Elements of coevolution in biological sequences.

By Olivier Rivoire. 2012

31 citations recorded by the source corpus.

Studies of coevolution of amino acids within and between proteins have revealed two types of coevolving units: coevolving contacts, which are pairs of amino acids distant along the sequence but in contact in the three-dimensional structure, and sectors, which are larger groups of structurally connected amino acids that underlie the biochemical properties of proteins. By reconciling two approaches for analyzing correlations in multiple sequence alignments, we link these two findings together and with coevolving units of intermediate size, called "sectons," which are shown to provide additional information. By extending the analysis to the co-occurrence of orthologous genes in bacterial genomes, we also show that the methods and results are general and relevant beyond protein structures.

Subfields: Molecular Biology

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Molecular Biology

Citations in the corpus

Revealing evolutionary constraints on proteins through sequence analysis (2018, background): “the fact that contacts are overrepresented within a sector but not across sectors [58].”
Fast pseudolikelihood maximization for direct-coupling analysis of protein structure from many homologous amino-acid sequences (2014, methodology): “Numerous freshly conceived methods expand the concepts and applicability of DCA in various directions [30, 31, 32, 33, 34, 35, 36, 37, 38].”
Coevolution-based inference of amino acid interactions underlying protein function (2018, background): “As explained previously, these two approaches sample different parts of the information contained in a sequence alignment (Cocco et al., 2013; Rivoire, 2013), and therefore are not mutually incompatible.”
Evolution-Based Functional Decomposition of Proteins (2015, unknown): “Using mathematical analyses that explore diﬀerent aspects of this matrix (7; 8), studies have exposed tertiary structural contacts in protein structures (Direct Coupling Analysis, or DCA, (4; 9)), determinants of binding speciﬁcity in paralogous protein complexes (5), and larger, collectively…”
Protein Sectors: Statistical Coupling Analysis versus Conservation (2014, methodology): “Independent component analysis (ICA) has also been invoked to find the linear combinations [19, 20, 22], but a mathematically rigorous motivation for the application of this procedure is missing.”
Patterns of coevolving amino acids unveil structural and dynamical domains (2017, background): “DCA and statistical coupling analysis share nevertheless important conceptual similarities (89, 90), and, therefore, similarities between EDs and sectors can be expected in specific contexts.”