title: Identification of potential Tpx inhibitors against pathogen-host interactions.
abstract: Yersinia organisms cause many infectious diseases by invading human cells and delivering their virulence factors via the type three secretion system (T3SS). One alternative strategy in the fight against these pathogenic organisms is to interfere with their T3SS. 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. In this study, the aim was to identify potential inhibitors of Tpx using an integrated approach starting with high throughput virtual screening and ending with molecular dynamics simulations of selected ligands. Virtual screening of ZINC database of 500,000 compounds via ligand-based and structure-based pharmacophore models retrieved 10,000 hits. The structure-based pharmacophore model was validated using high-throughput virtual screening (HTVS). After multistep docking (SP and XP), common scaffolds were used to find common substructures and the ligand binding poses were optimized using induced fit docking. The stability of the protein-ligand complex was examined with molecular dynamics simulations and the binding free energy of the complex was calculated. As a final outcome eight compounds with different chemotypes were proposed as potential inhibitors for Tpx. The eight ligands identified by a detailed virtual screening protocol can serve as leads in future drug design efforts against the destructive actions of pathogenic bacteria.
authors.affiliation: Chemical Engineering Department, Bogazici University, Bebek, 34342 Istanbul, Turkey.
authors.forename: Utku
authors.initials: U
authors.lastname: Deniz
authors.affiliation: Chemical Engineering Department, Bogazici University, Bebek, 34342 Istanbul, Turkey.
authors.forename: Kutlu O
authors.initials: KO
authors.lastname: Ulgen
authors.affiliation: Chemical Engineering Department, Bogazici University, Bebek, 34342 Istanbul, Turkey. Electronic address: elif.ozkirimli@boun.edu.tr.
authors.forename: Elif
authors.initials: E
authors.lastname: Ozkirimli
mesh_terms: D004791:Enzyme Inhibitors / Q000737:chemistry / Q000378:metabolism*; D054884:Host-Pathogen Interactions; D008024:Ligands; D062105:Molecular Docking Simulation; D056004:Molecular Dynamics Simulation; D010544:Peroxidases / Q000037:antagonists & inhibitors* / Q000737:chemistry / Q000378:metabolism*; D011485:Protein Binding; D011487:Protein Conformation; D015011:Yersinia pseudotuberculosis / Q000201:enzymology / Q000502:physiology
chemical_list: D004791:Enzyme Inhibitors; D008024:Ligands; D010544:Peroxidases
keywords: Efficiency index; Molecular docking; Substructure search; Tpx; Virtual screening