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<p>Multidrug resistance is caused by bacteria that generate New Delhi metallo-β-lactamase-1 (NDM-1), an enzyme that breaks down lactam antibiotics, including cephalosporin, penicillin, and carbapenems. The worldwide spread of NDM-1 is a serious threat to public health and a significant economic burden for the development of new antibiotics. Thus, the search for successful NDM-1 inhibitors is a challenging task. In the present investigation, a holistic computational approach was adopted, and a comprehensive bioinformatics workflow was used to screen a library of 10,000 compounds (ZINC library) against the target enzyme NDM-1. Techniques employed were molecular docking, molecular dynamics (MD) simulation, high-throughput virtual screening, and post-simulation analyses. Three compounds (ZINC000003860369, ZINC000013536586, and ZINC000006119198) were found to be the most promising inhibitors. Binding free-energy estimates together with MD trajectories analyses confirmed the formation of stable complexes between these ligands and NDM-1. The RMSDs for the three complexes were 1.51Å, 2.06Å, and 1.74Å, respectively, whereas the Apo (unbound) enzyme had a mean RMSD of 1.46Å, which suggests similar stability in the unbound state. Principal component analysis (PCA) and hydrogen-bond profiling analysis showed that there were fewer atomic fluctuations and a beneficial hydrogen-bond network for the novel complexes. It is particularly noteworthy that ZINC000003860369 formed the highest number of stable hydrogen bonds with residue ASP_95@OD2, which was continued in 145 simulation frames. Secondary-structure analyses and salt-bridge interaction analyses further supported the increase in stability of the ligand-NDM-1 complexes with minimal conformational changes of the protein upon ligand binding. This study sets a basic framework for the discovery of NDM-1 inhibitors. Nevertheless, computational predictions will need to be validated in the laboratory and in vivo experimentation to help with the development of these compounds for therapeutic purposes.</p>

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Identification of Novel Inhibitory Compounds against NDM-1, From High-Throughput Docking To Stability Analysis via Molecular Dynamics

  • 期刊论文

  • 发表日期：

    2026年3月13日

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  • Saad Amin,
  • Kalsoom Khan,
  • Hanan A. AL-Ghulikah,
  • Bader Alfardan,
  • Dawood Ahmad,
  • Sajjad Ahmad

摘要

Multidrug resistance is caused by bacteria that generate New Delhi metallo-β-lactamase-1 (NDM-1), an enzyme that breaks down lactam antibiotics, including cephalosporin, penicillin, and carbapenems. The worldwide spread of NDM-1 is a serious threat to public health and a significant economic burden for the development of new antibiotics. Thus, the search for successful NDM-1 inhibitors is a challenging task. In the present investigation, a holistic computational approach was adopted, and a comprehensive bioinformatics workflow was used to screen a library of 10,000 compounds (ZINC library) against the target enzyme NDM-1. Techniques employed were molecular docking, molecular dynamics (MD) simulation, high-throughput virtual screening, and post-simulation analyses. Three compounds (ZINC000003860369, ZINC000013536586, and ZINC000006119198) were found to be the most promising inhibitors. Binding free-energy estimates together with MD trajectories analyses confirmed the formation of stable complexes between these ligands and NDM-1. The RMSDs for the three complexes were 1.51Å, 2.06Å, and 1.74Å, respectively, whereas the Apo (unbound) enzyme had a mean RMSD of 1.46Å, which suggests similar stability in the unbound state. Principal component analysis (PCA) and hydrogen-bond profiling analysis showed that there were fewer atomic fluctuations and a beneficial hydrogen-bond network for the novel complexes. It is particularly noteworthy that ZINC000003860369 formed the highest number of stable hydrogen bonds with residue ASP_95@OD2, which was continued in 145 simulation frames. Secondary-structure analyses and salt-bridge interaction analyses further supported the increase in stability of the ligand-NDM-1 complexes with minimal conformational changes of the protein upon ligand binding. This study sets a basic framework for the discovery of NDM-1 inhibitors. Nevertheless, computational predictions will need to be validated in the laboratory and in vivo experimentation to help with the development of these compounds for therapeutic purposes.