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bioRxiv · 10.1101/2022.08.31.506128

OPUS-Fold3: a gradient-based protein all-atom folding and docking framework on TensorFlow

Xu, G.·Zhang, Y.·Wang, Q.·Ma, J.
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Abstract

For refining and designing protein structures, it is essential to have an efficient protein folding and docking framework that generates a protein 3D structure based on given constraints. In this study, we introduce OPUS-Fold3 as a gradient-based, all-atom protein folding and docking framework, which accurately generates 3D protein structures in compliance with specified constraints, such as a potential function as long as it can be expressed as a function of positions of heavy atoms. Our tests show that, for example, OPUS-Fold3 achieves performance comparable to pyRosetta in backbone folding, and significantly better in side-chain modeling. Developed using Python and TensorFlow 2.4, OPUS-Fold3 is user-friendly for any source-code level modifications and can be seamlessly combined with other deep learning models, thus facilitating collaboration between the biology and AI communities. The source code of OPUS-Fold3 can be downloaded from http://github.com/OPUS-MaLab/opus_fold3. It is freely available for academic usage.

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Xu, G., Zhang, Y., Wang, Q., Ma, J.. 2022-09-03. OPUS-Fold3: a gradient-based protein all-atom folding and docking framework on TensorFlow. https://doi.org/10.1101/2022.08.31.506128

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