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- W2551582013 abstract "Potts Hamiltonian models of protein sequence co-variation are statistical models constructed from the pair correlations observed in a multiple sequence alignment (MSA) of a protein family. These models are powerful because they capture higher order correlations induced by mutations evolving under constraints and help quantify the connections between protein sequence, structure, and function maintained through evolution. We review recent work with Potts models to predict protein structure and sequence-dependent conformational free energy landscapes, to survey protein fitness landscapes and to explore the effects of epistasis on fitness. We also comment on the numerical methods used to infer these models for each application." @default.
- W2551582013 created "2016-11-30" @default.
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- W2551582013 date "2017-04-01" @default.
- W2551582013 modified "2023-10-13" @default.
- W2551582013 title "Potts Hamiltonian models of protein co-variation, free energy landscapes, and evolutionary fitness" @default.
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- W2551582013 doi "https://doi.org/10.1016/j.sbi.2016.11.004" @default.
- W2551582013 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/5869684" @default.
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