Local energetic frustration conservation in protein families and superfamilies

Maria I. Freiberger, Victoria Ruiz-Serra, Camila Pontes, Miguel Romero-Durana, Pablo Galaz-Davison, Cesar A. Ramírez-Sarmiento, Claudio D. Schuster, Marcelo A. Marti, Peter G. Wolynes, Diego U. Ferreiro, R. Gonzalo Parra () and Alfonso Valencia
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Maria I. Freiberger: Universidad de Buenos Aires
Victoria Ruiz-Serra: Barcelona Supercomputing Center
Camila Pontes: Barcelona Supercomputing Center
Miguel Romero-Durana: Barcelona Supercomputing Center
Pablo Galaz-Davison: Pontificia Universidad Católica de Chile
Cesar A. Ramírez-Sarmiento: Pontificia Universidad Católica de Chile
Claudio D. Schuster: Universidad de Buenos Aires
Marcelo A. Marti: Universidad de Buenos Aires
Peter G. Wolynes: Rice University
Diego U. Ferreiro: Universidad de Buenos Aires
R. Gonzalo Parra: Barcelona Supercomputing Center
Alfonso Valencia: Barcelona Supercomputing Center

Nature Communications, 2023, vol. 14, issue 1, 1-14

Abstract: Abstract Energetic local frustration offers a biophysical perspective to interpret the effects of sequence variability on protein families. Here we present a methodology to analyze local frustration patterns within protein families and superfamilies that allows us to uncover constraints related to stability and function, and identify differential frustration patterns in families with a common ancestry. We analyze these signals in very well studied protein families such as PDZ, SH3, ɑ and β globins and RAS families. Recent advances in protein structure prediction make it possible to analyze a vast majority of the protein space. An automatic and unsupervised proteome-wide analysis on the SARS-CoV-2 virus demonstrates the potential of our approach to enhance our understanding of the natural phenotypic diversity of protein families beyond single protein instances. We apply our method to modify biophysical properties of natural proteins based on their family properties, as well as perform unsupervised analysis of large datasets to shed light on the physicochemical signatures of poorly characterized proteins such as the ones belonging to emergent pathogens.

Date: 2023
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DOI: 10.1038/s41467-023-43801-2

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