In Silico Identification of Irreversible Cathepsin B Inhibitors as Anti- Cancer Agents: Virtual Screening, Covalent Docking Analysis and Molecular Dynamics Simulations

Cathepsin B is a cysteine protease that belongs to the papain superfamily. Malfunctions related to cathepsin B can lead to inflammation and cancer. Via an integrated in silico approach, this study is aimed to identify novel Michael acceptors-type compounds that can irreversibly inhibit cathepsin B enzyme via covalent bond formation with the active site cysteine residue. Here, we report the first account of covalent docking approach incorporated into a hybrid ligand/structure-based virtual screening to estimate the binding affinities of various compounds from chemical databases against the cathepsin B protein. For validation, compounds with experimentally determined anti-cathepsin B activity from PubChem bioassay database were also screened and covalently docked to the enzyme target. Interestingly, four novel compounds exhibited better covalent binding affinity when compared against the experimentally determined prototypes. Molecular dynamics simulations were performed to ensure the stability of the docked complexes and to allow further analysis on the MD average structures. Perresidue interaction decomposition analysis was carried out to provide deeper insight into the interaction themes of discovered hits with the active site residues. It is found that polar and hydrophobic interactions contributed the most towards drug binding. The hybrid computational methods applied in this study should serve as a powerful tool in the drug design and development process.