Correlated mutations in protein sequences: Phylogenetic and structural effects

By A. Lapedes, B. Giraud, L. Liu, Gary D. Stormo. 1997

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Protein structure prediction from sequence variation (2012, background): “For example, if residues A and B contact each other, as do residues B and C, then there is in general, a transitive influence observed between residues A and C (‘chain-ing effect’ 17,27 ).”
3D structures of membrane proteins from genomic sequencing (2012, neutral): “The predicted toy contact map (middle) shows To discover residue interactions that are conserved by evolution, we developed an algorithm that extracts patterns of amino acid coevolution from these sequence alignments (Lapedes et al., 1997; Marks et al., 2011; Morcos et al., 2011).”
Patterns of coevolving amino acids unveil structural and dynamical domains (2017, methodology): “The PDB structures associated with the query sequences were used a posteriori to assess the structural and dynamical characteristics of the EDs inferred from the sole direct coupling analysis of the MSAs (39, 93).”
Accurate de novo structure prediction of large transmembrane protein domains using fragment-assembly and correlated mutation analysis (2012, background): “Lapedes et al. (33) related the problem of decoupling mutation correlations in MSAs to the inverse Ising problem in statistical physics and proposed a solution based on entropy maximization; however, it is only recently that practical solutions to the decoupling problem have been proposed (34 – 36) ”