Using Virtual Screening to Identify Novel Inhibitors for Enoyl‐Acyl Carrier Protein Reductase in Mycobacterium tuberculosis

Mycobacterium tuberculosis causes the highly infectious disease Tuberculosis, an airborne illness primarily affecting the lung which still remains in the top 10 causes of death worldwide, largely due to recent antibiotic resistant tuberculosis strains. InhA, the enoyl‐acyl carrier protein reductase, is an advantageous drug target due to its essentiality in M. tuberculosis, as it catalyzes the enoyl‐acyl carrier protein double bond reduction. This reaction is an essential precursor to create mycolic acids for cell wall fatty acid biosynthesis. Although there are current antibiotics for this enzyme, many of these once‐effective treatments are losing efficacy to the antibiotic‐resistant strains, creating a need for novel InhA inhibitors. Using an MtInhA crystallography structure (PDB 4DRE), numerous large libraries of compounds were virtually screened against InhA using the virtual screening program GOLD, Genetic Optimization for Ligand Docking (CCDC). This program uses a genetic algorithm to predict and quantify the binding interactions to estimate the ligand's total binding energy with a relative binding score for each. First, control ligands were docked to validate the GOLD software for compounds known to inhibit MtInhA. After a preliminary screening of tens of thousands of chemical compounds from various libraries was run with a low thoroughness to quickly screen out low‐probability hits for MtInhA, the top ten percent of ligands were then screened with higher thoroughness in GOLD, along with additional screening in the programs VINA and ICM. Supplemental filtering using Lipinski's criteria and examination of the best‐scoring ligands in the visualization program PyMOL further narrowed down the list. The majority of these top hits were found in the chemical library Novacore, along with a few ligands in the CBZinc library. Novacore's library greatly exceeded the best control ligand scoring 110.93, with scores ranging from 160.09 to 64.4. CBZinc's scores produced a much wider range of scores, from 110.47 to 24.75. These libraries have starkly different binding methods for MtInhA, with Novacore's ligands creating strong binding through a few strong interactions to a small portion of the active site, while CBZinc's ligands create strong binding through numerous interactions which span the entire active site. While the conformations differ greatly, these compounds are noteworthy nonetheless and should be further tested for MtInhA inhibition through wet‐lab research.