Structure-based virtual screening and molecular dynamics simulation for the identification of novel potential inhibitors for the NDM-1 of Klebsiella Pneumoniae from the marine natural products
Karthickeyan Chandrasekar, Parthasarathy Subbiah · Current Proteomics · 2026
The emergence of antibiotic-resistant bacteria, especially New Delhi Metallo-β-lactamase-1 (NDM-1) of Klebsiella pneumoniae , is a significant threat to serious public health. The aim of this study was to identify the marine natural compounds from brown, green, and red algae that have inhibitory binding characteristics to the New Delhi Metallo-β-lactamase-1 (NDM-1) protein. Structure-Based Virtual Screening (SBVS), Induced Fit Docking (IFD), and Molecular Dynamics (MD) simulation techniques were used in this study. Our outcomes provide significant emerging information for the development of novel drugs from marine natural products to treat bacterial infections of Klebsiella pneumoniae that are resistant to antibiotics. Initially, we obtained the NDM-1 protein (PDB ID: 5ZGE) 3D structure from Protein Data Bank (PDB) and retrieved the marine natural products of green algae (293 compounds), brown algae (1212 compounds), and red algae (1813 compounds), totaling 3,318 compounds from the Comprehensive Marine Natural Products Database (CMNPD). We performed the AutoDock Vina for structure-based virtual screening and filtered the best ranking compounds based on binding affinities scores. After the virtual screening, the induced fit docking for the top 4 ranked compounds was conducted by using the IFD applications in Schrodinger Suite software. Finally, the top-ranked compound of the protein-ligand complex of 100 ns molecular dynamics simulation was applied by using Desmond applications in Schrodinger Suite software. PyMOL software was used to illustrate the structure and binding interactions. Virtual screening from CMNPD was conducted using 3318 marine natural compounds against the NDM-1 protein. Based on the binding affinity score of AutoDock Vina, the four most competitive molecules were chosen for induced fit docking. From the induced fit docking results, we selected the protein-ligand complex with the highest glide score for use in MD simulation studies. This study result reveals that we were able to discover a potent binder from the marine natural product of CMNPD17791 that is found in brown algae. The main objective of our findings is to show potential inhibitory binding characteristics of marine algal products with the NDM-1 protein of Klebsiella pneumoniae based on a computational approach. Marine algal products provide a valuable and underexplored source of structurally diverse bioactive compounds relevant to drug discovery. The computational analysis of marine algal-derived candidates provides a cost-effective and rapid strategy for the initial step of molecular prioritization prior to experimental validation. The marine product CMNPD17791 showed a high potential for inhibitory activity with the NDM-1 protein of Klebsiella pneumoniae . Experimental validation is required to confirm whether this compound has the ability to inhibit NDM-1 enzymatic activity.