RESUMEN
Antibiotic resistance is a major threat to global health; this problem can be addressed by the development of new antibacterial agents to keep pace with the evolutionary adaptation of pathogens. Computational approaches are essential tools to this end since their application enables fast and early strategical decisions in the drug development process. We present a rational design approach, in which acylide antibiotics were screened based on computational predictions of solubility, membrane permeability, and binding affinity toward the ribosome. To assess our design strategy, we tested all candidates for in vitro inhibitory activity and then evaluated them in vivo with several antibiotic-resistant strains to determine minimal inhibitory concentrations. The predicted best candidate is synthetically more accessible, exhibits higher solubility and binding affinity to the ribosome, and is up to 56 times more active against resistant pathogens than telithromycin. Notably, the best compounds designed by us show activity, especially when combined with the membrane-weakening drug colistin, against Acinetobacter baumanii, Pseudomonas aeruginosa, and Escherichia coli, which are the three most critical targets from the priority list of pathogens of the World Health Organization.
Asunto(s)
Antibacterianos/farmacología , Bacterias/efectos de los fármacos , Farmacorresistencia Bacteriana Múltiple/efectos de los fármacos , Macrólidos/farmacología , Colistina/farmacología , Pruebas de Sensibilidad Microbiana/métodosRESUMEN
The concept of combinatorial biosynthesis promises access to compound libraries based on privileged natural scaffolds. Ever since the elucidation of the biosynthetic pathway towards the antibiotic erythromycin A in 1990, the predictable manipulation of type I polyketide synthase megaenzymes was investigated. However, this goal was rarely reached beyond simplified model systems. In this study, we identify the intermediates in the biosynthesis of the polyether monensin and numerous mutated variants using a targeted metabolomics approach. We investigate the biosynthetic flow of intermediates and use the experimental setup to reveal the presence of selectivity filters in polyketide synthases. These obstruct the processing of non-native intermediates in the enzymatic assembly line. Thereby we question the concept of a truly modular organization of polyketide synthases and highlight obstacles in substrate channeling along the cascade. In the search for the molecular origin of a selectivity filter, we investigate the role of different thioesterases in the monensin gene cluster and the connection between ketosynthase sequence motifs and incoming substrate structures. Furthermore, we demonstrate that the selectivity filters do not apply to new-to-nature side-chains in nascent polyketides, showing that the acceptance of these is not generally limited by downstream modules.