Fast and Flexible Protein Design Using Deep Graph Neural Networks

• Published in: Cell systems Vol. 11; no. 4; pp. 402 - 411.e4
• Main Authors: Strokach, Alexey, Becerra, David, Corbi-Verge, Carles, Perez-Riba, Albert, Kim, Philip M.
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 21.10.2020
• Subjects: constraint satisfaction problem; deep learning; graph neural networks; inverse protein folding; protein design; protein optimization; deep learning; graph neural networks; constraint satisfaction problem; protein optimization; inverse protein folding; protein design

Protein structure and function is determined by the arrangement of the linear sequence of amino acids in 3D space. We show that a deep graph neural network, ProteinSolver, can precisely design sequences that fold into a predetermined shape by phrasing this challenge as a constraint satisfaction prob...