Optimal sequence similarity of triplex capsid proteins of human herpes simplex virus (HHV) is a complex bioinformatics problem, which is controlled by alignment algorithms, substitution matrix, gap penalty and gap extension. A precise choice of mutation matrix is required to optimal the alignment similarity and appropriate computational approach required for similarity search. The present paper uses Adaptive Neuro-Fuzzy Inference System (ANFIS) approach to model and simulate the alignment similarity for PAM and Blosum substitution matrices. Mutation matrix and sequences of HHV-I and HHV-II were taken as model’s input parameters. The model is the combination of fuzzy inference, artificial neural network, and set of fuzzy rules has been developed directly from computational analysis using N-W algorithm. The proposed modeling approach is verified by comparing the expected results with the observed practical results obtained by computational analysis under specific conditions. The application of ANFIS test shows that the substitution matrix predicted by a proposed model is fully in agreement with the experimental values at 0.5% level of significance.