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There are many diseases caused by viruses or bacteria. The structure of virus and bacteria always mutate to create new structures. Sequence alignment is important so that it can be used to research genetic diseases and epidemics. In this reseach, we take case study of zika virus. To see the similarity between original virus and the mutation virus, it is required the alignment process of two virus sequences. The method used for aligning two virus sequences is Super Pairwise Alignment (SPA). Due to the value of objective function depends on SPA parameters, in this research we will apply heuristic method, such as Artificial Bee Colony (ABC) algorithm to optimize SPA parameters minimizing penalty value and maximizing similarity value as objective function. From the ABC simulations, we can obtain optimal SPA parameters resulting minimum penalty value and maximum similarity value between two aligned zika virus protein sequences.

sequence alignment; super pairwise alignment; artificial bee colony; penalty value; similarity value