Applying Protein Databases to Crowdsourcing Structural Protein Design

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 DESCRIPTION (provided by applicant): The design of novel synthetic proteins is a key challenge in computational biochemistry with the potential to lead to a better understanding of the processes that underlie life and allow the discovery of molecules with applications in therapeutics, materials, and scientific tools. However, due to the high number of degrees of freedom and rugged energy landscape in even small proteins, protein design remains a challenging computational problem. Researchers have begun turning to video games as a means to crowdsource human problem solving for proteomics at a mass scale. This project aims to significantly adapt the existing proteomics video game Foldit to incorporate big data from protein databases into computational structural protein design. This data will be used to inform the manipulation of structural components of proteins. Foldit, a scientific discovery game featuring an interactive protein manipulation interface, allows the public to contribute directly t scientific research involving the study of proteins. Previous work with Foldit has shown that with an appropriate interface and introduction, even amateur players with no formal background in biochemistry can make contributions to our knowledge of proteomics. Additionally, preliminary protein design work has shown that players can contribute to the successful redesign of existing protein enzymes. In this work we propose to build upon the existing successes of Foldit in crowdsourcing protein design. To do so, we will leverage the huge amount of data on protein structures that exists in protein databases like the RCSB Protein Data Bank. By integrating this data into the mechanics of the Foldit game, we will be able to both improve the tools available to the players and allow them to construct more realistic protein-like structures. We will additionall be able to reward players for staying closer to these structures when making future modifications and for finding novel sequences that do not exist in databases.