Identification of Mycobacterium tuberculosis transcriptional repressor EthR inhibitors: Shape-based search and machine learning studies.

ABSTRACT

Tuberculosis has been a challenge to the world since prehistoric times, and with the advent of drug-resistant strains, it has become more challenging to treat this infection. Ethionamide (ETH), a second-line drug, acts as a prodrug and targets mycolic acid synthesis by targeting the enoyl-acyl carrier protein reductase (InhA) enzyme. Mycobacterium tuberculosis (Mtb) EthR is an ethA gene repressor required to activate prodrug ETH. Recent studies suggest targeting the EthR could lead to newer drug molecules that would help better activate the ETH or complement this process. In this report, we have attempted and successfully identified three new molecules from the drug repurposing library that can target EthR protein and function as ETH boosters. These molecules were obtained after rigorous filtering of the database for their physicochemical, toxicological properties and safety. The molecular docking, molecular dynamics simulations and binding energy studies yielded three compounds, Ethyl (2-amino-4-((4-fluorobenzyl)amino)phenyl)carbamate) (L1), 2-((2,2-Difluorobenzo [d] [1,3]dioxol-5-yl)amino)-2-oxoethyl (E)-3-(5-bromofuran-2-yl)acrylate (L2), and N-(2,3-Dihydrobenzo [b] [1,4]dioxin-6-yl)-4-(2-((4-fluorophenyl)amino)-2-oxoethoxy)-3-methoxy benzamide (L3) are potential EthR inhibitors. We applied machine learning methods to evaluate these molecules for toxicity and synthesisability, suggesting safety and ease of synthesis for these molecules. These molecules are known for other pharmacological activities and can be repurposed faster as adjuvant therapy for tuberculosis.