Combined Bioinformatic and Rational Design Approach To Develop Antimicrobial Peptides against Mycobacterium tuberculosis

Drug-resistant pathogens are a growing problem, and novel strategies are needed to combat this threat. Among the most significant of these resistant pathogens is Mycobacterium tuberculosis, which is an unusually difficult microbial target due to its complex membrane. Here, we design peptides for specific activity against M. tuberculosis using a combination of "database filtering" bioinformatics, protein engineering, and de novo design. Several variants of these peptides are structurally characterized to validate the design process. The designed peptides exhibit potent activity (MIC values as low as 4 μM) against M. tuberculosis and also exhibit broad activity against a host of other clinically relevant pathogenic bacteria such as Gram-positive bacteria (Streptococcus) and Gram-negative bacteria (Escherichia coli). They also display excellent selectivity, with low cytotoxicity against cultured macrophages and lung epithelial cells. These first-generation antimicrobial peptides serve as a platform for the design of antibiotics and for investigating structure-activity relationships in the context of the M. tuberculosis membrane. The antimicrobial peptide design strategy is expected to be generalizable for any pathogen for which an activity database can be created.