SecretoMyc, a web-based database on mycobacteria secreted proteins and structure-based homology identification using bio-informatics tools

Abstract

To better understand the interaction between the host and the Mycobacterium tuberculosis pathogen, it is critical to identify its potential secreted proteins. While various experimental methods have been successful in identifying proteins under specific culture conditions, they have not provided a comprehensive characterisation of the secreted proteome. We utilized a combination of bioinformatics servers and in-house software to identify all potentially secreted proteins from six mycobacterial genomes through the three secretion systems: SEC, TAT, and T7SS. The results are presented in a database that can be crossed referenced to selected proteomics and transcriptomics studies (https://secretomyc.cbs.cnrs.fr). In addition, thanks to the recent availability of Alphafold models, we developed a tool in order to identify the structural homologues among the mycobacterial genomes.