Computational Investigation of HDLP Inhibitors toward Anticancer Drug Design: Molecular Dynamics-Based Binding Energy Evaluation and Binding Pocket Characterization

Abstract

Histone deacetylases (HDACs) are well-established therapeutic targets in cancer due to their critical roles in regulating histone acetylation, chromatin structure, and gene expression, which are associated with cell growth, differentiation, and apoptosis. This study aims to investigate the binding interactions of hydroxamic acid–based inhibitors against histone deacetylase-like protein (HDLP) using the MM-PBSA method, assess their structural stability, and evaluate their inhibitory potential, employing integrated computational approaches. In this study, SAHA and newly designed derivatives CHR3996, ACY1215, HAD1, and HAD5 were systematically evaluated using integrated in-silico drug discovery approaches. Molecular docking was performed to predict binding orientations, key intermolecular interactions, and relative binding affinities toward the HDLP enzyme. To further validate docking results, molecular dynamics simulations were performed to assess the structural stability, compactness, and conformational flexibility of the HDLP–inhibitor complexes under dynamic conditions. Trajectory analyses, including RMSD, radius of gyration, RMSF, solvent-accessible surface area, and Ramachandran plots, indicated improved stability and favourable conformational behaviour for complexes involving SAHA, CHR3996, ACY1215, HAD5, and HAD3. In addition, MM-PBSA binding free energy calculations confirmed that CHR3996, ACY1215, HAD5, and HAD3 exhibit stronger binding affinities compared to the remaining inhibitors. The inhibitory potential of the selected compounds was further assessed by theoretically estimating IC₅₀ values from docking-derived binding energies. ACY1215, CHR3996, and SAHA demonstrated the most potent inhibition with predicted nanomolar IC₅₀ values, whereas HAD2–HAD4 showed moderate to weak activity. Overall, these findings identify CHR3996, ACY1215, HAD5, and HAD3 as promising HDAC inhibitor candidates for further lead optimization, experimental validation, and preclinical anticancer drug development.