Anti-mycobacterial activity evaluation of designed peptides: cryptic and database filtering based approach.

Worldwide, TB is one of the deadly airborne diseases, which accounts for 10.4 million deaths annually. Serious toxicity issue, prolonged treatment regimens of the current drugs, rise in multidrug-resistant strains, and the unique defensive mechanism makes the development of novel therapeutic molecules against Mycobacterium tuberculosis (MT) an urgent need. As MT has a lengthy latent phase and unique cell wall architecture, a reasonable approach is needed to find molecules having a different killing mechanism rather than traditional approaches. Host defence peptides (HDPs) will be the most promising alternative, potential therapeutic candidates as they target the microbial membrane in particular and are an essential part of the innate immunity of humans. This works demonstrates the utility of "Database filtering" and three-dimensional (3D) modelling approach in finding novel AMPs with appreciable activity towards MT. Results of this study indicate that peptides with 70% hydrophobicity, but without hydrophobicity patches (> 4 hydrophobic amino acids in series) and charge of + 4 or + 5 are most likely to be good anti-tubercular candidates.