Improvement of clustal-derived sequence alignments with evolutionary algorithms

Multiple sequence alignment (MSA) is a central problem in bioinformatics. In this study, we extended previous efforts using evolutionary algorithms (EAs) for MSA. Candidate solutions in the initial population were derived from the well-known alignment program Clustal X. Evolutionary computation was then used to evolve increasingly appropriate solutions. Three new alignment operators were introduced and tested within the framework of protein sequence alignment. Statistics on alignment quality were generated with respect to selected alignment benchmarks from the BAliBASE database using the BLOSUM 62 substitution matrix. Our results indicate the degree to which EAs can enhance the results of Clustal X. Moreover, the experimental results show that the commonly used sum-of-pairs scoring scheme sometimes fails to correlate higher scoring alignments with increase in alignment quality in terms of the BAliBASE sum-of-pairs score.