Journal
REPORTS ON PROGRESS IN PHYSICS
Volume 81, Issue 3, Pages -Publisher
IOP PUBLISHING LTD
DOI: 10.1088/1361-6633/aa9965
Keywords
inverse problems; inverse Ising/Potts problem; statistical inference; protein sequence analysis; coevolution; protein structure prediction; protein-protein interaction
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Funding
- ANR project COEVSTAT [ANR-13-BS04-0012-01]
- 'Investissements d'Avenir' program [ANR-11-LABX-0037-01, ANR-11-IDEX-0004-02]
- Agence Nationale de la Recherche (ANR) [ANR-11-LABX-0037, ANR-13-BS04-0012] Funding Source: Agence Nationale de la Recherche (ANR)
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In the course of evolution, proteins undergo important changes in their amino acid sequences, while their three-dimensional folded structure and their biological function remain remarkably conserved. Thanks to modern sequencing techniques, sequence data accumulate at unprecedented pace. This provides large sets of so-called homologous, i.e. evolutionarily related protein sequences, to which methods of inverse statistical physics can be applied. Using sequence data as the basis for the inference of Boltzmann distributions from samples of microscopic configurations or observables, it is possible to extract information about evolutionary constraints and thus protein function and structure. Here we give an overview over some biologically important questions, and how statistical-mechanics inspired modeling approaches can help to answer them. Finally, we discuss some open questions, which we expect to be addressed over the next years.
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