Shape-based virtual screening, docking, and molecular dynamics simulations to identifyMtb-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.

Computational Approaches in Preclinical Studies on Drug Discovery and Development

“…However, more models should be constructed to cover more diverse chemical space if different shapes are available (Perez-Nueno and Ritchie, 2011 ), particularly for highly flexible proteins. Some studies using the shape-focused method have been reported in recent years (Reddy et al, 2013 ; Chen et al, 2015 ; Kumar et al, 2015 ; Prabhu and Singh, 2019 ). For example, Chen et al ( 2015 ) presented a shape-based virtual screening to find new cores for the design of acetylcholinesterase (AChE) inhibitors.…”

Asymmetric Synthesis of Chiral Amino Carboxylic‐Phosphonic Acid Derivatives

“…The Cox's group was particularly active in the design of phosphonic aspartic derivatives including phosphoramidates, phosphonates (see 2.5), monofluorophosphonates (see 3.1.3), and difluorophosphonates [160] . Aspartyl β‐difluorophosphonate (β‐AFP) of 218 , was identified as a lead compound and used to understand the molecular recognition interactions with ASA‐DH [161–162] . The synthesis of 218 was reported via different routes that all exploited aspartic acid as starting chiral substrate.…”

Shape based virtual screening and molecular docking towards designing novel pancreatic lipase inhibitors

“…This was carried out using Phase shape screening application from the Schrodinger suite [ 10 ]. This technique employs the methodology of screening of database based on shape and electrostatic properties of the known molecule to retract similar type of molecules from natural molecule database [ 11 ]. The screened molecules were predicted to show similar kind of binding modes with active site residues and in turn may produce similar type of activity.…”