Harnessing computational and experimental approaches to identify potent hits against Leishmania donovani sterol C-24 methyltransferase from ChemBridge library.

Abstract

Leishmaniasis is a neglected tropical disease and is one of the major causes of mortality in poverty-stricken areas. A limited chemotherapeutics arsenal is available to tackle this deadly infection. Thus, identifying novel potent scaffolds using innovative strategies is the need of the hour. High-throughput screening (HTS) is a critical technique that can accelerate the process of drug discovery by evaluating millions of drug-like molecules using various automation tools and biological assays. In the present study, we have employed the HTS strategy to identify potent hits against Leishmania donovani sterol C-24 methyltransferase (LdSMT) from the in-house ChemBridge library. Firstly, a robust dataset was prepared with previously reported sterol C-24 methyltransferase inhibitors, belonging to diverse structural classes. Then, ligand-based virtual screening using similarity search was performed to screen the ChemBridge library having ∼20,000 molecules. This computational approach yielded 81 candidate compounds, which were selected for further molecular docking and biological evaluation. Anti-leishmanial assays revealed that out of 81 molecules, seven showed potential parasitic killing. Three molecules namely IIIM-CB-14, IIIM-CB-29, and IIIM-CB-45 were the most potent ones with 50% inhibitory concentration (IC₅₀) of 5.76, 8.08, and 10.64 µg/mL, respectively. SEM analyses suggest that these potent hits cause considerable morphological alterations. ADME studies of the potent hit molecules indicate that all the hits have considerable drug-likeness properties. Further, molecular dynamics studies were also performed to check the stable confirmation of LdSMT protein with the top two hits (IIIM-CB-14 and IIIM-CB-45). Thus, the present study harnesses computational and experimental approaches to unravel potent anti-leishmanial scaffolds.