Similarity and homology are terms often used interchangeably when referring to sequence alignment comparisons. However, similarity refers to the percent identity, while homology is the inference drawn from the data suggesting a common evolutionary history. Optimal alignments are achieved by using an alignment algorithm that assigns positive incremental scores for aligning identical residues while assigning negative scores for substitutions and gaps. For protein alignments, the use of a substitution matrix increases the sensitivity to weak alignments. Statistical matrices are used both to identify sequences in a database, and to predict the biological significance of the match.
PAM matrices are most sensitive for alignments of sequences with evolutionary related homologs.
The selection of gap penalty parameters is empirical and there are no basic guidelines to follow. The general rule, however, is that the gap open penalty is greater than the gap extension penalty. A single mutational event is rare, but if one does occur, it is likely that several adjacent residues will be involved. Gap uses the algorithm of Needleman and Wunsch to find the alignment of two complete sequences. It maximizes the number of matches and minimizes the number of gaps.