DOCKING BASED PHARMACOPHORE MODEL FOR MYCOBACTERIUM TUBERCULOSIS PEPTIDE DEFORMYLASE INHIBITORS AND ITS APPLICATION IN DRUG DESIGNING

摘要

Objective: Peptide deformylase (PDF) is a metalloprotease enzyme playing important role in protein synthesis. This enzyme is encoded by def gene and its essentiality makes it as attractive drug-target in drug discovery process. The objective of this study was to explore the computational approaches to investigate PDF inhibitors. Methods: In this study, we have explored the binding mode of Mycobacterium tuberculosis (M.tb) PDF inhibitors using AutoDock and identified the key residues involved in bonding. We have also screened the Zinc database and identified potential hits with more potent binding energy as compared to previously known inhibitors. Results: Our study suggested that Val50 and Leu107 are the key residues involve in H-bonding. We have also identified two hydrophobic pockets and two electron acceptor regions using docking based pharmacophore features. Among the various docking based descriptors, binding free energy and unbound system energy showed a correlation value 0.14 and 0.65 with inhibitory activity. However, removal of two outliers identified by clustering technique showed the improvement in correlation value 0.44, and 0.89 with inhibitory activity. Conclusion: This study will be useful in future for better inhibitor designing and understanding the ligand protein interactions against mtb PDF protein