In silico discovery of potential novel anti-tuberculosis drug candidates from phytoconstituents of Chlorophytum borivilianum and Asparagus racemosus.

Abstract

Tuberculosis (TB), caused by Mycobacterium tuberculosis, remains a significant global health challenge, particularly in developing nations. Side effects and increasing drug resistance often limit conventional pharmaceutical treatments for TB. This has highlighted the urgent need for novel therapeutic agents. Traditional medicine offers a promising avenue for discovering effective and safer alternatives. In silico approaches play a crucial role in pharmaceutical research by facilitating the identification of novel therapeutic compounds. These techniques are widely employed to explore potential treatments for diverse diseases. This study aims to identify lead molecules with anti-tuberculosis potential that could be further studied for their inhibitory potential and possible optimization for the treatment of tuberculosis. Chlorophytum borivilianum and Asparagus racemosus were selected for their diverse phytochemical profiles and proven pharmacological activities, including significant antimicrobial properties that make them promising candidates for in silico exploration of anti-tuberculosis therapeutics. The drug-likeness and pharmacokinetics of phytochemicals from the plants were evaluated using Lipinski's rule of five, and ADMET predictions. Phytochemicals meeting these criteria were subjected to molecular docking against Mycobacterium tuberculosis targets: CYP51, InhA, and EthR, using Vina (PyRx)platform to calculate binding affinities and assess interaction stability. Molecular dynamics simulations (100 ns) were performed to validate the stability of the docked complexes, focusing on key parameters such as RMSD, RMSF, and Rg. This approach identified hecogenin, sarsasapogenin, and isoflavone as potential inhibitors of CYP51 with high binding affinities and stable interactions, suggesting their promise as lead compounds for tuberculosis treatment.