下降，最终导致痴呆。阿尔茨海默病目前还没有公认的治疗方法。到2050年，预计全球人口将见证约1亿阿尔茨海默病（AD）病例。尽管一个多世纪以来人们就认识到阿尔茨海默病是一种可怕的疾病，但迄今为止还没有发现有效的治疗方法。突触功能障碍可能是由于谷氨酸受体，特别是n -甲基- d -天冬氨酸受体（NMDARs）的过度激活引起的突触钙处理紊乱。谷氨酸是大脑的主要兴奋性神经递质，作用于嗜离子性和代谢性谷氨酸受体。近年来，从植物、动物和微生物中提取的一些药理活性物质通过关注各种致病过程，在治疗AD方面显示出了希望。最初，我们使用虚拟筛选来评估抗NMDA受体的天然产物样化合物。在本研究中，我们筛选了一个来源于zinc15的天然化合物数据库。然后通过分子动力学模拟（MDS）验证最佳候选物。结果显示，在测试的4221种化合物中，只有165种与天然配体相比表现出更好的结合相互作用，使其成为蛋白质的抑制剂。进一步的ADMET分析显示了良好的药物样性质，特别是对中枢神经系统药物相似。MDS结果包括RMSD、RMSF、Rg和残基相互作用，表明顶分子与靶蛋白之间存在强而稳定的关联。这证实了顶部分子可以有效地留在靶蛋白的结合口袋内，形成稳定的蛋白质-配体复合物。
{"title":"Investigating the anti-Alzheimer potential of biogenic compounds from Zinc15 database as NMDA antagonist: An in-silico approach.","authors":"Somdatta Chaudhari, Asavari Shinde, Mukund Salunke, Shriram Bairagi, Azad Dhage, Pinkal Patel, Vivek Rathod, Sandeep Pathare, Nojood Altwaijry, Mohd Shahnawaz Khan","doi":"10.1016/j.jmgm.2026.109277","DOIUrl":"https://doi.org/10.1016/j.jmgm.2026.109277","url":null,"abstract":"<p><p>Alzheimer's disease is an unavoidable neurological disorder in which the death of brain cells brings on memory loss, cognitive decline, and eventual dementia. There is no recognized treatment for Alzheimer's illness. By the year 2050, it is expected that the global population will witness approximately 100 million cases of Alzheimer's disease (AD). Despite recognizing AD as a formidable illness for over a century, no effective cure has been discovered thus far. Synaptic dysfunction could result from disturbed synaptic calcium handling caused by excessive activation of glutamate receptors, particularly the N-methyl-D-aspartate receptors (NMDARs). Glutamate serves as the brain's primary excitatory neurotransmitter, acting on ionotropic and metabotropic glutamate receptors. In recent years, several pharmacologically active substances derived from plants, animals, and microbes have shown promise in treating AD by focusing on various pathogenic processes. Initially, we used virtual screening to assess natural product-like compounds against NMDA receptors. In this research study, we have screened a natural compound database derived from zinc15. The best candidate was then validated through molecular dynamics simulation (MDS). The results revealed that out of 4221 compounds tested, only 165 showed superior binding interactions compared to native ligands, making them inhibitors for protein. Further analysis using ADMET indicates favorable drug-like properties, particularly for CNS drug-likeness. The MDS results, including RMSD, RMSF, Rg, and residue interactions, indicated a strong and stable association between top molecules and target protein. This confirms that top molecules can effectively remain within the binding pockets of the target proteins, forming stable protein-ligand complexes.</p>","PeriodicalId":16361,"journal":{"name":"Journal of molecular graphics & modelling","volume":"144 ","pages":"109277"},"PeriodicalIF":3.0,"publicationDate":"2026-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146157389","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-12DOI: 10.1016/j.jmgm.2026.109283
Mohamed Bakhit, Sina Karimzadeh, Tien-Chien Jen
This study investigates the potential of Mo2C MXene as a hydrogen storage material using density functional theory (DFT) and molecular dynamics (MD) simulations to examine its structural stability, electronic properties, and hydrogen adsorption behavior. The optimized Mo2C structure exhibits a hexagonal lattice with favorable adsorption sites over Mo atoms and shows a surface area expansion of approximately 4 % after hydrogen loading while maintaining lattice symmetry. Thermodynamic stability is confirmed through adsorption energy calculations, which reveal a clear relationship between energy levels and hydrogen concentration. The results indicate that H2 adsorption on Mo2C is a thermodynamically favorable and exothermic process, with adsorption energies ranging from −0.184 to −0.528 eV, satisfying the criteria for practical hydrogen storage applications. Charge transfer analysis identifies Mo atoms as electron acceptors. Density of States (DOS) calculations reveal a near-zero band gap, confirming the metallic nature of Mo2C, while Projected DOS (PDOS) and orbital maps show significant hybridization and electronic polarization among H, Mo, and C atoms. Charge density difference maps highlight effective charge redistribution with strong electric fields around Mo atoms. MD simulations further confirm the structural stability of the Mo2C–H2 system, showing minimal deformation during a 100 ps simulation and supporting efficient hydrogen adsorption. Overall, these findings establish Mo2C MXene as a promising candidate for hydrogen storage applications and provide valuable insights for experimental validation and further development of sustainable energy storage technologies.
{"title":"A first-principles study of hydrogen storage on MXene Mo2C monolayer","authors":"Mohamed Bakhit, Sina Karimzadeh, Tien-Chien Jen","doi":"10.1016/j.jmgm.2026.109283","DOIUrl":"10.1016/j.jmgm.2026.109283","url":null,"abstract":"<div><div>This study investigates the potential of Mo<sub>2</sub>C MXene as a hydrogen storage material using density functional theory (DFT) and molecular dynamics (MD) simulations to examine its structural stability, electronic properties, and hydrogen adsorption behavior. The optimized Mo<sub>2</sub>C structure exhibits a hexagonal lattice with favorable adsorption sites over Mo atoms and shows a surface area expansion of approximately 4 % after hydrogen loading while maintaining lattice symmetry. Thermodynamic stability is confirmed through adsorption energy calculations, which reveal a clear relationship between energy levels and hydrogen concentration. The results indicate that H<sub>2</sub> adsorption on Mo<sub>2</sub>C is a thermodynamically favorable and exothermic process, with adsorption energies ranging from −0.184 to −0.528 eV, satisfying the criteria for practical hydrogen storage applications. Charge transfer analysis identifies Mo atoms as electron acceptors. Density of States (DOS) calculations reveal a near-zero band gap, confirming the metallic nature of Mo<sub>2</sub>C, while Projected DOS (PDOS) and orbital maps show significant hybridization and electronic polarization among H, Mo, and C atoms. Charge density difference maps highlight effective charge redistribution with strong electric fields around Mo atoms. MD simulations further confirm the structural stability of the Mo<sub>2</sub>C–H<sub>2</sub> system, showing minimal deformation during a 100 ps simulation and supporting efficient hydrogen adsorption. Overall, these findings establish Mo<sub>2</sub>C MXene as a promising candidate for hydrogen storage applications and provide valuable insights for experimental validation and further development of sustainable energy storage technologies.</div></div>","PeriodicalId":16361,"journal":{"name":"Journal of molecular graphics & modelling","volume":"144 ","pages":"Article 109283"},"PeriodicalIF":3.0,"publicationDate":"2026-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145980546","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-12DOI: 10.1016/j.jmgm.2026.109285
Sidra Manzoor , Nadeem Raza , Faheem Abbas
Organic solar cells (OSCs) offer lightweight, flexible, and cost−effective energy solutions. However, fullerene−based systems face limitations in stability, tunability, and absorption, prompting the exploration of non−fullerene alternatives to enhance efficiency and scalability. In this work, five newly designed molecules (2TT−1A to 2TT−5A) were systematically studied using Density Functional Theory (DFT) and Time−Dependent DFT (TD−DFT) at the B3LYP/6−311G (d, p) level in both gas and solvent (chloroform) phases. Key optoelectronic properties, including HOMO−LUMO gaps, absorption spectra, dipole moments, and excitation energies, were analyzed to evaluate their photovoltaic performance. All compounds demonstrated strong light−harvesting abilities, with a notable redshift in the absorption spectra observed in the solvent phase. Among them, 2TT−5A stood out with the narrowest energy gap (1.35 eV), the longest absorption wavelength (861 nm), the highest dipole moment (12.17 D), and the lowest excitation energy (1.43 eV), indicating efficient charge transfer and exciton dissociation. Open−circuit voltages (Voc) ranging from 0.54 to 1.38 V also suggest good photovoltaic potential. Additionally, the nonlinear optical (NLO) and organic light−emitting diodes (OLED) properties of 2TT−5A were explored, revealing significant hyperpolarizability and a favorable emission profile. These results suggested that 2TT−5A is an exceptional multifunctional candidate, encouraging experimental synthesis and validating this material's stability, potentially accelerating the development of multifunctional organic optoelectronic devices.
{"title":"Unveiling the potential of π-conjugated 2TT-R non-fullerene alternatives for multifunctional optoelectronic applications: A first-principles study","authors":"Sidra Manzoor , Nadeem Raza , Faheem Abbas","doi":"10.1016/j.jmgm.2026.109285","DOIUrl":"10.1016/j.jmgm.2026.109285","url":null,"abstract":"<div><div>Organic solar cells (OSCs) offer lightweight, flexible, and cost−effective energy solutions. However, fullerene−based systems face limitations in stability, tunability, and absorption, prompting the exploration of non−fullerene alternatives to enhance efficiency and scalability. In this work, five newly designed molecules <strong>(2</strong><strong>TT−1A to 2</strong><strong>TT−5A)</strong> were systematically studied using Density Functional Theory (DFT) and Time−Dependent DFT (TD−DFT) at the B3LYP/6−311G (d, p) level in both gas and solvent (chloroform) phases. Key optoelectronic properties, including HOMO−LUMO gaps, absorption spectra, dipole moments, and excitation energies, were analyzed to evaluate their photovoltaic performance. All compounds demonstrated strong light−harvesting abilities, with a notable redshift in the absorption spectra observed in the solvent phase. Among them, <strong>2</strong><strong>TT−5A</strong> stood out with the narrowest energy gap (1.35 eV), the longest absorption wavelength (861 nm), the highest dipole moment (12.17 D), and the lowest excitation energy (1.43 eV), indicating efficient charge transfer and exciton dissociation. Open−circuit voltages (<em>V</em><sub>oc</sub>) ranging from 0.54 to 1.38 V also suggest good photovoltaic potential. Additionally, the nonlinear optical (NLO) and organic light−emitting diodes (OLED) properties of <strong>2</strong><strong>TT−5A</strong> were explored, revealing significant hyperpolarizability and a favorable emission profile. These results suggested that <strong>2</strong><strong>TT−5A</strong> is an exceptional multifunctional candidate, encouraging experimental synthesis and validating this material's stability, potentially accelerating the development of multifunctional organic optoelectronic devices.</div></div>","PeriodicalId":16361,"journal":{"name":"Journal of molecular graphics & modelling","volume":"144 ","pages":"Article 109285"},"PeriodicalIF":3.0,"publicationDate":"2026-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146018703","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Human metapneumovirus (HMPV) remains a major respiratory pathogen without approved antivirals, highlighting the urgent need for novel therapeutics. This study implemented an integrative computational pipeline combining virtual screening, molecular docking, 2 μs molecular dynamics (MD) simulations, density functional theory (DFT), pharmacophore modeling, and ADMET profiling to identify potent HMPV inhibitors from Traditional Chinese Medicine. Among 180 screened phytoconstituents, glycyrrhizin (–9.3 kcal mol−1), hesperidin (–9.1 kcal mol−1), and saikosaponins (–9.0 kcal mol−1) exhibited strong binding affinities toward the HMPV matrix protein (PDB ID: 5WB0). Extended MD simulations confirmed complex stability with RMSD 0.17–0.22 nm, average of 3–5 persistent H-bonds, and DCCM correlation coefficient = 0.86 for glycyrrhizin. MM-PBSA binding free energies (ΔG_bind) of –46.2 ± 2.5, –44.7 ± 2.8, and –43.9 ± 2.2 kJ mol−1 for glycyrrhizin, hesperidin, and oseltamivir respectively, validated strong and stable interactions. DFT results indicated favorable electronic reactivity (HOMO–LUMO gap = 3.86 eV; electrophilicity = 2.74 eV), enhancing ligand-target complementarity. ADMET analysis predicted low systemic toxicity (LD50= 380–530 mg kg−1) but revealed moderate CYP3A4/CYP2C9 inhibition, suggesting the need for metabolic stability evaluation. Compared with reported fusion inhibitors such as EGCG and rutin, this matrix-targeted strategy introduces a distinct therapeutic mechanism. Overall, these findings establish a robust computational foundation for developing and experimentally validating potent natural inhibitors against HMPV.
{"title":"Exploring traditional Chinese medicine for antiviral drug discovery: A computational approach to combat human metapneumovirus (HMPV)","authors":"Amit Dubey , Manish Kumar , Aisha Tufail , Vivek Dhar Dwivedi","doi":"10.1016/j.jmgm.2026.109290","DOIUrl":"10.1016/j.jmgm.2026.109290","url":null,"abstract":"<div><div>Human metapneumovirus (HMPV) remains a major respiratory pathogen without approved antivirals, highlighting the urgent need for novel therapeutics. This study implemented an integrative computational pipeline combining virtual screening, molecular docking, 2 μs molecular dynamics (MD) simulations, density functional theory (DFT), pharmacophore modeling, and ADMET profiling to identify potent HMPV inhibitors from Traditional Chinese Medicine. Among 180 screened phytoconstituents, <strong>glycyrrhizin (–9.3 kcal mol<sup>−1</sup>)</strong>, <strong>hesperidin (–9.1 kcal mol<sup>−1</sup>)</strong>, and <strong>saikosaponins (–9.0 kcal mol<sup>−1</sup>)</strong> exhibited strong binding affinities toward the HMPV matrix protein (<strong>PDB ID: 5WB0</strong>). Extended MD simulations confirmed complex stability with <strong>RMSD 0.17</strong>–<strong>0.22 nm</strong>, average of <strong>3</strong>–<strong>5 persistent H-bonds</strong>, and <strong>DCCM correlation coefficient = 0.86</strong> for glycyrrhizin. <strong>MM-PBSA</strong> binding free energies (ΔG_bind) of <strong>–46.2 ± 2.5</strong>, <strong>–44.7 ± 2.8</strong>, and <strong>–43.9 ± 2.2 kJ mol<sup>−1</sup></strong> for glycyrrhizin, hesperidin, and oseltamivir respectively, validated strong and stable interactions. <strong>DFT</strong> results indicated favorable electronic reactivity (HOMO–LUMO gap = 3.86 eV; electrophilicity = 2.74 eV), enhancing ligand-target complementarity. <strong>ADMET</strong> analysis predicted low systemic toxicity (<strong>LD<sub>50</sub></strong> <strong>= 380</strong>–<strong>530 mg kg<sup>−1</sup></strong>) but revealed moderate <strong>CYP3A4/CYP2C9 inhibition</strong>, suggesting the need for metabolic stability evaluation. Compared with reported fusion inhibitors such as EGCG and rutin, this <strong>matrix-targeted strategy</strong> introduces a distinct therapeutic mechanism. Overall, these findings establish a robust computational foundation for developing and experimentally validating potent natural inhibitors against HMPV.</div></div>","PeriodicalId":16361,"journal":{"name":"Journal of molecular graphics & modelling","volume":"144 ","pages":"Article 109290"},"PeriodicalIF":3.0,"publicationDate":"2026-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145980434","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study employs DFT calculations to investigate the structural stability and electronic properties of pristine and transition-metal-doped boron nitride (BN) nanosheets, using yttrium (Y) and zirconium (Zr) as dopants, as well as their gas-sensing response toward formamide (FO). The findings show that introducing Y or Zr atoms leads to notable modifications in the electronic structure of the BN nanosheet, substantially improving its chemical reactivity and adsorption performance. In the aqueous phase, the interaction between FO and Y/Zr-doped BN nanosheets becomes moderately weaker, with adsorption energies decreasing to – 4.23 to – 24.97 kcal mol−1; however, the most stable complexes still exhibit comparatively strong binding. Solvation also alters the electronic structure of the nanosheets, leading to noticeable variations in their energy gaps. Despite this reduction in interaction strength, both doped materials retain high sensitivity toward FO in water, with ZrBN reaching 99.9 %/1.43 × 103 % and YBN achieving 55.9 %/86.5 %. Moreover, the nanosheets exhibit extremely short recovery times in the liquid phase, with values of 1.27 × 10−15 s for ZrBN and 2.06 s for YBN, enabling rapid FO desorption and efficient restoration of active metal sites. These combined features confirm the strong potential of Y- and Zr-doped BN nanosheets as reusable and high-performance sensors for formamide detection in aqueous environments.
{"title":"Y- and Zr-modified boron nitride nanosheets as efficient sensors for formamide: A first-principles approach","authors":"Meryem Derdare, Abdel-Ghani Boudjahem, Nedjoua Cheghib","doi":"10.1016/j.jmgm.2026.109278","DOIUrl":"10.1016/j.jmgm.2026.109278","url":null,"abstract":"<div><div>This study employs DFT calculations to investigate the structural stability and electronic properties of pristine and transition-metal-doped boron nitride (BN) nanosheets, using yttrium (Y) and zirconium (Zr) as dopants, as well as their gas-sensing response toward formamide (FO). The findings show that introducing Y or Zr atoms leads to notable modifications in the electronic structure of the BN nanosheet, substantially improving its chemical reactivity and adsorption performance. In the aqueous phase, the interaction between FO and Y/Zr-doped BN nanosheets becomes moderately weaker, with adsorption energies decreasing to – 4.23 to – 24.97 kcal mol<sup>−1</sup>; however, the most stable complexes still exhibit comparatively strong binding. Solvation also alters the electronic structure of the nanosheets, leading to noticeable variations in their energy gaps. Despite this reduction in interaction strength, both doped materials retain high sensitivity toward FO in water, with ZrBN reaching 99.9 %/1.43 × 10<sub>3</sub> % and YBN achieving 55.9 %/86.5 %. Moreover, the nanosheets exhibit extremely short recovery times in the liquid phase, with values of 1.27 × 10<sup>−15</sup> s for ZrBN and 2.06 s for YBN, enabling rapid FO desorption and efficient restoration of active metal sites. These combined features confirm the strong potential of Y- and Zr-doped BN nanosheets as reusable and high-performance sensors for formamide detection in aqueous environments.</div></div>","PeriodicalId":16361,"journal":{"name":"Journal of molecular graphics & modelling","volume":"144 ","pages":"Article 109278"},"PeriodicalIF":3.0,"publicationDate":"2026-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145980542","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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