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Pré-Publication, Document De Travail Année : 2023

Mutational paths with sequence-based models of proteins: from sampling to mean-field characterisation

Résumé

Identifying and characterizing mutational paths is an important issue in evolutionary biology and in bioengineering. We here propose an algorithm to sample mutational paths, which we benchmark on exactly solvable models of proteins in silico, and apply to data-driven models of natural proteins learned from sequence data with Restricted Boltzmann Machines. We then use mean-field theory to characterize the properties of mutational paths for different mutational dynamics of interest, and show how it can be used to extend Kimura’s estimate of evolutionary distances to sequence-based epistatic models of selection.
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Dates et versions

hal-03645394 , version 1 (21-04-2022)
hal-03645394 , version 2 (21-10-2022)
hal-03645394 , version 3 (27-10-2022)
hal-03645394 , version 4 (06-02-2023)

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Eugenio Mauri, Simona Cocco, Rémi Monasson. Mutational paths with sequence-based models of proteins: from sampling to mean-field characterisation. 2022. ⟨hal-03645394v4⟩
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