Integrated in silico approaches for the identification of promising dual-target inhibitors of Mycobacterium tuberculosis DprE1 and InhA enzymes
Abstract
Tuberculosis (TB) remains a major global health challenge, exacerbated by the rapid emergence of drug-resistant Mycobacterium tuberculosis ( Mtb ) strains that compromise the efficacy of current therapies. The discovery of novel multi-target anti-tubercular agents from diverse chemical libraries using integrated computer-aided drug design approaches is therefore urgently needed. In this study, we investigated two essential anti-TB targets involved in cell wall and mycolic acid biosynthesis, namely DprE1 and InhA. A dataset of 55 reported morpholino-pyrimidine derivatives was used to develop robust 3D-pharmacophore (PH4) and 3D-QSAR models for DprE1 inhibition. The best-performing pharmacophore hypothesis, AHHHR_1, was employed to virtually screen the COCONUT, ChEMBL, and ANPDB databases. Compounds with high Phase scores (>1.900) were further evaluated through molecular docking against DprE1 (PDB ID: 4KW5 ), and the top-ranked candidates were subsequently screened against InhA (PDB ID: 5G0V ) to identify potential dual-target inhibitors. Binding affinities were subsequently assessed using Prime/MM-GBSA calculations. The inhibitory activities of 28 provisional hit compounds were predicted using a validated QSAR model (R² = 0.96, Pearson’s r = 0.95, Q² = 0.79). Induced-fit docking and 200 ns molecular dynamics simulations demonstrated stable interactions of the top dual-target hits with both proteins. In addition, DFT calculations at the B3LYP/6-31+G(d,p) level, ADMET…
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