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The Role of Local Backrub Motions in Evolved and Designed Mutations

Overview of attention for article published in PLoS Computational Biology, August 2012
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Title
The Role of Local Backrub Motions in Evolved and Designed Mutations
Published in
PLoS Computational Biology, August 2012
DOI 10.1371/journal.pcbi.1002629
Pubmed ID
Authors

Daniel A. Keedy, Ivelin Georgiev, Edward B. Triplett, Bruce R. Donald, David C. Richardson, Jane S. Richardson

Abstract

Amino acid substitutions in protein structures often require subtle backbone adjustments that are difficult to model in atomic detail. An improved ability to predict realistic backbone changes in response to engineered mutations would be of great utility for the blossoming field of rational protein design. One model that has recently grown in acceptance is the backrub motion, a low-energy dipeptide rotation with single-peptide counter-rotations, that is coupled to dynamic two-state sidechain rotamer jumps, as evidenced by alternate conformations in very high-resolution crystal structures. It has been speculated that backrubs may facilitate sequence changes equally well as rotamer changes. However, backrub-induced shifts and experimental uncertainty are of similar magnitude for backbone atoms in even high-resolution structures, so comparison of wildtype-vs.-mutant crystal structure pairs is not sufficient to directly link backrubs to mutations. In this study, we use two alternative approaches that bypass this limitation. First, we use a quality-filtered structure database to aggregate many examples for precisely defined motifs with single amino acid differences, and find that the effectively amplified backbone differences closely resemble backrubs. Second, we directly apply a provably-accurate, backrub-enabled protein design algorithm to idealized versions of these motifs, and discover that the lowest-energy computed models match the average-coordinate experimental structures. These results support the hypothesis that backrubs participate in natural protein evolution and validate their continued use for design of synthetic proteins.

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Geographical breakdown

Country Count As %
United States 4 6%
Germany 1 2%
United Kingdom 1 2%
Australia 1 2%
Peru 1 2%
Canada 1 2%
Unknown 57 86%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 21 32%
Researcher 17 26%
Student > Bachelor 7 11%
Student > Master 5 8%
Other 2 3%
Other 5 8%
Unknown 9 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 27 41%
Biochemistry, Genetics and Molecular Biology 14 21%
Chemistry 5 8%
Computer Science 3 5%
Engineering 2 3%
Other 3 5%
Unknown 12 18%