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The Proteome Folding Project: Proteome-scale prediction of structure and function
Author(s) -
Kevin Drew,
Patrick Winters,
Glenn L. Butterfoss,
Viktors Berstis,
Keith Uplinger,
Jonathan K. Armstrong,
Michael Riffle,
Erik Schweighofer,
Bill Bovermann,
David R. Goodlett,
Trisha N. Davis,
Dennis Shasha,
Lars Malmström,
Richard Bonneau
Publication year - 2011
Publication title -
genome research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 9.556
H-Index - 297
eISSN - 1549-5469
pISSN - 1088-9051
DOI - 10.1101/gr.121475.111
Subject(s) - proteome , biology , computational biology , annotation , genome , pipeline (software) , function (biology) , structural genomics , folding (dsp implementation) , gene prediction , computer science , bioinformatics , gene , genetics , protein structure , biochemistry , electrical engineering , programming language , engineering
The incompleteness of proteome structure and function annotation is a critical problem for biologists and, in particular, severely limits interpretation of high-throughput and next-generation experiments. We have developed a proteome annotation pipeline based on structure prediction, where function and structure annotations are generated using an integration of sequence comparison, fold recognition, and grid-computing-enabled de novo structure prediction. We predict protein domain boundaries and three-dimensional (3D) structures for protein domains from 94 genomes (including human, Arabidopsis , rice, mouse, fly, yeast, Escherichia coli , and worm). De novo structure predictions were distributed on a grid of more than 1.5 million CPUs worldwide (World Community Grid). We generated significant numbers of new confident fold annotations (9% of domains that are otherwise unannotated in these genomes). We demonstrate that predicted structures can be combined with annotations from the Gene Ontology database to predict new and more specific molecular functions.

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