Bioinformatics approach for structure modeling, vaccine design, and molecular docking of Brucella candidate proteins BvrR, OMP25, and OMP31

Abstract

Abstract Brucellosis is a zoonotic disease with significant economic and healthcare costs. Despite the eradication efforts, the disease persists. Vaccines prevent disease in animals while antibiotics cure humans with limitations. This study aims to design vaccines and drugs for brucellosis in animals and humans, using protein modeling, epitope prediction, and molecular docking of the target proteins (BvrR, OMP25, and OMP31). Tertiary structure models of three target proteins were constructed and assessed using RMSD, TM-score, C-score, Z-score, and ERRAT. The best models selected from AlphaFold and I-TASSER due to their superior performance according to CASP 12 – CASP 15 were chosen for further analysis. The motif analysis of best models using MotifFinder revealed two, five, and five protein binding motifs, however, the Motif Scan identified seven, six, and eight Post-Translational Modification sites (PTMs) in the BvrR, OMP25, and OMP31 proteins, respectively. Dominant B cell epitopes were predicted at (44–63, 85–93, 126–137, 193–205, and 208–237), (26–46, 52–71, 98–114, 142–155, and 183–200), and (29–45, 58–82, 119–142, 177–198, and 222–251) for the three target proteins. Additionally, cytotoxic T lymphocyte epitopes were detected at (173–181, 189–197, and 202–210), (61–69, 91–99, 159–167, and 181–189), and (3–11, 24–32, 167–175, and 216–224), while T helper lymphocyte epitopes were displayed at (39–53, 57–65, 150–158, 163–171), (79–87, 95–108, 115–123, 128–142, and 189–197), and (39–47, 109–123, 216–224, and 245–253), for the respective target protein. Furthermore, structure-based virtual screening of the ZINC and DrugBank databases using the docking MOE program was followed by ADMET analysis. The best five compounds of the ZINC database revealed docking scores ranged from (− 16.8744 to − 15.1922), (− 16.0424 to − 14.1645), and (− 14.7566 to − 13.3222) for the BvrR, OMP25, and OMP31, respectively. These compounds had good ADMET parameters and no cytotoxicity, while DrugBank compounds didn't meet Lipinski's rule criteria. Therefore, the five selected compounds from the ZINC20 databases may fulfill the pharmacokinetics and could be considered lead molecules for potentially inhibiting Brucella’s proteins.

Keywords

• Brucellosis
• Outer membrane protein
• BvrR
• Bioinformatics
• Protein modeling
• Epitopes prediction