Structure-based virtual screening of essential Mycobacterium tuberculosis enzymes AspS and KatG for potential inhibitors

基于结构的结核分枝杆菌必需酶AspS和KatG的潜在抑制剂虚拟筛选

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Abstract

Mycobacterium tuberculosis (TB) is a leading global cause of disease-related death. Recent works have studied metabolic pathways of the mycobacterium, highlighting essential enzymes to target via competitive inhibition through computational molecular modeling to suppress the organism's life cycle. We used the Protein Databank (PDB), the UniProt Knowledgebase and the iDock server in this study. In vitro toxicity screening and pharmacokinetic properties were assessed to determine potential ligand safety and drug properties. Our results have revealed five and nine potential ligands for the enzymes AspS and KatG respectively. The KatG active site has displayed binding affinities of -13.443 to -12.895 kcal/mol, while AspS ligands range from -6.580 to -6.490kcal/mol. The intermolecular forces responsible for the differing binding affinities of each enzyme are primarily Coulombic interactions for AspS, versus Coulombic and extensive hydrogen bonding interactions in KatG.

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