ArticlePLoS computational biology2017
Inferring repeat-protein energetics from evolutionary information.
Article in PLoS computational biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Probing the dark energy in the functional protein universe.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Inferring protein-folding mechanisms from natural sequence diversity.Biophysical journal · 2025Article
- Conserved and divergent signals in 5' splice site sequences across fungi, metazoa and plants.PLoS computational biology · 2023Article
- Evolution and folding of repeat proteins.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- The Effect of Mutations in the TPR and Ankyrin Families of Alpha Solenoid Repeat Proteins.Frontiers in bioinformatics · 2021Review
- Large Ankyrin repeat proteins are formed with similar and energetically favorable units.PloS one · 2020Article
- Size and structure of the sequence space of repeat proteins.PLoS computational biology · 2019Article
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Authors and funding
5 authors.
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Abstract
Natural protein sequences contain a record of their history. A common constraint in a given protein family is the ability to fold to specific structures, and it has been shown possible to infer the main native ensemble by analyzing covariations in extant sequences. Still, many natural proteins that fold into the same structural topology show different stabilization energies, and these are often related to their physiological behavior. We propose a description for the energetic variation given by sequence modifications in repeat proteins, systems for which the overall problem is simplified by their inherent symmetry. We explicitly account for single amino acid and pair-wise interactions and treat higher order correlations with a single term. We show that the resulting evolutionary field can be interpreted with structural detail. We trace the variations in the energetic scores of natural proteins and relate them to their experimental characterization. The resulting energetic evolutionary field allows the prediction of the folding free energy change for several mutants, and can be used to generate synthetic sequences that are statistically indistinguishable from the natural counterparts.
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