Determining crystal structures through crowdsourcing and coursework
We show here that computer game players can build high-quality crystal structures. Introduction of a new feature into the computer game Foldit allows players to build and real-space refine structures into electron density maps. To assess the usefulness of this feature, we held a crystallographic mod...
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Veröffentlicht in: | Nature communications 2016-09, Vol.7 (1), p.12549-11, Article 12549 |
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Sprache: | eng |
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Zusammenfassung: | We show here that computer game players can build high-quality crystal structures. Introduction of a new feature into the computer game Foldit allows players to build and real-space refine structures into electron density maps. To assess the usefulness of this feature, we held a crystallographic model-building competition between trained crystallographers, undergraduate students, Foldit players and automatic model-building algorithms. After removal of disordered residues, a team of Foldit players achieved the most accurate structure. Analysing the target protein of the competition, YPL067C, uncovered a new family of histidine triad proteins apparently involved in the prevention of amyloid toxicity. From this study, we conclude that crystallographers can utilize crowdsourcing to interpret electron density information and to produce structure solutions of the highest quality.
Building crystal structures into the electron density is an important step in protein structure solution. Here, the authors recruit online game players, students, and experienced crystallographers to compete in a competition to solve a new structure, and find that crowdsourcing model-building works. |
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ISSN: | 2041-1723 2041-1723 |
DOI: | 10.1038/ncomms12549 |