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A basic issue in aligning DNA and protein sequences is to find similar characters between two or more sequences in order to detect relations between newly defined sequences and well-known sequences stored in genetic databanks. Local Sequences Alignment (LSA) algorithms have been developed to reveal similar regions between compared sequences. LSA algorithms produced optimal alignment using similarity matrix with scoring scheme. Match, mismatch, and gap penalties are identified using substation matrix and affine gap function. The accuracy of the results relies on selecting the best values for these parameters. This paper mainly set out to validate statically parameters for calculating possible alignments.Estimated values are tested using real dataset and the optimal alignment was recorded as well as the parameters. Perfect symmetric results were obtained, when comparing mathematically and statically estimation for the LSA parameters.