Technical Report of HelixFold3 for Biomolecular Structure Prediction
<|reference_start|>Technical Report of HelixFold3 for Biomolecular Structure Prediction: The AlphaFold series has transformed protein structure prediction with remarkable accuracy, often matching experimental methods. AlphaFold2, AlphaFold-Multimer, and the latest AlphaFold3 represent significant strides in predicting single protein chains, protein complexes, and biomolecular structures. While AlphaFold2 and AlphaFold-Multimer are open-sourced, facilitating rapid and reliable predictions, AlphaFold3 remains partially accessible through a limited online server and has not been open-sourced, restricting further development. To address these challenges, the PaddleHelix team is developing HelixFold3, aiming to replicate AlphaFold3's capabilities. Using insights from previous models and extensive datasets, HelixFold3 achieves an accuracy comparable to AlphaFold3 in predicting the structures of conventional ligands, nucleic acids, and proteins. The initial release of HelixFold3 is available as open source on GitHub for academic research, promising to advance biomolecular research and accelerate discoveries. We also provide online service at PaddleHelix website at https://paddlehelix.baidu.com/app/all/helixfold3/forecast.<|reference_end|>
@article{liu2024technical,
    title={Technical Report of HelixFold3 for Biomolecular Structure Prediction},
    author={Lihang Liu, Shanzhuo Zhang, Yang Xue, Xianbin Ye, Kunrui Zhu, Yuxin
  Li, Yang Liu, Wenlai Zhao, Hongkun Yu, Zhihua Wu, Xiaonan Zhang, Xiaomin Fang},
    journal={arXiv preprint arXiv:2408.16975},
    year={2024},
    archivePrefix={arXiv},
    eprint={2408.16975},
    primaryClass={q-bio.BM cs.AI cs.LG}
}