Sculpting multi-epitope vaccine against Monkeypox viral strains using immunoinformatics

The epidemic of Monkeypox virus (MPXV), an emerging zoonotic Orthopoxvirus, in beginning OF May 2022, has drawn global attention owing to its increasingly reported cases by the World Health Organization (WHO) in multiple countries. Due to absence of any validated treatments for MPXV infections, the...

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Main Authors: Zaira Rehman, Ammad Fahim, Maryam Irtash
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-01-01
Series:Acta Virologica
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Online Access:https://www.frontierspartnerships.org/articles/10.3389/av.2024.13542/full
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author Zaira Rehman
Ammad Fahim
Maryam Irtash
author_facet Zaira Rehman
Ammad Fahim
Maryam Irtash
author_sort Zaira Rehman
collection DOAJ
description The epidemic of Monkeypox virus (MPXV), an emerging zoonotic Orthopoxvirus, in beginning OF May 2022, has drawn global attention owing to its increasingly reported cases by the World Health Organization (WHO) in multiple countries. Due to absence of any validated treatments for MPXV infections, the preventive strategies hold significant importance. The current study proposes potential vaccine targets against MPXV by deploying immunoinformatic method. The monkeypox virus encodes 190 different proteins. These proteins were shortlisted on the basis of antigenicity, surface expression, allergenicity, and toxicity. The shortlisted ten proteins were subjected to identification of B- and T-cell epitopes using IEDB, ABCpred, NetMHCpan4.0, and NetMHCIIpan4.0. All the epitopes were further screened for antigenicity, allergenicity, and toxicity properties using VaxiJen, Allertop, and Toxinpred server. All the epitopes have 97.5% worldwide population coverage. Overlapping B-cell, CTL and HTL epitopes were used to design three vaccine construct using suitable linkers and three different adjuvants. Molecular docking was performed for all the three vaccine constructs with TLR4. Based on docking scores and physicochemical profile the vaccine construct V1 with beta defensin adjuvant was selected for further analysis. In silico cloning of V1 into pBAD-DEST49 vector showed maximum expression in bacterial system. Immune simulations also confirmed the high immune responses of V1 within the host cell. The study results may lead towards identification of clinically effective vaccines against MPXV with better safety and potency profile.
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spelling doaj-art-abf63730bcff4774bc0980f0aa960a352025-01-20T04:12:03ZengFrontiers Media S.A.Acta Virologica1336-23052025-01-016810.3389/av.2024.1354213542Sculpting multi-epitope vaccine against Monkeypox viral strains using immunoinformaticsZaira Rehman0Ammad Fahim1Maryam Irtash2Department of Clinical Laboratories, Indus Hospital and Health Network, Karachi, PakistanOffice of Research, Innovation and Commercialization (ORIC), Indus Hospital and Health Network, Karachi, PakistanHealth Services Academy, Ministry of National Health Services Regulations and Coordination, Islamabad, PakistanThe epidemic of Monkeypox virus (MPXV), an emerging zoonotic Orthopoxvirus, in beginning OF May 2022, has drawn global attention owing to its increasingly reported cases by the World Health Organization (WHO) in multiple countries. Due to absence of any validated treatments for MPXV infections, the preventive strategies hold significant importance. The current study proposes potential vaccine targets against MPXV by deploying immunoinformatic method. The monkeypox virus encodes 190 different proteins. These proteins were shortlisted on the basis of antigenicity, surface expression, allergenicity, and toxicity. The shortlisted ten proteins were subjected to identification of B- and T-cell epitopes using IEDB, ABCpred, NetMHCpan4.0, and NetMHCIIpan4.0. All the epitopes were further screened for antigenicity, allergenicity, and toxicity properties using VaxiJen, Allertop, and Toxinpred server. All the epitopes have 97.5% worldwide population coverage. Overlapping B-cell, CTL and HTL epitopes were used to design three vaccine construct using suitable linkers and three different adjuvants. Molecular docking was performed for all the three vaccine constructs with TLR4. Based on docking scores and physicochemical profile the vaccine construct V1 with beta defensin adjuvant was selected for further analysis. In silico cloning of V1 into pBAD-DEST49 vector showed maximum expression in bacterial system. Immune simulations also confirmed the high immune responses of V1 within the host cell. The study results may lead towards identification of clinically effective vaccines against MPXV with better safety and potency profile.https://www.frontierspartnerships.org/articles/10.3389/av.2024.13542/fullmonkeypox virusantigenicityreverse vaccinologyimmune simulationmolecular dynamic simulation
spellingShingle Zaira Rehman
Ammad Fahim
Maryam Irtash
Sculpting multi-epitope vaccine against Monkeypox viral strains using immunoinformatics
Acta Virologica
monkeypox virus
antigenicity
reverse vaccinology
immune simulation
molecular dynamic simulation
title Sculpting multi-epitope vaccine against Monkeypox viral strains using immunoinformatics
title_full Sculpting multi-epitope vaccine against Monkeypox viral strains using immunoinformatics
title_fullStr Sculpting multi-epitope vaccine against Monkeypox viral strains using immunoinformatics
title_full_unstemmed Sculpting multi-epitope vaccine against Monkeypox viral strains using immunoinformatics
title_short Sculpting multi-epitope vaccine against Monkeypox viral strains using immunoinformatics
title_sort sculpting multi epitope vaccine against monkeypox viral strains using immunoinformatics
topic monkeypox virus
antigenicity
reverse vaccinology
immune simulation
molecular dynamic simulation
url https://www.frontierspartnerships.org/articles/10.3389/av.2024.13542/full
work_keys_str_mv AT zairarehman sculptingmultiepitopevaccineagainstmonkeypoxviralstrainsusingimmunoinformatics
AT ammadfahim sculptingmultiepitopevaccineagainstmonkeypoxviralstrainsusingimmunoinformatics
AT maryamirtash sculptingmultiepitopevaccineagainstmonkeypoxviralstrainsusingimmunoinformatics