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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.<\/jats:p>","DOI":"10.1093\/bib\/bbad365","type":"journal-article","created":{"date-parts":[[2023,9,25]],"date-time":"2023-09-25T14:20:10Z","timestamp":1695651610000},"source":"Crossref","is-referenced-by-count":2,"title":["OPUS-Fold3: a gradient-based protein all-atom folding and docking framework on TensorFlow"],"prefix":"10.1093","volume":"24","author":[{"given":"Gang","family":"Xu","sequence":"first","affiliation":[{"name":"Fudan University Multiscale Research Institute of Complex Systems, , Shanghai, 200433 , China"},{"name":"Fudan University Zhangjiang Fudan International Innovation Center, , Shanghai, 201210 , China"},{"name":"Shanghai AI Laboratory , Shanghai, 200030 , China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhenwei","family":"Luo","sequence":"additional","affiliation":[{"name":"Fudan University Multiscale Research Institute of Complex Systems, , Shanghai, 200433 , China"},{"name":"Fudan University 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