Determining crystal structures through crowdsourcing and coursework
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Determining crystal structures through crowdsourcing and coursework. / Foldit Players.
In: Nature Communications, Vol. 7, 2016, p. 12549.Research output: Contribution to journal › Journal article › Research › peer-review
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TY - JOUR
T1 - Determining crystal structures through crowdsourcing and coursework
AU - Horowitz, Scott
AU - Koepnick, Brian
AU - Martin, Raoul
AU - Tymieniecki, Agnes
AU - Winburn, Amanda A
AU - Cooper, Seth
AU - Flatten, Jeff
AU - Rogawski, David S
AU - Koropatkin, Nicole M
AU - Hailu, Tsinatkeab T
AU - Jain, Neha
AU - Koldewey, Philipp
AU - Ahlstrom, Logan S
AU - Chapman, Matthew R
AU - Sikkema, Andrew P
AU - Skiba, Meredith A
AU - Maloney, Finn P
AU - Beinlich, Felix R.M.
AU - Popović, Zoran
AU - Baker, David
AU - Khatib, Firas
AU - Bardwell, James C A
AU - Foldit Players
PY - 2016
Y1 - 2016
N2 - 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.
AB - 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.
KW - Crowdsourcing/methods
KW - Crystallography/methods
KW - Curriculum
KW - Hydrolases/chemistry
KW - Models, Chemical
KW - Protein Conformation
KW - Software
U2 - 10.1038/ncomms12549
DO - 10.1038/ncomms12549
M3 - Journal article
C2 - 27633552
VL - 7
SP - 12549
JO - Nature Communications
JF - Nature Communications
SN - 2041-1723
ER -
ID: 209744227