Discovering conserved epitopes of Monkeypox: Novel immunoinformatic and machine learning approaches

Mohammad Izadi; Fatemeh Mirzaei; Mohammad Aref Bagherzadeh; Shamim Ghiabi; Alireza Khalifeh

doi:10.1016/j.heliyon.2024.e24972

Discovering conserved epitopes of Monkeypox: Novel immunoinformatic and machine learning approaches

Heliyon. 2024 Jan 23;10(3):e24972. doi: 10.1016/j.heliyon.2024.e24972. eCollection 2024 Feb 15.

Authors

Mohammad Izadi¹, Fatemeh Mirzaei¹, Mohammad Aref Bagherzadeh², Shamim Ghiabi³, Alireza Khalifeh⁴

Affiliations

¹ Student Research Committee, Shiraz University of Medical Sciences, Shiraz, Iran.
² Student Research Committee, Jahrom University of Medical Sciences, Jahrom, Iran.
³ Department of Medical Chemistry, Faculty of Pharmacy, Tehran Medical Sciences, Islamic Azad University, Tehran, Iran.
⁴ Department of Pathology, Faculty of Dentistry, Shiraz Branch, Islamic Azad of University, Shiraz, Iran.

Abstract

The Monkeypox virus, an Orthopoxvirus with zoonotic origins, has been responsible for a growing number of human infections reminiscent of smallpox since May 2022, as reported by the World Health Organization. As of now, there are no established medical treatments for managing Monkeypox infections. In this study, we used machine learning to select conserved epitopes. Proteins were determined using Reverse Vaccinology and Gene Ontology subcellular localization, and their epitopes were predicted. NextClade was used to calculate the number of mutations in each amino acid position using 2433 Monkeypox sequences. The Unsupervised Nearest Neighbor machine learning algorithm and ideal matrix [0 0] were used to calculate the conservancy score of epitopes. Six proteins were determined for epitope prediction. Finally, 47 MHC-I epitopes, 5 MHC-II epitopes, and 10 Linear B cell epitopes were discovered. Our method can select epitopes for vaccine design to prevent viruses with accelerated evolution and high mutation rate.

Keywords: Conserved epitopes; Immunoinformatic; Machine learning; Monkeypox.