In Silico Evaluation of Potential NDM-1 Inhibitors: An Integrated Docking and Molecular Dynamics Approach

<b>Background/Objectives:</b> Non-fermenting Gram-negative bacteria are resistant to most antibiotics, due to the production of enzymes such as NDM-1. Faced with this challenge, computational methods have become essential for the design of NDM-1 carbapenemase inhibitors, optimizing both the time and cost of the development of new lead molecules. <b>Methods:</b> In this study, molecular docking and molecular dynamics (MD) simulations were performed in order to identify effective inhibitors against the NDM-1 enzyme. Protein preparation was carried out using UCSF Chimera and AutoDockTools 1.5.7, while ligands were prepared with MarvinSketch, Avogadro, and AutoDockTools 1.5.7. Molecular docking was run with AutoDock4 and AutoDock4Zn, determining that molecules M26 (-13.23 kcal/mol with AutoDock4 and -13.11 kcal/mol with AutoDockZn) and M25 (-10.61 kcal/mol with AutoDock4 and -11.18 kcal/mol with AutoDockZn) presented the best binding energy affinities with NDM-1. The M26 molecule formed six hydrogen bonds with the enzyme. <b>Results:</b> MD simulations, performed with GROMACS, indicated that the NDM-1-M26, NDM-1-M35, and NDM-1-M37 complexes showed conformational stability and flexibility. <b>Conclusions:</b> These results suggest that the M26, M37, and M35 ligands have significant potential as leading candidates in the development of new NDM-1 inhibitors, outperforming the antibiotic Meropenem in some respects.