Tropical Biomedicine 38(3): 265-275 (2021) https://doi.org/10.47665/tb.38.3.067 RESEARCH ARTICLE Bioinformatics characterization of Plasmodium knowlesi apical membrane antigen 1 (PkAMA1) for multi-epitope vaccine design Azazi, A. 1 , Haron, F.N. 1 , Chua, K.H. 2 , Lim, Y.A.L. 3,4 , Lee, P.C. 5 , Chew, C.H. 1* 1 Faculty of Health Sciences, Universiti Sultan Zainal Abidin, 21300 Kuala Nerus, Terengganu, Malaysia 2 Department of Biomedical Science, Faculty of Medicine, Universiti Malaya, 50603 Kuala Lumpur, Malaysia 3 Department of Parasitology, Faculty of Medicine, Universiti Malaya, 50603 Kuala Lumpur, Malaysia 4 Centre of Excellence for Research in AIDS (CERiA), Universiti Malaya, 50603 Kuala Lumpur, Malaysia 5 Faculty of Science and Natural Resources, Universiti Malaysia Sabah, Jalan UMS, 88400 Kota Kinabalu, Sabah, Malaysia * Corresponding author: chinghoong80@yahoo.com; chewch@unisza.edu.my INTRODUCTION Malaria is a life-threatening disease caused by Plasmodium parasites that kills more than 400 000 people worldwide every year. In 2019, an estimated 229 million new malaria infections and 409 000 deaths were recorded (World Health Organization, 2020). Plasmodium knowlesi is classified as a zoonotic malaria parasite as the macaque monkeys serve as the reservoir host of this parasite species and transmission from animal to human is via anopheline mosquito. This species is now considered the fifth Plasmodium species that can cause human malaria, especially in forested areas of Southeast Asian countries (Chew et al ., 2012; Goh et al., 2013; Lee et al., 2015; Millar & Cox-Singh, 2015; Zaw & Lin, 2019; Cooper et al., 2020). Malaysia has reported zero indigenous cases for two consecutive years, 2018-2019. However, about 3 213 cases of P. knowlesi were reported in 2019, which is only slightly lower than in the previous year, in which 4 000 cases were reported (World Health Organization, 2020). Hence, research into the transmission control method such as vaccine development and anti- malarial drugs is essential as an effective control strategy. Even though many attempts have been made to develop an effective malaria vaccine, none has yet proven to be successful. This may be due to challenges in identifying the immunogenic antigens to be included as pivotal vaccine Published by Malaysian Society of Parasitology and Tropical Medicine. All rights reserved. ARTICLE HISTORY ABSTRACT Received: 23 March 2021 Revised: 11 June 2021 Accepted: 11 June 2021 Published: 31 July 2021 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 . Keywords: Apical membrane antigen 1 (AMA1); Plasmodium knowlesi ; bioinformatics; B-cell epitopes; T-cell epitopes.