Arnab Sen
NBU Bioinformatics Facility, Department of Botany, University of North Bengal, Siliguri 734013, India.

ABSTRACT

The genus Mycobacterium includes pathogen known to causes some deadliest diseases of Mankind such as Tuberculosis and Leprosy. Availability of complete genome sequence and annotation of the Mycobacterium genome has provided new information related to proteins involve in extracellular secretion. Secreted proteins play an important part in the pathogenicity of Mycobacterium and are of particularly important for vaccine development because they are often immunogenic and have potential to be recognized early in infection. Elucidation of protein secretion in Mycobacterium could provide new insights into their virulence factor and provide a source of proteins with potential for vaccine. Here we have attempted to construct a database named “MycoSec”, which provides a complete repository of computationally predicted signal peptides in the 21 different strains of Mycobacterium genome currently available in public domain. The database also provides comprehensive information about the functional role, expression pattern, COG distribution and cleavage site pattern of the secretory proteins found across the Mycobacterium. The database “MycoSec” have been designed by Adobe Dreamweaver software using HTML code. The data were collected by the use of signal peptide prediction algorithm like SignalP along with TMHMM server v.2.0 for prediction of transmembrane helices in protein sequences. For prediction of TAT-type and LIPO-type of signal peptide the servers TATFIND 1.4 and PredLipo was used respectively. MycoSec database provides users with an easy-to-use web interface to search for desired signal peptide data. This data can be utilized by the microbiologist, molecular biologist and researchers engaged in the study of pathogenesis, drug designing and vaccine development. Read more…