Comparative analysis of the quality of a global algorithm and a local algorithm for alignment of two sequences

Using model series of amino acid sequence pairs, we studied the relative "quality" of results produced by local and global alignments versus (1) the relative length of similar parts of the sequences (their "cores") and their nonhomologous parts, and (2) relative positions of the core regions in the compared sequences. We obtained numerical values of the average quality (measured as accuracy and confidence) of the global alignment method and the local alignment method for evolutionary distances between homologous sequence parts from 30 to 240 PAM and for the core length making from 10% to 70% of the total length of the sequences for all possible positions of homologous sequence parts relative to the centers of the sequences.We revealed criteria allowing to specify conditions of preferred applicability for the local and the global alignment algorithms depending on positions and relative lengths of the cores and nonhomologous parts of the sequences to be aligned. It was demonstrated that when the core part of one sequence was positioned above the core of the other sequence, the global algorithm was more stable at longer evolutionary distances and larger nonhomologous parts than the local algorithm. On the contrary, when the cores were positioned asymmetrically, the local algorithm was more stable at longer evolutionary distances and larger nonhomologous parts than the global algorithm. This opens a possibility for creation of a combined method allowing generation of more accurate alignments.Pair-wise alignment of amino acid sequences is the main method of comparative protein analysis. Among the most popular algorithms based on comparison of protein primary structures the Needleman-Wunch algorithm [1], the Smith-Waterman algorithm [2], BLAST [3], and FASTA [4] should be noted. On the basis of paper [1] the algorithm [5] was created for comparing sequences with intermittent similarities. The improved version [6] makes use of multiple parameter sets in computation of an o