While monomer protein structure prediction tools boast impressive accuracy,
the prediction of protein complex structures remains a daunting challenge in
the field. This challenge is particularly pronounced in scenarios involving
complexes with protein chains from different species, such as antigen-antibody
interactions, where accuracy often falls short. Limited by the accuracy of
complex prediction, tasks based on precise protein-protein interaction analysis
also face obstacles. In this report, we highlight the ongoing advancements of
our protein complex structure prediction model, HelixFold-Multimer,
underscoring its enhanced performance. HelixFold-Multimer provides precise
predictions for diverse protein complex structures, especially in therapeutic
protein interactions. Notably, HelixFold-Multimer achieves remarkable success
in antigen-antibody and peptide-protein structure prediction, surpassing
AlphaFold-Multimer by several folds. HelixFold-Multimer is now available for
public use on the PaddleHelix platform, offering both a general version and an
antigen-antibody version. Researchers can conveniently access and utilize this
service for their development needs.

我们报道了我们的蛋白质复合物结构预测模型 HelixFold-Multimer 的不断改进，强调其卓越的性能。HelixFold-Multimer 在多样的蛋白质复合物结构，特别是治疗蛋白质相互作用方面，提供了精确的预测，尤其在抗原 - 抗体和肽 - 蛋白质结构预测方面超过了 AlphaFold-Multimer 数倍。HelixFold-Multimer 现在可在 PaddleHelix 平台上进行公开使用，提供通用版本和抗原 - 抗体版本，研究人员可以方便地访问和利用此服务满足其开发需求。