Evolutionary Computing to Examine Variation in Proteins with Evolution

Abstract

Amino-acid sequences play a pivotal role for the structure of proteins. Alterations in a single amino-acid may vary the protein functioning. Alignment of sequences recognizes evolutionary and structurally related residues in a group of amino-acid sequences. It also aids to perceive the regions that are conserved throughout and are also functionally important. Although protein alignment issue has been studied in the past decades, but computational approaches serves as more accurate to investigate the entire process in a comparably lesser time. Evolutionary algorithms, more specifically, genetic algorithms are very beneficial. It leads to the global optimization of the protein after observance of “the fittest” among the rest. On global optimization, the protein tends to be more stable, thereby, helping the process of interactions among other stable proteins and provides a residue level study. Thus, this state-of-art can be implemented for alignment of macro-molecules, which serves as an essential criterion for further molecular level analyses.