Author/Authors :
Goel, Prerna Department of Bioinformatics - Goswami Ganesh Dutta Sanatan Dharma College, Sector, Chandigarh, India , Panchal, Tanya Department of Bioinformatics - Goswami Ganesh Dutta Sanatan Dharma College, Sector, Chandigarh, India , Kaushik, Nandini Department of Bioinformatics - Goswami Ganesh Dutta Sanatan Dharma College, Sector, Chandigarh, India , Chauhan, Ritika Department of Bioinformatics - Goswami Ganesh Dutta Sanatan Dharma College, Sector, Chandigarh, India , Saini, Sandeep Department of Bioinformatics - Goswami Ganesh Dutta Sanatan Dharma College, Sector, Chandigarh, India , Ahuja, Vartika Department of Bioinformatics - Goswami Ganesh Dutta Sanatan Dharma College, Sector, Chandigarh, India , Jyoti Thakur, Chander Department of Bioinformatics - Goswami Ganesh Dutta Sanatan Dharma College, Sector, Chandigarh, India
Abstract :
Francisella tularensis is a pathogenic, aerobic gram-negative coccobacillus bacterium. It is
the causative agent of tularemia, a rare infectious disease that can attack skin, lungs, eyes, and
lymph nodes. The genome of F. tularensis has been sequenced, and ~16% of the proteome is
still uncharacterized. Characterizations of these proteins are essential to find new drug targets
for better therapeutics. In silico characterization of proteins has become an extremely important
approach to determine the functionality of proteins as experimental functional elucidation is
unable to keep pace with the current growth of the sequence database. Initially, we have
annotated 577 Hypothetical Proteins (HPs) of F. tularensis strain SCHU4 with seven
bioinformatics tools which characterized them based on the family, domain and motif. Out of
577 HPs, 119 HPs were annotated by five or more tools and are further screened to predict their
virulence properties, subcellular localization, transmembrane helices as well as physicochemical
parameters. VirulentPred predicted 66 HPs out of 119 as virulent. These virulent proteins were
annotated to find the interacting partner using STRING, and proteins with high confidence
interaction scores were used to predict their 3D structures using Phyre2. The three virulent
proteins Q5NH99 (phosphoserine phosphatase), Q5NG42 (Cystathionine beta-synthase) and
Q5NG83 (Rrf2-type helix turn helix domain) were predicted to involve in modulation of
cytoskeletal and innate immunity of host, H2S (hydrogen sulfide) based antibiotic tolerance and
nitrite and iron metabolism of bacteria. The above predicted virulent proteins can serve as novel
drug targets in the era of antibiotic resistance.
Keywords :
Domains , Drug target , Virulence factor , Annotation , Microbial resistance , Bioinformatics