Novel Mycosin Protease MycP₁ Inhibitors Identified by Virtual Screening and 4D Fingerprints

Abstract

The rise of drug-resistant Mycobacterium tuberculosis lends urgency to the need for new drugs for the treatment of tuberculosis (TB). The identification of a serine protease, mycosin protease-1 (MycP1), as the crucial agent in hydrolyzing the virulence factor, ESX-secretion-associated protein B (EspB), potentially opens the door to new tuberculosis treatment options. Using the crystal structure of mycobacterial MycP1 in the apo form, we performed an iterative ligand- and structure-based virtual screening (VS) strategy to identify novel, nonpeptide, small-molecule inhibitors against MycP1 protease. Screening of ∼485 000 ligands from databases at the Genomics Research Institute (GRI) at the University of Cincinnati and the National Cancer Institute (NCI) using our VS approach, which integrated a pharmacophore model and consensus molecular shape patterns of active ligands (4D fingerprints), identified 81 putative inhibitors, and in vitro testing subsequently confirmed two of them as active inhibitors. Thereafter, the lead structures of each VS round were used to generate a new 4D fingerprint that enabled virtual rescreening of the chemical libraries. Finally, the iterative process identified a number of diverse scaffolds as lead compounds that were tested and found to have micromolar IC50 values against the MycP1 target. This study validated the efficiency of the SABRE 4D fingerprints as a means of identifying novel lead compounds in each screening round of the databases. Together, these results underscored the value of using a combination of in silico iterative ligand- and structure-based virtual screening of chemical libraries with experimental validation for the identification of promising structural scaffolds, such as the MycP1 inhibitors.

Peptide Inhibitors Targeting the Neisseria gonorrhoeae Pivotal Anaerobic Respiration Factor AniA

“…The pose ensemble was filtered to reject poses that did not have sufficient shape complementarity with the active site of the protein. In separate docking runs, the binding poses of the ligand structure were refined by MD simulations followed by free energy calculations using the Sander module from the Amber12 package (91) as previously described (92)(93)(94)(95). The AniA-peptide binding complex was neutralized by adding appropriate counterions and was solvated in a rectangular box of TIP3P (transferable intermolecular potential with 3-points model) water molecules with a minimum solute wall distance of 10 Å (96).…”

Hierarchical virtual screening approaches in small molecule drug discovery

“…Drug-likeness filter and molecular docking were used to further prioritize these compounds. In another study, Hamza et al [110] employed a VS protocol that integrated a pharmacophore model, consensus molecular shape patterns of active ligands and molecular docking to identify inhibitors with lM potency against mycobacterial mycosin protease-1. Recently, our group has identified 1,2,5-oxadiazoles as novel inhibitors of SUMO specific protease 2 (SENP2) utilizing a VS protocol that combines shape and electrostatic potential based similarity searches with molecular docking [108].…”

Assessing the progress of Mycobacterium tuberculosis H37Rv structural genomics

“…Of 204 proteins, 18 have not been analysed by TuberQ as yet, one is listed as non-druggable, 16 as poorly druggable, 43 as druggable, and 126 as highly druggable. While this data has been used to develop inhibitors (23,24), no anti-TB drugs currently in clinical trials appears to have been designed from protein structural data (25,26). Instead, drugs were mainly discovered through phenotypic screening of bacteria cells exposed to various compounds (27).…”