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BioinformaticsbioRxiv
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GYDE: A collaborative drug discovery platform for AI-powered protein design and engineering

Thomas A. DowniD, Mateusz WarownyiD, April Walker, Luigi D’AscenzoiD, Donald Lee, Zhenru Zhou, Shengya CaoiD, Travis W. BainbridgeiD, John M. NicoludisiD, Seth F. HarrisiD, Kiran MukhyalaiD

Abstract

As computational tools and machine learning models for protein sciences continue to advance and proliferate, bench scientists face increasing technical challenges adopting these tools for specific applications such as drug discovery. Here we present GYDE (Guide Your Design and Engineering), an open-source, versatile, and web-based collaboration platform designed to make computational analyses of proteins and antibodies easily accessible to bench scientists. GYDE enables the exploration of sequence-structure-function relationships through a tightly integrated visual interface, offering researchers a comprehensive exploration of protein functional determinants either via real assay data or computational tools. GYDEs intuitive interface facilitates seamless access to cutting-edge AI models for protein and antibody structure prediction, design, and downstream analyses. The flexible and easy addition of new tools and models is facilitated by the use of the Slivka compute API. The platform supports saved sessions that enable researchers to easily share their findings with other users, fostering a more collaborative scientific community. GYDE is freely available for protein scientists in academia and industry to build drug discovery analytics platforms customized to their needs.

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