Identification of novel selective Mtb-DHFR inhibitors as antitubercular agents through structure-based computational techniques.

Inhibition of dihydrofolate reductase from Mycobacterium tuberculosis-dihydrofolate reductase (Mtb-DHFR) has emerged as a promising approach for the treatment of tuberculosis. To identify novel Mtb-DHFR inhibitors, structure-based virtual screening (SBVS) of the Molecular Diversity Preservation International (MolMall) database was performed using Glide against the Mtb-DHFR and h-DHFR enzymes. On the basis of SBVS, receptor fit, drug-like filters, and ADMET (absorption, distribution, metabolism, excretion, and toxicity) analysis, 16 hits were selected and tested for their antitubercular activity against the H37RV strain of M. tuberculosis. Five compounds showed promising activity with compounds 11436 and 15275 as the most potent hits with IC50 values of 0.65 and 12.51 mu M, respectively, against the H37RV strain of M. tuberculosis. The two compounds were further tested in the Mtb-DHFR and h-DHFR enzymatic assay for selectivity and were found to be three- to eight-fold selective towards Mtb-DHFR over h-DHFR with minimum inhibitory concentration values of 5.50, 73.89 mu M and 42.00, 263.00 mu M, respectively. In silico simulation studies also supported the stability of the protein-ligand complex formation. The present study demonstrates the successful utilization of in silico SBVS tools for the identification of novel and potential Mtb-DHFR inhibitors and compound 11436 ((2,4-dihydroxyphenyl)(3,4,5-trihydroxyphenyl)methanone) as a potential lead for the development of novel Mtb-DHFR inhibitors.