Structure-based virtual screening, molecular docking, and MD simulation studies: An in-silico approach for identifying potential MBL inhibitors

基于结构的虚拟筛选、分子对接和分子动力学模拟研究:一种用于识别潜在MBL抑制剂的计算机辅助方法

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Abstract

The global rise of antibiotic-resistant infections has been driven in part by the spread of bacteria producing metallo-β-lactamase (MBL), particularly New Delhi metallo-β-lactamase-1 (NDM-1). Currently, there are no clinically approved inhibitors targeting NDM-1 or other MBLs, highlighting the urgent need for novel therapeutic agents. This study addresses this gap by identifying potential NDM-1 inhibitors through a comprehensive in silico workflow. A total of 4,561 natural product compounds were screened using a machine learning (ML)-based quantitative structure-activity relationship (QSAR) model. Molecular docking was then performed to prioritize hits, followed by Tanimoto similarity-based clustering to identify representative compounds. The three most promising compounds identified were S721-1034, S904-0022, and N118-0137. 300 ns molecular dynamics (MD) simulation was used to examine binding interactions and stability of a control molecule (meropenem (0RV)) and the three selected compounds (S721-1034, S904-0022, and N118-0137) with the target protein. Among the three compounds evaluated, S904-0022 demonstrated consistent root mean square deviation (RMSD) values throughout the molecular dynamics (MD) simulation compared to the other two ligands. Additionally, S904-0022 exhibited considerable affinity with key residues, including Gln123, His250, Trp93, and Val73, indicating robust interactions with NDM-1. The strength of this interaction was further validated by a significantly favorable binding free energy of -35.77 kcal/mol, markedly better than the control compound (-18.90 kcal/mol). The strength of this interaction was further validated by a significantly favorable binding free energy of -35.77 kcal/mol, markedly better than the control compound (-18.90 kcal/mol). The findings of this study provide valuable insights into the molecular interactions and stability of these compounds, which can be used to improve drug development and explore the interactions between proteins and ligands. The study concluded that S904-0022 exhibited substantial therapeutic potential and requires additional experimental exploration as a potential NDM-1 inhibitor.

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