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Accurate positioning of functional residues with robotics-inspired computational protein design

Cody Krivacic, Kale Kundert, Xingjie Pan, Roland A. Pache, Lin Liu, Shane Ó Conchúir, Jeliazko R. Jeliazkov, Jeffrey J. Gray, Michael C. Thompson, James S. Fraser, Tanja Kortemme

发表年份
2022
引用次数
10

摘要

SignificanceComputational protein design promises to advance applications in medicine and biotechnology by creating proteins with many new and useful functions. However, new functions require the design of specific and often irregular atom-level geometries, which remains a major challenge. Here, we develop computational methods that design and predict local protein geometries with greater accuracy than existing methods. Then, as a proof of concept, we leverage these methods to design new protein conformations in the enzyme ketosteroid isomerase that change the protein's preference for a key functional residue. Our computational methods are openly accessible and can be applied to the design of other intricate geometries customized for new user-defined protein functions.

关键词

Protein designLeverage (statistics)Computer scienceArtificial intelligenceProtein engineeringRoboticsComputational biologyProtein structureMachine learningBiology

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