Computational structure-guided approach to simulate delamanid and pretomanid binding to mycobacterial F420 redox cycling proteins: identification of key determinants of resistance.

Abstract

The recently approved delamanid (DLM) and pretomanid (PTM) improved the existing options to treat multidrug-resistant tuberculosis (MDR-TB). However, the high spontaneous mutation rates in mycobacterial F420 genes ddn, fgd1, fbiA, fbiB, fbiC, and fbiD create a bottleneck to successful anti-TB treatments. Of known mutations, identifying the therapeutically relevant ones is a prerequisite for understanding the drug resistance mechanism. Here, we applied a multistep computational pipeline to rank the mutations in F420 genes associated with DLM/PTM resistance. The DLM-/PTM-resistant protein mutants were built and simulated their innate sensitivity towards the drugs. The molecular dynamics (MD) and molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) calculations quantified the effect of key mutations on drug union. The dynamic cross-correlated map (DCCM) and principal component analysis (PCA) showed a substantial link between the drug binding region and other sections in the mutants, hints to their potential role as an allosteric site. Also, the alterations induced conformationally unstable proteins with decreased DLM/PTM affinity. These investigations highlighted the DLM-tolerant G53D and Y65S and PTM-resilient Y133M (Ddn), L308P (FbiA), and C562W (FbiC) as candidate loss-of-function mutants of progressive research. The present results and interpretations could supply vital clues for protein engineering and drug development.