Integrated bioinformatics based subtractive genomics approach to decipher the therapeutic function of hypothetical proteins from Salmonella typhi XDR H-58 strain.

The efficacy of drugs against Salmonella infection have compromised due to emerging XDR H58 strain. There is a dire need to find novel antimicrobial drug targets as well as drug candidates to cure by the XDR strain of Salmonella. It is observed that the complete genome sequence of the XDR H58 strain contains a large number of hypothetical proteins with unknown cellular and biological functions. Hence, it is indispensable to annotate these proteins functionally as well as structurally to identify novel drug targets. In the current study, a comparative genomics and proteomics based approach was applied to find the novel drug targets in XDR strain while comparing the MDR and NR strains of Salmonella typhi. The characterization of ~ 350 hypothetical proteins were performed through determination of their physio-chemical properties, sub-cellular localization, functional annotation, and structure-based studies. As a result, only five proteins were prioritized as essential, druggable, and virulent proteins. Moreover, only one protein i.e. WP_000916613.1 was functionally annotated with high confidence and subjected to further structure-based analysis. The current study presents a hypothetical protein from the XDR S. typhi proteome as a potential pharmacological target against which novel therapeutic candidates may be predicted. The outcome of the current study may lead to formulate a general set of pipelines for better understanding of the role of hypothetical proteins in pathogenesis of not only Salmonella but also for other pathogens. © 2021. The Author(s), under exclusive licence to Springer Nature B.V.

Citation

Kanwal Khan, Reaz Uddin. Integrated bioinformatics based subtractive genomics approach to decipher the therapeutic function of hypothetical proteins from Salmonella typhi XDR H-58 strain. Biotechnology letters. 2022 Feb;44(2):279-298

Mesh Tags

Substances

PMID: 35037232

search → result