Chai-1: The Multi-modal Foundation Model for Biomolecular Structure Prediction

Chai-1 is a state-of-the-art AI model for molecular structure prediction that performs across a variety of tasks crucial to drug discovery. Built by Chai Discovery, this multi-modal foundation model is designed to decode the molecular interactions of life from raw sequence and chemical inputs.

On the Tamarind Bio platform, you can leverage Chai-1 to generate highly accurate protein-ligand structure prediction and complex protein multimer prediction with performance comparable to AlphaFold3 (AF3).

State-of-the-Art Performance Across All Modalities

Chai-1 sets a new benchmark for accuracy and flexibility in biomolecular structure prediction:

• Protein-Ligand Prediction: Achieves a ligand RMSD success rate of 77% on the stringent PoseBusters benchmark, comparable to AF3. Chai-1 is highly effective for co-folding proteins and small molecules.

• Protein Multimer Prediction: Significantly outperforms AlphaFold Multimer 2.3 (AF2.3) on low-homology evaluation sets for protein-protein interfaces.

• Antibody-Antigen Prediction: Achieves superior performance on challenging antibody-protein interfaces compared to AF2.3, making it a particularly potent tool for therapeutic antibody design.

• Protein-Nucleic Acid Complexes: Provides comparable performance to specialized methods for protein-nucleic acid structures and RNA targets, even running in single-sequence mode.

• Protein Monomer Folding: When provided with full MSA information, Chai-1 statistically outperforms AF2.3 on monomer folding accuracy.

Breakthrough Features of Chai-1: Control and Flexibility

Chai-1 offers unique features that enable users to guide predictions using real-world experimental constraints or accelerate workflows by eliminating the need for complex pre-processing.

Enhanced Controllability with Experimental Constraints

You can boost prediction accuracy by prompting Chai-1 with known information, which improves performance by double-digit percentage points. This capability is ideal for refining difficult binding complexes:

• Pocket Conditioning and Contact Constraints: Directly input distance restraints derived from techniques like epitope mapping or cross-linking mass spectrometry to guide the model toward known interaction sites. Conditioning on just four sampled epitope residues can more than double the prediction success rate.

• Apo Structure and Ligand Docking: Provide the unbound (Apo structure) of the protein to evaluate structural changes upon binding or run tasks that mimic classical docking by supplying pairwise distance information.

• Modified Residues and Covalent Bonds: The model natively supports and accurately predicts structures involving modified residues and complexes connected by covalent bonds.

Accelerated Workflows with Single-Sequence Mode

Chai-1 is designed for high efficiency and speed, offering a seamless experience even without extensive sequence search:

• Single-Sequence Mode: You can run Chai-1 without generating Multiple Sequence Alignments (MSAs) while preserving most of its performance. This greatly speeds up design cycles, particularly for highly variable sequences like those in immunological proteins where evolutionary signal is sparse.

• Language Model Embeddings: The model utilizes per-residue embeddings from a large protein language model to enable strong, high-accuracy predictions even when MSAs are omitted.

What is Tamarind Bio?

Tamarind Bio is a pioneering no-code bioinformatics platform built to democratize access to powerful computational tools for life scientists and researchers. Recognizing that many cutting-edge machine learning models are often difficult to deploy and use, Tamarind provides an intuitive, web-based environment that completely abstracts away the complexities of high-performance computing, software dependencies, and command-line interfaces.

The platform is designed provide easy access to biologists, chemists, and other researchers who may not have a background in programming or cloud infrastructure but want to run experimental models with their data. Key features include a user-friendly graphical interface for setting up and launching experiments, a robust API for integration into existing research pipelines, and an automated system for managing and scaling computational resources. By handling the technical heavy lifting, Tamarind empowers researchers to concentrate on their scientific questions and accelerate the pace of discovery. The Tamarind team hold information/data security as a top priority, as detailed in our Trust Center & Terms of Service, ensuring your data is safe on the platform.

Accelerating Discovery with Chai-1 on Tamarind Bio

The integration of Chai-1's advanced capabilities with Tamarind Bio's user-centric platform creates a powerful synergy that can significantly accelerate the drug discovery and research process.

• Unified Prediction and Flexibility: Chai-1's multi-modal nature allows it to perform a variety of tasks from a single model, including predicting protein-ligand and protein multimer interactions, which are critical for drug discovery. This is all available through a single, easy-to-use interface on Tamarind.

• Rapid and Accurate Insights: By combining Chai-1's ability to run in fast single-sequence mode with Tamarind's massive scalability, researchers can quickly screen thousands of protein-ligand interactions and get high-quality predictions without the need for extensive computational setup.

• Democratizing structural bioinformatics: The no-code platform makes state-of-the-art tools like Chai-1 accessible to a broader scientific community, including researchers in academia and small biotech companies who might not have access to dedicated computational resources. This democratization of access to advanced AI models for molecular structure prediction helps to accelerate fundamental research and drive innovation in therapeutic design.

How to Use Chai-1 on Tamarind Bio

Tamarind Bio makes using Chai-1 straightforward and efficient, regardless of your technical expertise. The no-code platform streamlines the entire workflow for molecular structure prediction.

Here is a simple, step-by-step guide for researchers to get started:

1. Access the Platform: Begin by logging in to the tamarind.bio website.

2. Select Chai-1: From the list of available computational models, choose the Chai-1 tool.

3. Specify Inputs: You can provide your input in various forms, including protein sequences (FASTA), chemical compositions for ligands (SMILES), and experimental constraint data. For predicting complexes, you can simply provide multiple sequences, and the platform will fold them together.

4. Configure Parameters: In a simple, graphical user interface, you can specify your prediction parameters. This includes choosing to use an MSA or single-sequence mode, and optionally adding experimental restraints. You can also set the number of recycles and diffusion steps, balancing accuracy with prediction time.

5. Submit and Monitor: With a single click, you can submit your job. The Tamarind platform handles the high-performance computing, parallelization, and GPU orchestration, saving you time and money. You can monitor the progress of your job directly from a user-friendly dashboard.

6. Analyze the Results: Once the job is complete, you will receive a comprehensive report with the predicted structures. You can explore interactive 3D visualizations of the structures directly in your browser. The platform also ensures that your inputs and outputs are securely stored in your private cloud, and that you retain ownership of all your data.

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