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Article history: Received: 21 August, 2020 Accepted: 05 December, 2020 Online: 20 March, 2021 The Anopheles gambiae’s CYP6Z3 protein belongs to the Cytochrome P450 family and functions in oxidation-reduction processes, many studies including our previous work on elucidating insecticide resistance genes of the Anopheles also implicated her in pyrethroid insecticide resistance. Model prediction, functional analysis, and enrichment of the target gene with triplex binding sites may become a useful diagnostic biomarker for the disease subtype, but wrong classification of the model by various existing alignment algorithms is a daunting issue that complicates and misleads in decision making during pathway and functional analysis. The aim of this study is to predict five in-silico model of CYP6Z3 Anopheles protein by homology modeling, evaluate and classify them to elucidate the performance of the sequence alignment algorithm deployed, then characterize the top model that is correctly classified. Template selection from three alignment algorithms with sequence of the target-protein, (Anopheles-CYP6Z3) obtained from UNIPROT served as input, Clustal omega and Clustalw2 algorithms was used to generate alignment files for homologous template search to the target-protein. Best template was sought, and the 3D model built in an-automated-mode. PROCHECK was used to evaluate the best-of-the-fiveobtained models. Estimating the quality of all models, the prime model emerged from ClustalW2 alignment algorithm, but was wrongly classified as a homo-tetramer-state. These provided a misleading-information which was revealed during model evaluation and interpretation, that resulted to an inappropriate pathway and functional-analysis, false positive model was then isolated, and the current best model emerged from clustalo alignment algorithm having 87.7% amino residues in the most favorable regions, 0.7% in the disallowed regions at monomer oligo state. Functional analysis of the best Anopheles CYP6Z3 secondary structure showed characteristics that explain the different degrees of genetic regulation translating to resistance mechanism in the malaria vector.

Homology Modeling of CYP6Z3 Protein of Anopheles Mosquito