mlsanityData to 7 Oct 2026

HelixFold-Multimer: Elevating Protein Complex Structure Prediction to New Heights

arXiv 2404.10260 ↗First posted 16 Apr 2024q-bio.BM cs.AIcited by 2

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Abstract (arXiv)

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.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 3 of its 25 references that are in the map. First posted on arXiv 16 Apr 2024.

Builds on

3 of 25 references.

References · 3

  1. 2021Independent SE(3)-Equivariant Models for End-to-End Rigid Protein Dockingcited by 81
  2. 2022HelixFold-Single: MSA-free Protein Structure Prediction by Using Protein Language Model as an Alternativecited by 15
  3. 2022HelixFold: An Efficient Implementation of AlphaFold2 using PaddlePaddlecited by 12

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Citing papers per year: 2024: 1; 2025: 1.

2 papers.