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Inferring protein 3D structure from deep mutation scans

Nature genetics, 2019-07, Vol.51 (7), p.1170-1176 [Peer Reviewed Journal]

COPYRIGHT 2019 Nature Publishing Group ;COPYRIGHT 2019 Nature Publishing Group ;Copyright Nature Publishing Group Jul 2019 ;ISSN: 1061-4036 ;EISSN: 1546-1718 ;DOI: 10.1038/s41588-019-0432-9 ;PMID: 31209393

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Title:
Inferring protein 3D structure from deep mutation scans
Author: Rollins, Nathan J ; Brock, Kelly P ; Poelwijk, Frank J ; Stiffler, Michael A ; Gauthier, Nicholas P ; Sander, Chris ; Marks, Debora S
Subjects: Adaptor Proteins, Signal Transducing - chemistry ; Adaptor Proteins, Signal Transducing - genetics ; Amino acid sequence ; Amino acids ; Bacterial Proteins - chemistry ; Bacterial Proteins - genetics ; Biological evolution ; Crystal structure ; Epistasis ; Epistasis, Genetic ; Experiments ; Gene mutations ; Genetic epistasis ; Genetic screening ; Genomics ; Genotype & phenotype ; Humans ; Laboratories ; Macromolecules ; Mutants ; Mutation ; Nucleotide sequence ; Poly(A)-Binding Proteins - chemistry ; Poly(A)-Binding Proteins - genetics ; Protein Conformation ; Protein Domains ; Protein Folding ; Protein structure ; Proteins ; Ribonucleic acid ; RNA ; RNA, Catalytic - chemistry ; RNA, Catalytic - genetics ; Saccharomyces cerevisiae Proteins - chemistry ; Saccharomyces cerevisiae Proteins - genetics ; Transcription Factors - chemistry ; Transcription Factors - genetics
Is Part Of: Nature genetics, 2019-07, Vol.51 (7), p.1170-1176
Description: 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.
Publisher: United States: Nature Publishing Group
Language: English
Identifier: ISSN: 1061-4036
EISSN: 1546-1718
DOI: 10.1038/s41588-019-0432-9
PMID: 31209393
Source: Geneva Foundation Free Medical Journals at publisher websites
MEDLINE
ProQuest Central

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Inferring protein 3D structure from deep mutation scans

COPYRIGHT 2019 Nature Publishing Group ;COPYRIGHT 2019 Nature Publishing Group ;Copyright Nature Publishing Group Jul 2019 ;ISSN: 1061-4036 ;EISSN: 1546-1718 ;DOI: 10.1038/s41588-019-0432-9 ;PMID: 31209393

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