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5UYO

Solution NMR structure of the de novo mini protein HEEH_rd4_0097

Summary for 5UYO
Entry DOI10.2210/pdb5uyo/pdb
NMR InformationBMRB: 30249
DescriptorHEEH_rd4_0097 (1 entity in total)
Functional Keywordsde novo design, helix-strand-strand-helix, mini protein, de novo protein
Biological sourceEscherichia coli
Total number of polymer chains1
Total formula weight7469.42
Authors
Lemak, A.,Rocklin, G.J.,Houliston, S.,Carter, L.,Chidyausiku, T.M.,Baker, D.,Arrowsmith, C.H. (deposition date: 2017-02-24, release date: 2017-07-26, Last modification date: 2024-05-15)
Primary citationRocklin, G.J.,Chidyausiku, T.M.,Goreshnik, I.,Ford, A.,Houliston, S.,Lemak, A.,Carter, L.,Ravichandran, R.,Mulligan, V.K.,Chevalier, A.,Arrowsmith, C.H.,Baker, D.
Global analysis of protein folding using massively parallel design, synthesis, and testing.
Science, 357:168-175, 2017
Cited by
PubMed Abstract: Proteins fold into unique native structures stabilized by thousands of weak interactions that collectively overcome the entropic cost of folding. Although these forces are "encoded" in the thousands of known protein structures, "decoding" them is challenging because of the complexity of natural proteins that have evolved for function, not stability. We combined computational protein design, next-generation gene synthesis, and a high-throughput protease susceptibility assay to measure folding and stability for more than 15,000 de novo designed miniproteins, 1000 natural proteins, 10,000 point mutants, and 30,000 negative control sequences. This analysis identified more than 2500 stable designed proteins in four basic folds-a number sufficient to enable us to systematically examine how sequence determines folding and stability in uncharted protein space. Iteration between design and experiment increased the design success rate from 6% to 47%, produced stable proteins unlike those found in nature for topologies where design was initially unsuccessful, and revealed subtle contributions to stability as designs became increasingly optimized. Our approach achieves the long-standing goal of a tight feedback cycle between computation and experiment and has the potential to transform computational protein design into a data-driven science.
PubMed: 28706065
DOI: 10.1126/science.aan0693
PDB entries with the same primary citation
Experimental method
SOLUTION NMR
Structure validation

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