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Nat Commun. 2016 Sep 16;7:12549. doi: 10.1038/ncomms12549.

Determining crystal structures through crowdsourcing and coursework.

Collaborators (165)

Caglar A, Coral A, Jensen AE, Lubow A, Boitano A, Lisle AE, Maxwell AT, Failer B, Kaszubowski B, Hrytsiv B, Vincenzo B, de Melo Cruz BR, McManus BJ, Kestemont B, Vardeman C, Comisky C, Neilson C, Landers CR, Ince C, Buske DJ, Totonjian D, Copeland DM, Murray D, Jagieła D, Janz D, Wheeler DC, Cali E, Croze E, Rezae F, Martin FO, Beecher G, de Jong GA, Ykman G, Feldmann H, Chan HP, Kovanecz I, Vasilchenko I, Connellan JC, Borman JL, Norrgard J, Kanfer J, Canfield JM, Slone JD, Oh J, Mitchell J, Bishop J, Kroeger JD, Schinkler J, McLaughlin J, Brownlee JM, Bell J, Fellbaum KW, Harper K, Abbey KJ, Isaksson LE, Wei L, Cummins LN, Miller LA, Bain L, Carpenter L, Desnouck M, Sharma MG, Belcastro M, Szew M, Szew M, Britton M, Gaebel M, Power M, Cassidy M, Pfützenreuter M, Minett M, Wesselingh M, Yi M, Cameron NH, Bolibruch NI, Benevides N, Kathleen Kerr N, Barlow N, Crevits NK, Dunn P, Silveira Belo Nascimento Roque PS, Riber P, Pikkanen P, Shehzad R, Viosca R, James Fraser R, Leduc R, Madala R, Shnider S, de Boisblanc S, Butkovich S, Bliven S, Hettler S, Telehany S, Schwegmann SA, Parkes S, Kleinfelter SC, Michael Holst S, van der Laan TJ, Bausewein T, Simon V, Pulley W, Hull W, Kim AY, Lawton A, Ruesch A, Sundar A, Lawrence AL, Afrin A, Maheshwer B, Turfe B, Huebner C, Killeen CE, Antebi-Lerrman D, Luan D, Wolfe D, Pham D, Michewicz E, Hull E, Pardington E, Galal GO, Sun G, Chen G, Anderson HE, Chang J, Hewlett JT, Sterbenz J, Lim J, Morof J, Lee J, Inn JS, Hahm K, Roth K, Nair K, Markin K, Schramm K, Toni Eid K, Gam K, Murphy L, Yuan L, Kana L, Daboul L, Shammas MK, Chason M, Sinan M, Andrew Tooley N, Korakavi N, Comer P, Magur P, Savliwala Q, Davison RM, Sankaran RR, Lewe S, Tamkus S, Chen S, Harvey S, Hwang SY, Vatsia S, Withrow S, Luther TK, Manett T, Johnson TJ, Ryan Brash T, Kuhlman W, Park Y.

Author information

1
Department of Molecular, Cellular, and Developmental Biology, University of Michigan, Ann Arbor, Michigan 48109, USA.
2
Howard Hughes Medical Institute, University of Michigan, Ann Arbor, Michigan 48109, USA.
3
Department of Biochemistry, University of Washington, Seattle, Washington 98195, USA.
4
Biophysics Graduate Group, University of California, Berkeley, California 94720, USA.
5
Center for Complex Networks and Systems Research, Department of Informatics, Indiana University, Bloomington, Indiana 47408, USA.
6
Program in Cognitive Science, Indiana University, 1900 E 10th Street, Bloomington, Indiana 47406, USA.
7
Northeastern University, College of Computer and Information Science, Boston, Massachusetts 02115, USA.
8
Department of Computer Science and Engineering, Center for Game Science, University of Washington, Seattle, Washington 98195, USA.
9
Department of Pathology, University of Michigan, Ann Arbor, Michigan 48109, USA.
10
Department of Microbiology and Immunology, University of Michigan, Ann Arbor, Michigan 48109, USA.
11
ProQR Therapeutics NV., 2333 Leiden, The Netherlands.
12
Department of Biological Chemistry and Life Sciences Institute, University of Michigan, Ann Arbor, Michigan 48109, USA.
13
Chemical Biology Doctoral Program, University of Michigan, Ann Arbor, Michigan 48109, USA.
14
Institute of Complex Systems, Cellular Biophysics (ICS-4), Forschungszentrum, D-52428 Jülich, Germany.
15
Institute for Protein Design, University of Washington, Seattle, Washington 98195, USA.
16
Howard Hughes Medical Institute, University of Washington, Seattle, Washington 98195, USA.
17
Department of Computer and Information Science, University of Massachusetts Dartmouth, Dartmouth, Massachusetts 02747, USA.

Abstract

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.

PMID:
27633552
PMCID:
PMC5028414
DOI:
10.1038/ncomms12549
[Indexed for MEDLINE]
Free PMC Article

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