People exert large amounts of problem-solving effort playing computer
games. Simple image- and text-recognition tasks have been
successfully ‘crowd-sourced’ through games1–3, but it is not clear if
more complex scientific problems can be solved with humandirected
computing. Protein structure prediction is one such
problem: locating the biologically relevant native conformation
of a protein is a formidable computational challenge given the
very large size of the search space. Here we describe Foldit, a
multiplayer online game that engages non-scientists in solving
hard prediction problems. Foldit players interact with protein
structures using direct manipulation tools and user-friendly
versions of algorithms from the Rosetta structure prediction
methodology4, while they compete and collaborate to optimize
the computed energy. We show that top-ranked Foldit players
excel at solving challenging structure refinement problems in
which substantial backbone rearrangements are necessary to
achieve the burial of hydrophobic residues. Players working
collaboratively develop a rich assortment of new strategies and
algorithms; unlike computational approaches, they explore not
only the conformational space but also the space of possible search
strategies. The integration of human visual problem-solving and
strategy development capabilities with traditional computational
algorithms through interactive multiplayer games is a powerful
new approach to solving computationally-limited scientific
problems.
http://www.nature.com/nature/journal/v466/n7307/edsumm/e100805-10.html
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