A Molecular-Dynamics-Simulation-Based Drug Discovery Platform for Pathogenic Bacteria

Abstract

This dissertation presents an in-silico molecular-dynamic-simulation-based drug discovery tool and its utility to find inhibitors for pathogenic microorganisms. Specifically, the applicability of the tool has been demonstrated using two pathogenic bacteria, enterohemorrhagic E. coli subtype O104:H4 and Candidatus Liberibacter spp. First, a pharmacophore modeling and refinement tool ELIXIR-A (Enhanced Ligand Exploration and Interaction Recognition Algorithm) was developed using Python programming language. The tool helps refine pharmacophores generated from multiple ligand-receptor interaction points using the Iterative Closest Point (ICP) variant algorithm. ELIXIR-A identified six potential inhibitory compounds for the E. coli O104: H4 βlactamase receptor protein. One non-β-lactam compound showed good inhibitory activity of E. coli O104: H4 on Kirby Bauer disk diffusion susceptibility testing. These results suggested that this novel non-β-lactam compound could be used as a lead compound to develop potent drugs targeting β-lactam-resistant Gram-negative bacterial strains. Then the tool was applied to screen inhibitors targetting serine tyrosine phosphatase, a putative virulence protein of Candidatus Liberibacter spp. The in silico analysis followed by in vitro binding kinetic studies resulted in two small molecules (G6P3510 and G6P6373) that were further verified by in planta studies (performed elsewhere). Finally, a computational modeling strategy was employed to identify antimicrobial peptides (AMPs) that could be used as potential bacterial inhibitors via blocking TolC, an essential protein in the efflux pump of the Type 1 Secretion System (T1SS) of Candidatus Liberibacter asiaticus (CLas). Multiple in silico approaches such as homology modeling, molecular docking, molecular dynamics simulations, Molecular Mechanics/Generalized Born Surface Area (MM-GBSA) calculations, and Principal Component Analysis (PCA) were used to identify potential AMPs against the outer membrane protein TolC. The results (including in vitro studies with surrogate bacteria conducted elsewhere) suggested that the screened AMPs can be used as inhibitors targeting the TolC receptor.