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HelixFold 3

By Baidu PaddleHelix →

All-atom biomolecular structure prediction for proteins, nucleic acids, and small molecules

HelixFold 3 is a comprehensive biomolecular structure prediction platform built on PaddlePaddle, predicting 3D coordinates for complexes of proteins, DNA, RNA, ligands, and covalent modifications.

Unified prediction of protein-ligand, protein-nucleic acid, and multi-chain assembliesHigh-throughput distributed inference accelerated by PaddleHelix engineIncludes specialized chemical bond loss for precise covalent drug interactionsOpenly accessible web server and downloadable weights for enterprise deployment
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Overview

HelixFold 3 is a comprehensive biomolecular structure prediction platform built on PaddlePaddle, predicting 3D coordinates for complexes of proteins, DNA, RNA, ligands, and covalent modifications.

Information checked against an official source; not a hands-on test. Source · Last reviewed: 20/09/2026, 11:09:40

Key Features

  • Unified prediction of protein-ligand, protein-nucleic acid, and multi-chain assemblies
  • High-throughput distributed inference accelerated by PaddleHelix engine
  • Includes specialized chemical bond loss for precise covalent drug interactions
  • Openly accessible web server and downloadable weights for enterprise deployment
Interactive 3D Structure

HelixFold 3 Predicted Complex

Streams real 3D atomic coordinates from RCSB Protein Data Bank
⇄ Drag to rotate · Scroll to zoom
pLDDT / B-Factor:
>90 Very high 70-90 Confident 50-70 Low <50 Very low

Academic Context & Research Evidence

Biological & Workflow Fit

Biological Application
Target-ligand interaction modeling, RNA-protein complex prediction, and covalent drug discovery
Research Workflow
Input biomolecular sequence and SMILES -> generate 3D complex coordinates and confidence scores
Compute & Hardware
1x NVIDIA A100 or Kunlunxin AI accelerators
Licensing & Academic Use
Apache 2.0 (code) / Model License
Documented Evidence
View validation publication / source ↗

Cite this Tool

Use this citation format when referencing HelixFold 3 in scientific publications and benchmark papers.

@software{helixfold_3_2026,
  title = {{HelixFold 3}},
  author = {{Baidu PaddleHelix}},
  year = {2026},
  url = {https://github.com/PaddlePaddle/PaddleHelix},
  note = {Indexed on aibioatlas - AI for Biology and Drug Discovery}
}

Peer-Reviewed Literature & Preprints

Live scientific citations streamed from Europe PMC and PubMed for HelixFold 3.

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Technical / Product Information

Missing values mean the catalog has no recorded information. They do not mean a feature is absent.

Entry typeAI Model / Web Server
Access modeOpen Source & Web Service
AI roleStructural Complex Modeling
Input dataNot recorded
Output dataNot recorded
Licence conditionsApache 2.0 (code) / Model License
Commercial eligibilityOpen research access with enterprise private deployment
Compute requirements1x NVIDIA A100 or Kunlunxin AI accelerators
ValidationNot recorded
TypeAll-atom structure prediction model
Intended useNot recorded
CompatibilityNot recorded
ManufacturerBaidu Inc.
Biological applicationTarget-ligand interaction modeling, RNA-protein complex prediction, and covalent drug discovery
Research workflowInput biomolecular sequence and SMILES -> generate 3D complex coordinates and confidence scores
Evidence levelPreprint and blind benchmark evaluation (2024)
Integration evidencehttps://github.com/PaddlePaddle/PaddleHelix
Laboratory handoffStructures inform cryo-EM model fitting and crystallographic phasing
AvailabilityAvailable globally on GitHub
Price / accessFree Open Source / Enterprise Support

Research fit & compatibility

No software–hardware integration has been verified for this entry yet. Explore documented research workflows.

Gallery & resources

No licensed product photograph recorded for HelixFold 3 yet. Visit the official resource below for manufacturer imagery.

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FAQ

Where is this product available?

Available globally on GitHub

How is pricing handled?

Prices reflect the source at its last check. Confirm current pricing and regional availability on the official site.

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Peer Reviews & Community Ratings

Feedback from researchers and computational biologists evaluating HelixFold 3.

5.0
★★★★★Based on 0 researcher evaluations
Biological Accuracy
4.8/5
Ease of Installation
4.3/5
Documentation & Code
4.6/5