Structural Characterization and Functional Annotation of a Hypothetical Protein from Salmonella Bongori: An In-Silico Investigation

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Authors: Md. Easin Mia, Partha Singha, Farzana Akter, Nur Alam
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Abstract

Salmonella bongori, a gram-negative, rod-shaped bacterium, is responsible for causing salmonellosis, a gastrointestinal illness marked by symptoms such as sudden fever, nausea, vomiting, cramping diarrhea, and abdominal discomfort. Identifying the relevant protein could potentially facilitate the development of effective treatments for S. bongori infection. Currently, many proteins in S. bongori remain unidentified and are called hypothetical proteins (HPs). This study aimed to elucidate the structure and function of an uncharacterized HP (accession no. QXY84013.1) from S. bongori. Analysis of subcellular localization and various physicochemical properties suggested that this protein is cytoplasmic and exhibits stability. NCBI-CD Search, the functional annotation software, indicated that our selected protein would be categorized as a constituent of the formate-dependent nitrite reductase complex, known explicitly as NrfG. NrfG, composed of tetratricopeptide repeat (TPR) proteins, plays a pivotal role in bacterial virulence, aiding in virulence factor transfer into host cells and phagolysosome maturation inhibition. Additionally, it plays a crucial role in developing the heme lyase complex (NrfEFG), potentially impacting bacterial iron acquisition and pathogenesis, thus influencing the severity of human bacterial infections. The predominant secondary structure observed was the alpha helix. Utilizing homology modeling via the SWISS-MODEL server, the protein’s threedimensional (3D) structure was determined, employing a template protein with 100% sequence similarity (PDB ID: A0A5U3DZQ4.1.A). Several quality assessment tools including ERRAT, QMEAN, and PROCHECK were used to verify the 3D structure. Furthermore, the modeled structure’s active site was predicted using the CASTp server. These findings hold promise as a potential foundation for the development of future antibacterial treatments. FENI UNIVERSITY JOURNAL, 2024, 3(1), ISSN [2518-3869], PP. (1-30)

Fields of Study & Subjects

Machine Learning in Bioinformatics Bacterial Genetics and Biotechnology Enzyme Structure and Function

Publication details

Journal / source
Feni University Journal
Volume
3
Issue
1
Pages
1–30
Publication date
4 January 2026