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Updated: Mar 1, 2026

Incorporating Target Protein Structure Flexibility and Dynamics in Computational Drug Discovery Using Ensemble-Based Docking Analysis
Published on: June 20, 2025
In Silico discovery of GES-5 inhibitors via molecular docking, molecular dynamics simulation studies, and ADMET
Manal Ghatesse1, Hicham Charoute2, Amal Raoufi3
1Laboratory of Health, Environment and Biotechnology, Faculty of Sciences Ain Chock, Hassan II University, Casablanca, Morocco; Laboratory of Molecular Bacteriology, Institut Pasteur du Maroc, Casablanca, Morocco.
Abstract:
The emergence of multidrug-resistant Enterobacteriaceae represents a major threat to global public health. Among the key resistance mechanisms, the production of β-lactamases enzymes that hydrolyze the β-lactam ring plays a central role in compromising antibiotic efficacy. Targeting these enzymes, particularly carbapenemases, remains a promising strategy for the development of novel antibacterial agents. In this study, we focused on the carbapenemase GES-5 and performed a large-scale virtual screening of 7527 natural compounds derived from two independent databases (1012 and 6515 compounds, respectively). Molecular docking was carried out using AutoDock Vina to identify high-affinity inhibitors. The pharmacokinetic and toxicity profiles of the top-ranked hits were evaluated through ADMET predictions using SwissADME and pkCSM. To further assess binding stability and dynamic behavior, 100 ns molecular dynamics simulations were conducted using GROMACS. Docking results revealed several compounds exhibiting low binding affinities (≤ -10 kcal/mol) toward the GES-5 active site. Among these, Riccardin C, Daturametelin A, and 2-hydroxysenaganolide emerged as the most promising candidates based on their favorable interaction patterns. ADMET analysis indicated that the majority of selected compounds possess acceptable pharmacokinetic properties and low predicted toxicity. Molecular dynamics simulations confirmed the structural stability of the protein-ligand complexes throughout the 100 ns trajectory. Overall, these findings identify promising natural inhibitors of GES-5 and provide a robust in silico framework for further experimental validation and lead optimization.
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