Direct coupling analysis

Direct coupling analysis or DCA is an umbrella term comprising several methods for analyzing sequence data in computational biology. The common idea of these methods is to use statistical modeling to quantify the strength of the direct relationship between two positions of a biological sequence, excluding effects from other positions. This contrasts usual measures of correlation, which can be large even if there is no direct relationship between the positions (hence the name direct coupling analysis). Such a direct relationship can for example be the evolutionary pressure for two positions to maintain mutual compatibility in the biomolecular structure of the sequence, leading to molecular coevolution between the two positions. DCA has been used in the inference of protein residue contacts, RNA structure prediction, the inference of protein-protein interaction networks, the modeling of fitness landscapes, and the identification of functionally relevant residue communities. The basis of DCA is a statistical model for the variability within a set of phylogenetically related biological sequences. When fitted to a multiple sequence alignment (MSA) of sequences of length , the model defines a probability for all possible sequences of the same length. This probability can be interpreted as the probability that the sequence in question belongs to the same class of sequences as the ones in the MSA, for example the class of all protein sequences belonging to a specific protein family. We denote a sequence by , with the being categorical variables representing the monomers of the sequence (if the sequences are for example aligned amino acid sequences of proteins of a protein family, the take as values any of the 20 standard amino acids). The probability of a sequence within a model is then defined as where are sets of real numbers representing the parameters of the model (more below) is a normalization constant (a real number) to ensure The parameters depend on one position and the symbol at this position.