Designing multi-epitope-based vaccine targeting surface immunogenic protein of Streptococcus agalactiae using immunoinformatics to control mastitis in dairy cattle

Abstract

Background Milk provides energy as well as the basic nutrients required by the body. In particular, milk is beneficial for bone growth and development in children. Based on scientific evidence, cattle milk is an excellent and highly nutritious dietary component that is abundant in vitamins, calcium, potassium, and protein, among other minerals. However, the commercial productivity of cattle milk is markedly affected by mastitis. Mastitis is an economically important disease that is characterized by inflammation of the mammary gland. This disease is frequently caused by microorganisms and is detected as abnormalities in the udder and milk. Streptococcus agalactiae is a prominent cause of mastitis. Antibiotics are rarely used to treat this infection, and other available treatments take a long time to exhibit a therapeutic effect. Vaccination is recommended to protect cattle from mastitis. Accordingly, the present study sought to design a multi-epitope vaccine using immunoinformatics. Results The vaccine was designed to be antigenic, immunogenic, non-toxic, and non-allergic, and had a binding affinity with Toll-like receptor 2 (TLR2) and TLR4 based on structural modeling, docking, and molecular dynamics simulation studies. Besides, the designed vaccine was successfully expressed in E. coli. expression vector (pET28a) depicts its easy purification for production on a larger scale, which was determined through in silico cloning. Further, immune simulation analysis revealed the effectiveness of the vaccine with an increase in the population of B and T cells in response to vaccination. Conclusion This multi-epitope vaccine is expected to be effective at generating an immune response, thereby paving the way for further experimental studies to combat mastitis.

Targeting the PEDV 3CL protease for identification of small molecule inhibitors: an insight from virtual screening, ADMET prediction, molecular dynamics, free energy landscape, and binding energy calculations

“…The MD simulation was conducted using GROMACS version 2018.1 [ 31 , 32 ]. The system preparation was performed in accordance with previous research [ 33 – 35 ]. PRODRG was used to generate the ligand topology [ 36 ], whilst the pdb2gmx was used to create the protein topology [ 37 ].…”

Annotation of Potential Vaccine Targets and Designing of mRNA-Based Multi-Epitope Vaccine against Lumpy Skin Disease Virus via Reverse Vaccinology and Agent-Based Modeling

“…Therefore, molecular docking was carried out to screen the binding affinity of the different vaccine construct models to the host immune receptors. The 3D structures of bovine TLR2 (ID = AF-Q95LA9-F1) and TLR4 (ID = AF-Q9GL65-F1) [ 37 ] were retrieved from the AlphaFold Protein Structure Database [ 38 ]. Subsequently, the vaccine construct was intensively docked with receptors using the ClusPro 2.0 server [ 39 ].…”

Vetinformatics from functional genomics to drug discovery: Insights into decoding complex molecular mechanisms of livestock systems in veterinary science

“…To address this issue, computational vaccine design has been a major area of interest for researchers over the last two decades. Several tools and web-based resources have been developed that have proven useful in vaccine design (133,134). Researchers can now utilize advanced vetinformatics approaches to design vaccines that provide protection against livestock diseases (33,115,131).…”