ArticleNature genetics2019
Inferring protein 3D structure from deep mutation scans.
Article in Nature genetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 83 papers.
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Who cites it
83 citing papers in PubMed.
- Hierarchical Organization of Evolutionary Constraint in Duplicated EF-Hand Motifs.Journal of molecular evolution · 2026Article
- Article
- Concentration-dependent mutational scanning probes the cellular folding landscape of α-synuclein in yeast.Protein science : a publication of the Protein Society · 2026Article
- Concentration-Dependent Mutational Scanning Probes the Cellular Folding Landscape of α-Synuclein in Yeast.bioRxiv : the preprint server for biology · 2025Article
- Epistatic drift in protein evolution.Current opinion in genetics & development · 2025Review
- Dynamic Allostery: Evolution's Double-Edged Sword in Protein Function and Disease.Journal of molecular biology · 2025Review
- Deep Mutational Scanning in Immunology: Techniques and Applications.Pathogens (Basel, Switzerland) · 2025Review
- Distinguishing direct interactions from global epistasis using rank statistics.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Adaptive genetics reveals constraints on protein structure/function by evolving E. coli under constant nutrient limitation.BMC biology · 2025Article
- Deep-learning structure elucidation from single-mutant deep mutational scanning.Nature communications · 2025Article
- Multi-dimensional annotation of porcine variants using genomic and epigenomic features in pigs.BMC biology · 2025Article
- Deep mutational scanning of the multi-domain phosphatase SHP2 reveals mechanisms of regulation and pathogenicity.Nature communications · 2025Article
- Massively parallel genetic perturbation suggests the energetic structure of an amyloid-β transition state.Science advances · 2025Article
- An easy-to-use three-dimensional protein-structure-prediction online platform "DPL3D" based on deep learning algorithms.Current research in structural biology · 2025Article
- Resolving discrepancies between chimeric and multiplicative measures of higher-order epistasis.Nature communications · 2025Article
- MaveDB 2024: a curated community database with over seven million variant effects from multiplexed functional assays.Genome biology · 2025Article
- AlphaFold2, SPINE-X, and Seder on Four Hard CASP Targets.Methods in molecular biology (Clifton, N.J.) · 2025Article
- Combining Oligo Pools and Golden Gate Cloning to Create Protein Variant Libraries or Guide RNA Libraries for CRISPR Applications.Methods in molecular biology (Clifton, N.J.) · 2025Article
- MoCHI: neural networks to fit interpretable models and quantify energies, energetic couplings, epistasis, and allostery from deep mutational scanning data.Genome biology · 2024Article
- The genetic architecture of protein stability.Nature · 2024Article
23 more citing papers are in PubMed but not listed here.
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7 authors.
Funding
Abstract
We describe an experimental method of three-dimensional (3D) structure determination that exploits the increasing ease of high-throughput mutational scans. Inspired by the success of using natural, evolutionary sequence covariation to compute protein and RNA folds, we explored whether 'laboratory', synthetic sequence variation might also yield 3D structures. We analyzed five large-scale mutational scans and discovered that the pairs of residues with the largest positive epistasis in the experiments are sufficient to determine the 3D fold. We show that the strongest epistatic pairings from genetic screens of three proteins, a ribozyme and a protein interaction reveal 3D contacts within and between macromolecules. Using these experimental epistatic pairs, we compute ab initio folds for a GB1 domain (within 1.8 Å of the crystal structure) and a WW domain (2.1 Å). We propose strategies that reduce the number of mutants needed for contact prediction, suggesting that genomics-based techniques can efficiently predict 3D structure.
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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.