Technical Report of HelixFold3 for Biomolecular Structure Prediction

Lihang Liu, Shanzhuo Zhang, Yang Xue, Xianbin Ye, Kunrui Zhu, Yuxin Li, Yang Liu, Xiaonan Zhang, Xiaomin Fang
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Abstract

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.
用于生物分子结构预测的 HelixFold3 技术报告
AlphaFold 系列已经改变了蛋白质结构预测的方式,其准确性令人惊叹,往往与实验方法不相上下。AlphaFold2、AlphaFold-Multimer 和最新的 AlphaFold3 在预测单个蛋白质链、蛋白质复合物和生物分子结构方面取得了重大进展。AlphaFold2和AlphaFold-Multimer已经开源,为快速可靠的预测提供了便利,但AlphaFold3仍可通过有限的在线服务器部分访问,且尚未开源,限制了进一步发展。为了应对这些挑战,PaddleHelixt 团队正在开发 HelixFold3,旨在复制 AlphaFold3 的功能。HelixFold3 利用从以前的模型和大量数据集中获得的洞察力,在预测常规配体、核酸和蛋白质结构方面达到了与 AlphaFold3 相当的准确性。HelixFold3的初始版本已在GitHub上开源,供学术研究使用,有望推动生物分子研究并加速发现。我们还在 PaddleHelix 网站(https://paddlehelix.baidu.com/app/all/helixfold3/forecast)上提供在线服务。
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