Concept

Foldit

Foldit is an online puzzle video game about protein folding. It is part of an experimental research project developed by the University of Washington, Center for Game Science, in collaboration with the UW Department of Biochemistry. The objective of Foldit is to fold the structures of selected proteins as perfectly as possible, using tools provided in the game. The highest scoring solutions are analyzed by researchers, who determine whether or not there is a native structural configuration (native state) that can be applied to relevant proteins in the real world. Scientists can then use these solutions to target and eradicate diseases and create biological innovations. A 2010 paper in the science journal Nature credited Foldit's 57,000 players with providing useful results that matched or outperformed algorithmically computed solutions. Prof. David Baker, a protein research scientist at the University of Washington, founded the Foldit project. Seth Cooper was the lead game designer. Before starting the project, Baker and his laboratory coworkers relied on another research project named Rosetta to predict the native structures of various proteins using special computer protein structure prediction algorithms. Rosetta was eventually extended to use the power of distributed computing: The Rosetta@home program was made available for public download, and displayed its protein-folding progress as a screensaver. Its results were sent to a central server for verification. Some Rosetta@home users became frustrated when they saw ways to solve protein structures, but could not interact with the program. Hoping that humans could improve the computers' attempts to solve protein structures, Baker approached David Salesin and Zoran Popović, computer science professors at the same university, to help conceptualize and build an interactive program, a video game, that would appeal to the public and help efforts to find native protein structures. Many of the same people who created Rosetta@home worked on Foldit.

About this result
This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.
Related lectures (7)
Protein Structure Prediction
Explores predicting protein structure from sequence data using maximum entropy modeling and discusses recent advancements in protein structure prediction.
Protein Folding: Basics and Models
Explores protein folding basics, stability, mutations, and computational methods.
Metabolic Engineering: Systems Biology and Tools
Explores systems biology of metabolism, genome-scale models, and metabolic engineering applications.
Show more
Related publications (30)

Protein target highlights in CASP15: Analysis of models by structure providers

Bruno Lemaitre, Luciano Andres Abriata, Samuel Rommelaere, Kuan-Lin Wu, Han Xiao

We present an in-depth analysis of selected CASP15 targets, focusing on their biological and functional significance. The authors of the structures identify and discuss key protein features and evaluate how effectively these aspects were captured in the su ...
WILEY2023

Bridging Native and Intrinsic Structures of Microhydrated Biomolecules by Cold Ion Spectroscopy

Andrei Zviagin

Solving native structures of such large molecules, like biomolecules, is often challenging, particularly due to the potentially infinite number of non-covalent interactions with water. In this thesis, we report the use of cold ion gas-phase action spectros ...
EPFL2023

A generic framework for hierarchical de novo protein design

Bruno Emanuel Ferreira De Sousa Correia, Zander Harteveld, Jaume Bonet Martinez, Fabian Sesterhenn, Stéphane Rosset, Che Yang

De novo protein design enables the exploration of novel sequences and structures absent from the natural protein universe. De novo design also stands as a stringent test for our understanding of the underlying physical principles of protein folding and may ...
NATL ACAD SCIENCES2022
Show more
Related concepts (4)
Folding@home
Folding@home (FAH or F@h) is a distributed computing project aimed to help scientists develop new therapeutics for a variety of diseases by the means of simulating protein dynamics. This includes the process of protein folding and the movements of proteins, and is reliant on simulations run on volunteers' personal computers. Folding@home is currently based at the University of Pennsylvania and led by Greg Bowman, a former student of Vijay Pande.
Protein design
Protein design is the rational design of new protein molecules to design novel activity, behavior, or purpose, and to advance basic understanding of protein function. Proteins can be designed from scratch (de novo design) or by making calculated variants of a known protein structure and its sequence (termed protein redesign). Rational protein design approaches make protein-sequence predictions that will fold to specific structures.
Citizen science
Citizen science (similar to community science, crowd science, crowd-sourced science, civic science, participatory monitoring, or volunteer monitoring) is scientific research conducted with participation from the general public (who are sometimes referred to as amateur/nonprofessional scientists). There are variations in the exact definition of citizen science, with different individuals and organizations having their own specific interpretations of what citizen science encompasses.
Show more

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.