Correlations among amino acid sites in bHLH protein domains: an information theoretic analysis.

By W. Atchley, Kurt R. Wollenberg, Walter M. Fitch, W. Terhalle, A. Dress. 2000

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Protein 3D Structure Computed from Evolutionary Sequence Variation (2011, background): “This suggests that residue correlations could provide information about amino acid residues that are close in structure [4,5,6,7,8,9,10,11].”
Direct-coupling analysis of residue coevolution captures native contacts across many protein families (2011, methodology): “solutions for the fitting are possible. To remove this freedom, we consider all couplings and fields measured relative to the last amino acid €ij A=q, and set € ∀i,j,A:e(A,q)=e ij (q,A)=0,h i (q)=0 , (6) Details on the maximum-entropy approach are given in the Supplement. Small-coupling expansion Eq”
Protein sectors: evolutionary units of three-dimensional structure (2009, background): “Though the principles of computing correlations vary, similar approaches for partial elimination of purely phylogenetic correlations in protein sequence alignments have been previously described (Atchley et al., 2000; Buck and Atchley, 2005; Ortiz et al., 1999).”
Prevalence of Epistasis in the Evolution of Influenza A Surface Proteins (2011, methodology): “Early methods were based on the idea that co-evolving pairs of sites in a protein should leave a typical signature in a sequence alignment, which can be detected using quantities such as mutual information [48–50].”
Synthetic protein alignments by CCMgen quantify noise in residue-residue contact prediction (2018, background): “The background noise eﬀects arising in residue-residue contact prediction have been postulated to arise from three independent sources [1, 8, 14, 18, 22, 33, 37, 43]: random sampling noise due to the limited number of se-40 quences, phylogenetic noise due to the evolutionary re-latedness of…”
Consensus protein design (2016, background): “…have typically utilised additional statistical analysis that identifies coupling or covariation (Göbel et al., 1994; Lockless and Ranganathan, 1999; Atchley et al., 2000; Socolich et al., 2005; Talavera et al., 2015) and have generally been very successful in the engineering of stability (Magliery…”
Computing Highly Correlated Positions Using Mutual Information and Graph Theory for G Protein-Coupled Receptors (2009, background): “These correlations could possibly be due to coevolving residues, correlated mutations, phylogenetic noise, a biased dataset, or a combination of these factors [32].”
3D Protein Structure Predicted from Sequence (2011, unknown): “This suggests that residue correlation can provide information about amino acid residues that are close in structure [4,5,6,7,8,9,10,11].”
Predicting Functionally Informative Mutations in Escherichia coli BamA Using Evolutionary Covariance Analysis (2013, methodology): “MI ij scores were calculated as where single and pair amino acid frequencies are calculated with sequence down-weighting but do not incorporate pseu-docounts (Atchley et al. 2000).”
The Regulation of Flavonoid Biosynthesis (2006, background): “Similar to the R2R3-MYB family, the plant bHLH family is very large, with more than 150 members in Arabidopsis (Atchley et al., 2000; Buck and Atchley, 2003; Heim et al., 2003; Toledo-Ortiz et al., 2003).”
Features of protein-protein interactions in two-component signaling deduced from genomic libraries. (2007, background): “Various unique measures have been introduced to investigate covariance between amino acid positions in proteins (Altschuh et al., 1987; Atchley et al., 2000; Go¨bel etal.,1994; Kassand Horovitz, 2002; Locklessand Ranganathan, 1999; Suel et al., 2003).”
Influence of conservation on calculations of amino acid covariance in multiple sequence alignments (2004, methodology): “Our implementation of the MI algorithm follows the description given by Atchley et al.(13) According to this algorithm, “the extent of ‘correlation’ or association between residues at amino acid sites X and Y that might arise from evolutionary, functional, or structural constraints” is defined as”
Using multiple interdependency to separate functional from phylogenetic correlations in protein alignments (2003, background): “Methods to find constrained regions in the alignment (Aimon et al., 2002) or to find correlations between sites (Shindyalov et al., 1994; Pollock et al., 1999; Atchley et al., 2000; Wollenberg and Atchley, 2000) assume a phylogeny and substitution model.”
Inference of direct residue contacts in two-component signaling. (2010, methodology): “Covariance-based methods have been extensively applied to gain insights into protein tertiary structure (Altschuh et al., 1987; Atchley et al., 2000; Göbel et al., 1994; Suel et al., 2003) and more recently to identifying protein interaction surfaces (Burger and van Nimwegen, 2008; Kass and…”