ReviewCurrent opinion in structural biology2017
Potts Hamiltonian models of protein co-variation, free energy landscapes, and evolutionary fitness.
Review in Current opinion in structural biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 63 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
63 citing papers in PubMed.
- Protein stability is determined by single-site bias rather than pairwise covariance.Nature chemical biology · 2026Article
- Beyond native sequence recovery: Improved modeling of the sequence-energy landscape of protein structures.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Epistasis plays a limited role in driving entrenchment during neutral protein evolution.Genome biology · 2026Article
- Detecting and quantifying overparametrization in RNA language models with REDIAL.bioRxiv : the preprint server for biology · 2026Article
- Review
- Results of a Large-Scale Study of the Binding of 50 Type II Inhibitors to 348 Kinases: The Role of Protein Reorganization.Journal of medicinal chemistry · 2026Article
- Generative Artificial Intelligence-Empowered Virtual Evolution of Enzyme with the VERnet Model.ACS catalysis · 2026Article
- Structural ontogeny of protein-protein interactions.Science (New York, N.Y.) · 2026Article
- Results of a large scale study of the binding of 50 type II inhibitors to 348 kinases: The role of protein reorganization.bioRxiv : the preprint server for biology · 2026Article
- Beyond native sequence recovery: Improved modeling of the sequence-energy landscape of protein structures.bioRxiv : the preprint server for biology · 2026Article
- Phylogenetic corrections and higher-order sequence statistics in protein families: Potts vs multiple sequence alignment transformer machine learning models.Physical review research · 2025Article
- Predicting side chain conformations in folded proteins by AlphaFold: Perspective and challenges.Biophysical journal · 2025Article
- Second-order allosteric control as a mechanism for compensatory mutations in B-cell translocation gene 2.Protein science : a publication of the Protein Society · 2025Article
- Generative Landscapes and Dynamics to Design Functional Multidomain Artificial Transmembrane Transporters.ACS central science · 2025Article
- Using AlphaFold2 to Predict the Conformations of Side Chains in Folded Proteins.bioRxiv : the preprint server for biology · 2025Article
- How the technologies behind self-driving cars, social networks, ChatGPT, and DALL-E2 are changing structural biology.BioEssays : news and reviews in molecular, cellular and developmental biology · 2025Review
- Generating Artificial Ribozymes Using Sparse Coevolutionary Models.Methods in molecular biology (Clifton, N.J.) · 2025Article
- Article
- Density estimation for ordinal biological sequences and its applications.Physical review. E · 2024Article
- Insertions and Deletions: Computational Methods, Evolutionary Dynamics, and Biological Applications.Molecular biology and evolution · 2024Review
3 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
3 authors.
Funding
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.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.