1. Inferring protein 3D structure from deep mutation scans.
- Author
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Rollins NJ, Brock KP, Poelwijk FJ, Stiffler MA, Gauthier NP, Sander C, and Marks DS
- Subjects
- Adaptor Proteins, Signal Transducing genetics, Bacterial Proteins genetics, Humans, Poly(A)-Binding Proteins genetics, Protein Domains, Protein Folding, RNA, Catalytic genetics, Saccharomyces cerevisiae Proteins genetics, Transcription Factors genetics, YAP-Signaling Proteins, Adaptor Proteins, Signal Transducing chemistry, Bacterial Proteins chemistry, Epistasis, Genetic, Mutation, Poly(A)-Binding Proteins chemistry, Protein Conformation, RNA, Catalytic chemistry, Saccharomyces cerevisiae Proteins chemistry, Transcription Factors chemistry
- 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.
- Published
- 2019
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