In silico structural modeling and quality assessment of Plasmodium knowlesi apical membrane antigen 1 using comparative protein models

ABSTRACT

@#Plasmodium knowlesi is the most common zoonotic parasite associated with human malaria infection in Malaysia. Apical membrane antigen 1 (AMA1) protein in the parasite plays a critical role in parasite invasion into host cells. To date, there is no complete three-dimensional ectodomain structure of P. knowlesi AMA1 (PkAMA1) protein. The knowledge of a protein structure is important to understand the protein molecular functions. Three in silico servers with respective structure prediction methods were used in this study, i.e., SWISS-MODEL for homology modeling and Phyre2 for protein threading, which are template-based modeling, while I-TASSER for template-free ab initio modeling. Two query sequences were used in the study, i.e., native ectodomain of PkAMA1 strain H protein designated as PkAMA1-H and a modified PkAMA1 (mPkAMA1) protein sequence in adaptation for Pichia pastoris expression. The quality of each model was assessed by ProSA-web, QMEAN and SAVES v6.0 (ERRAT, Verify3D and Ramachandran plot) servers. Generated models were then superimposed with two models of Plasmodium AMA1 deposited in Protein Data Bank (PDB), i.e., PkAMA1 (4UV6.B) and Plasmodium vivax AMA1 (PvAMA1, 1W81) protein structures for similarity assessment, quantified by root-meansquare deviation (RMSD) value. SWISS-MODEL, Phyre2 and I-TASSER server generated two, one and five models, respectively. All models are of good quality according to ProSA-web assessment. Based on the average values of model quality assessment and superimposition, the models that recorded highest values for most parameters were selected as best predicted models, i.e., model 2 for both PkAMA1-H and mPkAMA1 from SWISS-MODEL as well as model 1 of PkAMA1-H and model 3 of mPkAMA1 from I-TASSER. Template-based method is useful if known template is available, but template-free method is more suitable if there is no known available template. Generated models can be used as guidance in further protein study that requires protein structural data, i.e., protein-protein interaction study.