HelixFold-Multimer: Elevating Protein Complex Structure Prediction to New Heights
<|reference_start|>HelixFold-Multimer: Elevating Protein Complex Structure Prediction to New Heights: 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, greatly surpassing AlphaFold 3. 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.<|reference_end|>
@article{fang2024helixfold-multimer:,
    title={HelixFold-Multimer: Elevating Protein Complex Structure Prediction to
  New Heights},
    author={Xiaomin Fang, Jie Gao, Jing Hu, Lihang Liu, Yang Xue, Xiaonan Zhang,
  Kunrui Zhu},
    journal={arXiv preprint arXiv:2404.10260},
    year={2024},
    archivePrefix={arXiv},
    eprint={2404.10260},
    primaryClass={q-bio.BM cs.AI}
}