An accompanying study showed that the artificial WW domains were functionally similar to natural WW domains in ligand binding affinity and specificity. Statistical coupling analysis reveals coevolved continuous clusters of amino acid residues that extend from the active site into the hydrophobic cores of each of the two domains and include … Statistical coupling analysis (SCA) regards evolution as a natural mutagenesis process and utilizes the known protein sequences to economically examine comprehensive correlations between amino acid residues. [7], Definition of statistical coupling energy, Ranganathan lecture on statistical coupling analysis (audio included). Interpretation of the results and sector definition, SCA6.0 - The DHFR (dihydrofolate reductase) family, SCA6.0 - The Beta-lactamase enzyme family. The method applies spectral analysis to a matrix obtained by combining correlation information with sequence conservation. This analysis retrieves two co-evolved residues in a protein for either structural or functional reasons. [3] Using the PDZ domain family, they were able to identify a small network of residues that were energetically coupled to a binding site residue. “Evolution-Based Functional Decomposition of Proteins”. In statistical coupling analysis, the conservation (ΔGstat) at each site (i) is defined as: 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. This contrasts usual measures of correlation, which can be large even if … t This support for the SCA hypothesis was made more compelling considering that a) the successfully folded proteins had only 36% average sequence identity to natural WW folds, and b) none of the artificial proteins designed without coupling information folded properly. Calculation of the conservation and co-evolution statistics, 4. Statistical coupling analysis (SCA) is a method for analyzing multiple sequence alignments that was used to identify groups of coevolving residues termed \sectors". Alignment pre-processing and conditioning, 3. statistical analysis of the impacts of varying input parameters is much less common. Getting oriented... a quick note on file and directory structure: 1. premise is that extending the traditional definition of conservation Given a representative G The statistical coupling analysis was performed in accordance with the projection method [19, 25], which is the default in the newest version of the SCA … amino acid positions in a protein family. protein folding. In this paper, the authors establish a theoretical framework for statistical timing analysis with coupling. #10, Kutty Street, Nungambakkam, Chennai, Tamil Nadu – 600034, India No : +91-4448137070, UK No : +44-1223926607 , US No : +1-9725029262 Email: [email protected] ln Please Cite: Olivier Rivoire, Kimberly Reynolds, and Rama The Statistical Coupling Analysis (SCA) is an approach for characterizing the pattern of evolutionary constraints on and between amino acid positions in a protein family. Statistical coupling analysis. Monte Carlo simulations reveal a distinct gain in accuracy (up to 24%) of our approach in comparison to the others. The network consisted of both residues spatially close to the binding site in the tertiary fold, called contact pairs, and more distant residues that participate in longer-range energetic interactions. An iterative statistical timer that considers coupling de-terministically, based on [15]. Statistical coupling energy, denoted ΔΔGi, jstat, is simply the difference between these two values. = Later applications of SCA by the Ranganathan group on the GPCR, serine protease and hemoglobin families also showed energetic coupling in sparse networks of residues that cooperate in allosteric communication. .[2]. i Here, Pix describes the probability of finding amino acid x at position i, and is defined by a function in binomial form as follows: where N is 100, nx is the percentage of sequences with residue x (e.g. functional constraint on all pairs of sequence positions (the analysis of conservation), and for measuring and analyzing the coupled pairwise-correlated, or “second-order” analysis of conservation). Continuing with the example MSA from the beginning of the section, consider a perturbation at position j where the amino distribution changes from 40% I, 40% H, 20% M to 100% I.