AlphaDesign: A graph protein design method and benchmark on AlphaFold DB

Zhangyang Gao, Cheng Tan, Stan Z. Li

Abstract: While AlphaFold has remarkably advanced protein folding, the inverse problem, protein design, by which protein sequences are predicted from the corresponding 3D structures, still faces significant challenges. First of all, there lacks a large-scale benchmark covering the vast protein space for evaluating methods and models; secondly, existing methods are still low in prediction accuracy and time-inefficient inference. This paper establishes a new benchmark based on AlphaFold DB, one of the world's largest protein structure databases. Moreover, we propose a new baseline method called AlphaDesign, which achieves 5\% higher recovery than previous methods and about 70 times inference speed-up in designing long protein sequences. We also reveal AlphaDesign's potential for practical protein design tasks, where the designed proteins achieve good structural compatibility with native structures. The open-source code will be released.

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