Immunoinformatics-based epitope prediction in MERS-CoV and docking analysis of Catharanthus roseus compounds for drug...

Middle East Respiratory Syndrome Coronavirus (MERS-CoV) remains a major global health concern due to its high mortality rate and lack of effective therapeutic interventions. In the present study, an integrated immunoinformatics and molecular docking approach was employed to identify potential epitopes and phytochemical inhibitors against MERS-CoV. Initially, thirty spike protein sequences of MERS-CoV were retrieved from the National Center for Biotechnology Information (NCBI) database and evaluated for antigenicity, allergenicity, physicochemical, and structural properties using various bioinformatics tools, including VaxiJen, Immunomedicine, AllerTOP, ProtParam, SOPMA, PSIPRED, and Pro-SA. Based on the obtained results, highly antigenic and structurally stable epitopes were shortlisted for further analysis. B-cell and T-cell epitope prediction identified several immunogenic regions within the spike glycoprotein, particularly associated with receptor-binding domains. Simultaneously, the methanolic leaf extract of Catharanthus roseus was subjected to GC-MS analysis, resulting in the identification of eight major phytochemical compounds. The biological activities of the compounds were predicted using PASS online, while drug-likeness and pharmacokinetic properties were evaluated through SWISSADME. Molecular docking studies were performed using AutoDock Vina against selected MERS-CoV proteins with PDB IDs 4ZS6, 6C6Z, and 6L8Q. Among the investigated compounds, 2,20-Cycloaspidospermidine-3-carboxylic acid, 6,7-didehydro exhibited the highest binding affinity with docking scores of -12.2, -10.6, and -9.5 kcal/mol, respectively. The docked complexes were further analyzed through molecular dynamics simulations and RMSD/RMSF analyses to assess their dynamic stability. The findings suggest that phytochemicals derived from Catharanthus roseus possess promising antiviral potential against MERS-CoV and highlight the significance of combining immunoinformatics and computational drug discovery approaches for the development of novel antiviral therapeutics.