Abstract:
Antibiotic resistance is a major health issue as due to the emergence of multidrug resistant bacteria. Thus, there is an increasing need for the identification of new drug targets and discovery of novel scaffolds in the combat with infectious diseases. One mechanism that can be targeted is the pathogen-host interaction. Effector proteins of pathogenic bacteria invade the host cell through type III secretion system (T3SS) and disrupt the cellular signaling mechanism. Previous studies demonstrated that thiol peroxidase, Tpx, is functional in the assembly of T3SS and its inhibition by salicylidene acylhydrazides prevents the secretion of pathogenic effectors. The aim of this thesis study is to carry out virtual screening and molecular docking to identify potential Tpx inhibitors. Both ligand-based and structure-based pharmacophore models were developed to screen the ZINC database of 500,000 compounds based on 3D similarity to the chosen pharmacophore hypotheses. Molecular docking of filtered 10,000 compounds was performed with Glide module of Maestro molecular modeling package to predict binding modes of the ligands. Top scoring hits were further analyzed by efficiency indices, strain energy corrections, and their absorption, distribution, metabolism and excretion (ADME) and druglikeness properties. Common scaffolds of the selected clusters were used for substructure search and 31 hits with high docking scores, fitness values to the hypothesis and binding efficiency index (BEI), low molecular weight and high percentage of human oral absorption (HOA) values were obtained. As a final outcome, eight ligands with different chemotypes including n-benzyl formamide, 1,2-dimethoxybenzene and phenoxyethanol were proposed as potential inhibitors of Tpx after induced fit docking and selectivity analysis.
