TB Research

In-silico Evaluation of Bioactive Compounds from Medicinal Plants as Promising Inhibitory Agents against Mycobacterium tuberculosis dihydrofolate reductase

Olatunji K Toyosi, Peters Oladosu, Kolawole O. Matthew

International Journal of Research and Innovation in Applied Science · 2025-01

Abstract

Tuberculosis (TB) is one of the major public health challenges around the globe. Targeting dihydrofolate reductase (DHFR), a key enzyme involved in folate metabolism, is a promising path to discovering an effective TB treatment. This study assessed the molecular docking of eight bioactive compounds from two medicinal plants (Berlinia grandiflora and Senna occidentalis) to the active site of Mycobacterium tuberculosis dihydrofolate reductase (MtbDHFR) (6VVB.pdb). Molecular docking and computational tools were used to evaluate the binding energies and interactions with MtbDHFR active site. The chemical structures of the bioactive compounds and the 3D structure of the target protein were retrieved from the PubChem database and Research Collaboratory for Structural Bioinformatics (RCSB) Protein Data Bank, respectively. The binding energy of the bioactive compounds ranged between -4.468 to -6.146 kcal/mol, while the reference drug exhibited a binding energy of –5.392 kcal/mol. Interestingly, five compounds (4 to 8) showed stronger binding energies (-5.485 to -6.146 kcal/mol) than the reference drug, depicting them as promising antituberculosis agents. Among them, L-(+)-ascorbic acid 2, 6-dihexadecanoate exhibited the highest binding energy of -6.146 kcal/mol. Additionally, the compounds exhibited hydrogen bonds and hydrophobic interactions with the active site residues of the protein. Overall, the results indicate that these bioactive compounds exhibited favorable docking interactions with the target protein, highlighting their potential as therapeutic agents for TB drug discovery.

MeSH terms

  • In silico
  • Dihydrofolate reductase
  • Mycobacterium tuberculosis
  • Inhibitory postsynaptic potential
  • Tuberculosis
  • Pharmacology
  • Biology
  • Chemistry
  • Computational biology
  • Microbiology