Bioinformatics characterization of Plasmodium knowlesi apical membrane antigen 1 (PkAMA1) for multi-epitope vaccine design

Malaria caused by Plasmodium knowlesi species has become a public health concern, especially in Malaysia. Plasmodium knowlesi parasite which originates from the macaque species, infects human through the bite of the Anopheles mosquitoes. Research on malaria vaccine has been a continuous effort to er...

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Main Authors: Azazi, A., Haron, F. N., Chua, K. H., Lim, Y. A. L., Lee, P. C., Chew, C. H.
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Published: Malaysian Soc Parasitology Tropical Medicine 2021
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Online Access:http://eprints.um.edu.my/28185/
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spelling my.um.eprints.281852022-03-05T07:35:07Z http://eprints.um.edu.my/28185/ Bioinformatics characterization of Plasmodium knowlesi apical membrane antigen 1 (PkAMA1) for multi-epitope vaccine design Azazi, A. Haron, F. N. Chua, K. H. Lim, Y. A. L. Lee, P. C. Chew, C. H. R Medicine Malaria caused by Plasmodium knowlesi species has become a public health concern, especially in Malaysia. Plasmodium knowlesi parasite which originates from the macaque species, infects human through the bite of the Anopheles mosquitoes. Research on malaria vaccine has been a continuous effort to eradicate the malaria infection, yet there is no vaccine against P. knowlesi malaria to date. Apical membrane antigen 1 (AMA1) is a unique surface protein of all apicomplexan parasites that plays a crucial role in parasite-host cell invasion and thus has been a long-standing malaria vaccine candidate. The selection of protective epitopes in silico has led to significant advances in the design of the vaccine. The present study aimed to employ bioinformatics tools to predict the potential immunogenic B- and T-cell epitopes in designing malaria vaccine targeting P. knowlesi AMA1 (PkAMA1). B-cell epitopes were predicted using four bioinformatics tools, i.e., BepiPred, ABCpred, BcePred, and IEDB servers whereas T-cell epitopes were predicted using two bioinformatics servers, i.e., NetMHCpan-4.1 and NetMHCIIpan-4.0 targeting human major histocompatibility complex (MHC) class I and class II molecules, respectively. The antigenicity of the selected epitopes computed by both B - and T-cell predictors were further analyzed using the VaxiJen server. The results demonstrated that PkAMA1 protein encompasses multi antigenic regions that have the potential for the development of multi-epitope vaccine. Two B- and T-cell epitopes consensus regions, i.e., NSGIRIDLGEDAEVGNSKYRIPAGKCP (codons 28-54) and KTHAASFVIAEDQNTSY RHPAVYDEKNKT (codons 122-150) at domain I (DI) of PkAMA1 were reported. Advancement of bioinformatics in characterization of the target protein may facilitate vaccine development especially in vaccine design which is costly and cumbersome process. Thus, comprehensive B-cell and T-cell epitope prediction of PkAMA1 offers a promising pipeline for the development and design of multi-epitope vaccine against P. knowlesi. Malaysian Soc Parasitology Tropical Medicine 2021-09 Article PeerReviewed Azazi, A. and Haron, F. N. and Chua, K. H. and Lim, Y. A. L. and Lee, P. C. and Chew, C. H. (2021) Bioinformatics characterization of Plasmodium knowlesi apical membrane antigen 1 (PkAMA1) for multi-epitope vaccine design. Tropical Biomedicine, 38 (3). pp. 265-275. ISSN 0127-5720, DOI https://doi.org/10.47665/tb.38.3.067 <https://doi.org/10.47665/tb.38.3.067>. 10.47665/tb.38.3.067
institution Universiti Malaya
building UM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaya
content_source UM Research Repository
url_provider http://eprints.um.edu.my/
topic R Medicine
spellingShingle R Medicine
Azazi, A.
Haron, F. N.
Chua, K. H.
Lim, Y. A. L.
Lee, P. C.
Chew, C. H.
Bioinformatics characterization of Plasmodium knowlesi apical membrane antigen 1 (PkAMA1) for multi-epitope vaccine design
description Malaria caused by Plasmodium knowlesi species has become a public health concern, especially in Malaysia. Plasmodium knowlesi parasite which originates from the macaque species, infects human through the bite of the Anopheles mosquitoes. Research on malaria vaccine has been a continuous effort to eradicate the malaria infection, yet there is no vaccine against P. knowlesi malaria to date. Apical membrane antigen 1 (AMA1) is a unique surface protein of all apicomplexan parasites that plays a crucial role in parasite-host cell invasion and thus has been a long-standing malaria vaccine candidate. The selection of protective epitopes in silico has led to significant advances in the design of the vaccine. The present study aimed to employ bioinformatics tools to predict the potential immunogenic B- and T-cell epitopes in designing malaria vaccine targeting P. knowlesi AMA1 (PkAMA1). B-cell epitopes were predicted using four bioinformatics tools, i.e., BepiPred, ABCpred, BcePred, and IEDB servers whereas T-cell epitopes were predicted using two bioinformatics servers, i.e., NetMHCpan-4.1 and NetMHCIIpan-4.0 targeting human major histocompatibility complex (MHC) class I and class II molecules, respectively. The antigenicity of the selected epitopes computed by both B - and T-cell predictors were further analyzed using the VaxiJen server. The results demonstrated that PkAMA1 protein encompasses multi antigenic regions that have the potential for the development of multi-epitope vaccine. Two B- and T-cell epitopes consensus regions, i.e., NSGIRIDLGEDAEVGNSKYRIPAGKCP (codons 28-54) and KTHAASFVIAEDQNTSY RHPAVYDEKNKT (codons 122-150) at domain I (DI) of PkAMA1 were reported. Advancement of bioinformatics in characterization of the target protein may facilitate vaccine development especially in vaccine design which is costly and cumbersome process. Thus, comprehensive B-cell and T-cell epitope prediction of PkAMA1 offers a promising pipeline for the development and design of multi-epitope vaccine against P. knowlesi.
format Article
author Azazi, A.
Haron, F. N.
Chua, K. H.
Lim, Y. A. L.
Lee, P. C.
Chew, C. H.
author_facet Azazi, A.
Haron, F. N.
Chua, K. H.
Lim, Y. A. L.
Lee, P. C.
Chew, C. H.
author_sort Azazi, A.
title Bioinformatics characterization of Plasmodium knowlesi apical membrane antigen 1 (PkAMA1) for multi-epitope vaccine design
title_short Bioinformatics characterization of Plasmodium knowlesi apical membrane antigen 1 (PkAMA1) for multi-epitope vaccine design
title_full Bioinformatics characterization of Plasmodium knowlesi apical membrane antigen 1 (PkAMA1) for multi-epitope vaccine design
title_fullStr Bioinformatics characterization of Plasmodium knowlesi apical membrane antigen 1 (PkAMA1) for multi-epitope vaccine design
title_full_unstemmed Bioinformatics characterization of Plasmodium knowlesi apical membrane antigen 1 (PkAMA1) for multi-epitope vaccine design
title_sort bioinformatics characterization of plasmodium knowlesi apical membrane antigen 1 (pkama1) for multi-epitope vaccine design
publisher Malaysian Soc Parasitology Tropical Medicine
publishDate 2021
url http://eprints.um.edu.my/28185/
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