De novo protein design by inversion of the AlphaFold structure prediction network.

ABSTRACT: De novo protein design enhances our understanding of the principles that govern protein folding and interactions, and has the potential to revolutionize biotechnology through the engineering of novel protein functionalities. Despite recent progress in computational design strategies, de novo design of protein structures remains challenging, given the vast size of the sequence-structure space. AlphaFold2 (AF2), a state-of-the-art neural network architecture, achieved remarkable accuracy in predicting protein structures from amino acid sequences. This raises the question whether AF2 has learned the principles of protein folding sufficiently for de novo design. Here, we sought to answer this question by inverting the AF2 network, using the prediction weight set and a loss function to bias the

SUBMITTER: Goverde CA 

PROVIDER: S-EPMC10204179 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature