Statistical coupling analysis
method to identify covarying pairs of amino acids in protein multiple sequence alignments
Statistical Coupling Analysis (SCA) is a method used in bioinformatics to study how pairs of amino acids in a protein sequence evolve together. It analyzes a multiple sequence alignment (MSA), which is a display of the sequences of many related proteins arranged to highlight similarities and differences. SCA measures how much the amino acid makeup at one position in the protein changes when the amino acid makeup at another position is altered. This relationship is quantified as statistical coupling energy. A higher coupling energy indicates that the amino acids at both positions are more likely to have co-evolved and are therefore functionally or structurally linked. In simpler terms, it helps scientists understand which parts of a protein are working together and how they have changed over evolutionary time.
Definition of statistical coupling energy
Statistical coupling energy measures how a perturbation of amino acid distribution at one site in an MSA affects the amino acid distribution at another site. For example, consider a multiple sequence alignment with sites (or columns) a through z, where each site has some distribution of amino acids. At position i, 60% of the sequences have a valine and the remaining 40% of sequences have a leucine, at position j the distribution is 40% isoleucine, 40% histidine and 20% methionine, k has an average distribution (the 20 amino acids are present at roughly the same frequencies seen in all proteins), and l has 80% histidine, 20% valine. Since positions i, j and l have an amino acid distribution different from the mean distribution observed in all proteins, they are said to have some degree of conservation.
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