Predicting protein structures with a multiplayer online game

By Seth Cooper, Firas Khatib, Adrien Treuille, J. Barbero, Jeehyung Lee, Michael Beenen, Andrew Leaver-Fay, David Baker, Zoran Popovic, Foldit players. 2010

1,393 citations recorded by the source corpus.

People exert large amounts of problem-solving effort playing computer games. Simple image- and text-recognition tasks have been successfully ‘crowd-sourced’ through games, but it is not clear if more complex scientific problems can be solved with human-directed 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 methodology, 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.

Subfields: Artificial Intelligence, Communication, Sociology and Political Science, Computational Biology & Bioinformatics

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Citations in the corpus

CommonsenseQA 2.0: Exposing the Limits of AI through Gamification (2021, methodology): “Gamiﬁcation, the collection of data through a fun interactive design, was attempted by prior work for multi-choice question answering [45], image labeling [46] and protein folding [47].”
Rosetta3: An Object-Oriented Software Suite for the Simulation and Design of Macromolecules (2011, positive): “The new architecture has allowed the creation of a multithreaded, interactive game where players are given access to ROSETTA ’s minimization, packing, and loop modeling routines to compete for the best protein structure predictions (Cooper et al. , 2010).”
Interactive machine learning for health informatics: when do we need the human-in-the-loop? (2016, background): “A good example of such an approach is foldit, an experimental game which takes advantage of crowdsourcing for category discovery of new protein structures [37].”
Large Scale Visual Recognition (2012, background): “A promising direction is to explore low or zero cost approaches to crowdsourcing, in particular, online games [144].”
Best of both worlds: Human-machine collaboration for object annotation (2015, background): “The field of crowd engineering has provided lots of insight into human-machine collaboration for solving difficult problems in computing such as protein folding [41, 9], disaster relief distribution [18] and galaxy discovery [38].”
Computational Design of Ligand Binding Proteins with High Affinity and Selectivity (2013, methodology): “The latter was enforced by explicitly introducing second-shell amino acids that bolster the programmed interacting residues using Foldit 35 and by selecting designs having rotamer Boltzmann probabilities 16 .”
Hough-CNN: Deep learning for segmentation of deep brain regions in MRI and ultrasound (2016, background): “crowd-based labeling of medical images [8] and successes with “gamification” [9].”
Better together: Elements of successful scientific software development in a distributed collaborative community (2020, methodology): “For example, in 2008, the Foldit video game[29,30] was released, which uses Rosetta as a foundation and employs a graphical user interface to allow the player to manipulate a protein structure.”