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

Abstract

Purpose 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. Methods 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 . Results 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. Conclusion 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. Supplementary Information The online version contains supplementary material available at 10.1007/s10529-021-03219-6.

Some Transmembrane Proteins Of Salmonella Typhimurium Are Potential Drug Targets: An In Silico Analysis

“…Bioinformatics plays a crucial role in identifying drug targets in Salmonella through diverse computational methods and data analysis techniques. It facilitates the analysis of genomic and proteomic data from Salmonella strains, aiding in pinpointing potential drug targets (Khan & Uddin 2022). By comparing genomes of drug-resistant strains with susceptible ones, bioinformatics detects genetic variations linked to resistance, thus highlighting potential intervention targets (Jalal et al 2021).…”

“…Identifying transmembrane proteins in pathogenic microorganisms involves employing bioinformatic tools and computational approaches to predict and analyze protein structures and functions. Sequence-based bioinformatics tools are utilized to detect potential transmembrane domains within protein sequences, employing algorithms like Hidden Markov Models (HMMs) and Position-Specific Scoring Matrices (PSSMs) to recognize characteristic patterns indicative of transmembrane regions (Khan & Uddin 2022). Subsequently, structural bioinformatics tools are employed to model the three-dimensional structure of identified proteins, enabling visualization of transmembrane domains and their orientation within the lipid bilayer.…”