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Chai-1: Advanced Biomolecular Structure Prediction Now Available on Vecura

This update enables structural biologists and drug discovery researchers to predict complex 3D biomolecular structures through a guided workflow inside Vecura, eliminating the need to manage complex GPU infrastructure and environment setups.

May 26, 2026Chai-1
Chai-1
Chai-1 is now available on Vecura
vecura.com

What is Chai-1?

Chai-1 is a multi-modal foundation model developed by Chai Discovery designed for the all-atom prediction of biomolecular structures. It uniquely integrates proteins, small-molecule ligands, DNA, and RNA into a single, unified prediction framework. By employing a sophisticated diffusion-based architecture, it enables researchers to predict the complex 3D architecture of biological systems with state-of-the-art accuracy.

What can users do with Chai-1 on Vecura?

With Chai-1 on Vecura, users can:

  • Generate high-resolution 3D all-atom structural models for complex assemblies.

  • Predict binding geometries for protein-ligand, protein-DNA, and protein-RNA interactions.

  • Utilize automated MSA and template retrieval to enhance prediction confidence for homologous sequences.

  • Rank multiple structural samples based on aggregate scores, ensuring the selection of biologically plausible and clash-free conformations.

Chai-1 model on Vecura

What the output means

The output provides ranked CIF structural files alongside comprehensive confidence metrics, including pLDDT scores (reflecting local residue confidence) and pTM/ipTM scores (assessing overall structural and interface accuracy).

This output should be used to support scientific decision making. It does not replace experimental validation.

Why this matters

The ability to predict the structure of diverse biomolecular complexes from sequence data alone is a transformative capability for drug discovery and structural biology. By allowing for the simultaneous modeling of ligands and genetic material alongside protein scaffolds, Chai-1 streamlines the characterization of molecular machinery and binding interfaces that were previously difficult to resolve.

This capability empowers researchers to rapidly prioritize candidates for experimental validation, significantly reducing the time and resources required to understand complex molecular interactions.

  • Developed by: Chai Discovery

  • Source: Chai-1 Technical Report (bioRxiv)

  • Reference: Official GitHub repository

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主题

protein-structuredrug-discoverymulti-modalcomplex-predictionbiomolecular

On this page

What is Chai-1?What can users do with Chai-1 on Vecura?What the output meansWhy this matters
Vecura

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  • 定价

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  • 博客
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  • 隐私政策
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© 2026 NYB AI 保留所有权利。

所有系统运行正常