In Silico Approach: Anti-Tuberculosis Activity of Caespitate in the H37Rv Strain

• Published in: Current issues in molecular biology Vol. 46; no. 7; pp. 6489 - 6507
• Main Authors: Moreno-Ceballos, Andrea, Caballero, Norma A, Castro, María Eugenia, Perez-Aguilar, Jose Manuel, Mammino, Liliana, Melendez, Francisco J
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 01-07-2024
• Subjects: antituberculosis activity; caespitate; H37Rv strain; MM/GBSA; molecular docking; antituberculosis activity; molecular docking; MM/GBSA; H37Rv strain; caespitate
• ISSN: 1467-3045; 1467-3037; 1467-3045
• DOI: 10.3390/cimb46070387

Tuberculosis is a highly lethal bacterial disease worldwide caused by
(
). Caespitate is a phytochemical isolated from
, a plant used in African traditional medicine that shows anti-tubercular activity, but its mode of action remains unknown. It is suggested that there are four potential targets in
, specifically in the H37Rv strain: InhA, MabA, and UGM, enzymes involved in the formation of
's cell wall, and PanK, which plays a role in cell growth. Two caespitate conformational structures from DFT conformational analysis in the gas phase (GC) and in solution with DMSO (CS) were selected. Molecular docking calculations, MM/GBSA analysis, and ADME parameter evaluations were performed. The docking results suggest that CS is the preferred caespitate conformation when interacting with PanK and UGM. In both cases, the two intramolecular hydrogen bonds characteristic of caespitate's molecular structure were maintained to achieve the most stable complexes. The MM/GBSA study confirmed that PanK/caespitate and UGM/caespitate were the most stable complexes. Caespitate showed favorable pharmacokinetic characteristics, suggesting rapid absorption, permeability, and high bioavailability. Additionally, it is proposed that caespitate may exhibit antibacterial and antimonial activity. This research lays the foundation for the design of anti-tuberculosis drugs from natural sources, especially by identifying potential drug targets in
.