Subtractive Genome Analysis for Identification and Characterization of Novel Drug Targets in the Streptococcus pneumoniae by Using In-silico Approach

This is the authors' abstract. We don't add key points for this paper.

As per WHO, the pneumococcus causes one million fatalities each year because of their underdeveloped immune systems, children are the most vulnerable to pneumococcal infections. The rise of S. pneumoniae resistance to antibiotics is causing widespread alarm all across the globe. Since the last couple of years, a recently developed technique is being used to overcome resistant pathogens. One of these is the computational subtractive genomics technique, in which the bacterial pathogen full proteins are effectively decreased to a limited amount of probable therapeutic targets. The procedures employed in this strategy are to locate human non-homologs targets, proteins that are vital to the illness producing agent, and participation of the identified proteins in pathogen metabolic pathways that are required for bacterial survival. In this work, we applied computational subtractive genomics on the proteins of the S. pneumonia strain D39 and came up with three cytoplasmic proteins that can serve as a promising candidate for novel drug to control the pathogenicity caused by S. pneumoniae.