ArticleNature genetics2019
Determining protein structures using deep mutagenesis.
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 90 papers.
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Who cites it
90 citing papers in PubMed.
- Inference of fitness landscapes with heterogeneous patterns of epistasis across sites.bioRxiv : the preprint server for biology · 2026Article
- Article
- Deep learning-guided dual-fitness evolution of T7 RNA polymerase for enhanced stability and activity.Nucleic acids research · 2026Article
- 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
- Dynamic Allostery: Evolution's Double-Edged Sword in Protein Function and Disease.Journal of molecular biology · 2025Review
- Distinguishing direct interactions from global epistasis using rank statistics.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Employing deep mutational scanning in theProceedings 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
- AI based natural inhibitor targeting RPS20 for colorectal cancer treatment using integrated computational approaches.Scientific reports · 2025Article
- Massively parallel genetic perturbation suggests the energetic structure of an amyloid-β transition state.Science advances · 2025Article
- Current perspectives in drug targeting intrinsically disordered proteins and biomolecular condensates.BMC biology · 2025Review
- 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
- A deep mutational scanning platform to characterize the fitness landscape of anti-CRISPR proteins.Nucleic acids research · 2024Article
- 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
- Deciphering GB1's Single Mutational Landscape: Insights from MuMi Analysis.The journal of physical chemistry. B · 2024Article
- Sampling Strategies for Experimentally Mapping Molecular Fitness Landscapes Using High-Throughput Methods.Journal of molecular evolution · 2024Article
30 more citing papers are in PubMed but not listed here.
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Authors and funding
2 authors.
Funding
Abstract
Determining the three-dimensional structures of macromolecules is a major goal of biological research, because of the close relationship between structure and function; however, thousands of protein domains still have unknown structures. Structure determination usually relies on physical techniques including X-ray crystallography, NMR spectroscopy and cryo-electron microscopy. Here we present a method that allows the high-resolution three-dimensional backbone structure of a biological macromolecule to be determined only from measurements of the activity of mutant variants of the molecule. This genetic approach to structure determination relies on the quantification of genetic interactions (epistasis) between mutations and the discrimination of direct from indirect interactions. This provides an alternative experimental strategy for structure determination, with the potential to reveal functional and in vivo structures.
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