Title: Identification of natural FtsZ inhibitors through computational approaches to combat drug-resistant tuberculosis

Abstract

The Mycobacterial cell division protein FtsZ is a promising target for addressing multidrug-resistant tuberculosis (MDR-TB). We employed computational strategies to screen a large library of natural compounds for FtsZ inhibitors. Our virtual screening process involved high-throughput docking simulations, standard precision and extra precision docking, and in silico ADME analysis to evaluate the drug-likeness of selected compounds. Four promising ligands were identified, with two emerging as potential FtsZ ligands: CID_5487121 (Capuramycin) and CID_71452248 (Deacetylkirschsteinin). These molecules exhibited high docking affinities and consistent behavior throughout molecular dynamics simulations. Our findings demonstrate the potential of these compounds as leads for further experimental validation and development of novel therapeutics against MDR-TB. Additionally, the molecular dynamics simulations provided insights into the stability and interaction patterns of these compounds with the FtsZ protein, highlighting their potential as strong inhibitors. The comprehensive ADME analysis ensured that these compounds possess favorable drug-like properties, making them viable candidates for further development.