ArticleNature communications2023
Local energetic frustration conservation in protein families and superfamilies.
Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
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Who cites it
32 citing papers in PubMed.
- The protein-water H-bond network for bacterial response regulator REC domain activation.Journal of structural biology: X · 2026Article
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- How to frustrate a plant pathogen.The Plant journal : for cell and molecular biology · 2026Review
- Exploration of the structural and functional diversity in the metamorphic RfaH subfamily.bioRxiv : the preprint server for biology · 2026Article
- AF2BIND: predicting small-molecule binding sites using the pair representation of AlphaFold2.Nature methods · 2026Article
- Deconvolving mutation effects on protein stability and function with disentangled protein language models.bioRxiv : the preprint server for biology · 2026Article
- Residue-level determinants of the thermal stability of the extremophilic Ts2631 endolysin.Scientific reports · 2026Article
- Probing the dark energy in the functional protein universe.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Structural analysis of antigenic variation and adaptive evolution of the H5N1 neuraminidase gene.PLoS computational biology · 2026Article
- Predicting Protein Folding Dynamics Using Sequence Information.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Prostate cancer risk-associated single-nucleotide polymorphisms impact the conformational dynamics of prostate-specific antigen.BMC biology · 2025Article
- Support field neural representation learner framework for learning stability landscapes in molecular geometry.npj biomedical innovations · 2025Article
- Neutral Frustration Landscape Architecture of SARS-CoV-2 Spike-Antibody Interfaces Shapes Immune Evasion Mechanisms for Ultrapotent Neutralizing Antibodies and Determines Pathways of Viral Adaptation: Insights from Integrative Computational Approach.bioRxiv : the preprint server for biology · 2025Article
- Mapping the energy landscape of a fold-switching protein MAD2.Protein science : a publication of the Protein Society · 2025Article
- DIVERGE v4: A Platform for Large-Scale Analysis of Functional Divergence Across Multi-Gene Families.Molecular biology and evolution · 2025Article
- The Evolving Landscape of Protein Allostery: From Computational and Experimental Perspectives.Journal of molecular biology · 2025Review
- Multi-Modal Topology-Aware Graph Neural Network for Robust Chemical-Protein Interaction Prediction.International journal of molecular sciences · 2025Article
- An AlphaFold guided model for the evolution of the CaMKII interactome.bioRxiv : the preprint server for biology · 2025Article
- Inferring protein-folding mechanisms from natural sequence diversity.Biophysical journal · 2025Article
- Computational and experimental assessment of key interdomain residues controlling the fold-switch of RfaH.Protein science : a publication of the Protein Society · 2025Article
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Authors and funding
12 authors.
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No grant is acknowledged in the PubMed record.
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.
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