title: Shape-based virtual screening, docking, and molecular dynamics simulations to identify Mtb-ASADH inhibitors.
abstract: Aspartate β-semialdehyde dehydrogenase (ASADH) is a key enzyme for the biosynthesis of essential amino acids and several important metabolites in microbes. Inhibition of ASADH enzyme is a promising drug target strategy against Mycobacterium tuberculosis (Mtb). In this work, in silico approach was used to identify potent inhibitors of Mtb-ASADH. Aspartyl β-difluorophosphonate (β-AFP), a known lead compound, was used to understand the molecular recognition interactions (using molecular docking and molecular dynamics analysis). This analysis helped in validating the computational protocol and established the participation of Arg99, Glu224, Cys130, Arg249, and His256 amino acids as the key amino acids in stabilizing ligand-enzyme interactions for effective binding, an essential feature is H-bonding interactions with the two arginyl residues at the two ends of the ligand. Best binding conformation of β-AFP was selected as a template for shape-based virtual screening (ZINC and NCI databases) to identify compounds that competitively inhibit the Mtb-ASADH. The top rank hits were further subjected to ADME and toxicity filters. Final filter was based on molecular docking analysis. Each screened molecule carries the characteristics of the highly electronegative groups on both sides separated by an average distance of 6 Å. Finally, the best predicted 20 compounds exhibited minimum three H-bonding interactions with Arg99 and Arg249. These identified hits can be further used for designing the more potent inhibitors against ASADH family. MD simulations were also performed on two selected compounds (NSC4862 and ZINC02534243) for further validation. During the MD simulations, both compounds showed same H-bonding interactions and remained bound to key active residues of Mtb-ASADH.
authors.affiliation: a Department of Pharmacoinformatics , National Institute of Pharmaceutical Education and Research (NIPER) , Sector-67, S.A.S. Nagar 160 062 , Punjab , India.
authors.forename: Rajender
authors.initials: R
authors.lastname: Kumar
authors.forename: Prabha
authors.initials: P
authors.lastname: Garg
authors.forename: P V
authors.initials: PV
authors.lastname: Bharatam
mesh_terms: D001223:Aspartate-Semialdehyde Dehydrogenase / Q000037:antagonists & inhibitors / Q000737:chemistry* / Q000378:metabolism; D001426:Bacterial Proteins / Q000037:antagonists & inhibitors / Q000737:chemistry* / Q000378:metabolism; D001665:Binding Sites; D003198:Computer Simulation; D004791:Enzyme Inhibitors / Q000737:chemistry* / Q000378:metabolism / Q000494:pharmacology; D006860:Hydrogen Bonding; D008024:Ligands; D062105:Molecular Docking Simulation; D056004:Molecular Dynamics Simulation; D015394:Molecular Structure; D009169:Mycobacterium tuberculosis / Q000187:drug effects / Q000201:enzymology; D063065:Organophosphonates / Q000737:chemistry / Q000378:metabolism / Q000494:pharmacology; D011485:Protein Binding; D017434:Protein Structure, Tertiary; D013329:Structure-Activity Relationship
chemical_list: D001426:Bacterial Proteins; D004791:Enzyme Inhibitors; D008024:Ligands; D063065:Organophosphonates; D001223:Aspartate-Semialdehyde Dehydrogenase
keywords: MD simulations; aspartate β-semialdehyde dehydrogenase; molecular docking; molecular recognition interactions; shape-based virtual screening