Chai Discovery
@chaidiscovery
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We’re excited to introduce Chai-2, a major breakthrough in molecular design. Chai-2 enables zero-shot antibody discovery in a 24-well plate, exceeding previous SOTA by >100x. Thread👇
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Listen to today's @NoPriorsPod to hear why the @chaidiscovery team is bullish on biotech. Thank you to @saranormous for hosting @_jackdent and @joshim5.
🆕!! AI and atomic-level structure prediction are accelerating drug discovery — turning a slow, empirical search process into something closer to molecular engineering. @joshim5 @_jackdent co-founders @chaidiscovery chat their new bio foundation model, Chai-2. It enables
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RT @tbpn: We asked @joshim5 (Co-Founder @chaidiscovery) about the future of AI in biotechnology. "We have scientists working for years try….
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We’re grateful to many partners for making this possible: @OracleCloud for the massive compute that was required; @NVIDIAHealth for new GPU kernels and accelerating our sequence search; and @Sino_Biological and @AdaptyvBio for conducting many wet-lab experiments in the paper.
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We believe that these results mark a transition from empirical discovery to deterministic molecular engineering. ✨Reach out at if you’d like access to Chai-2.
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At the core of Chai-2’s success is its multimodal generative architecture, integrating all-atom structure prediction and generative modeling. This enables Chai-2 to create novel and epitope-specific binders. 🔬Whitepaper with more details:
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We prompt Chai-2 with 50 targets, test the designs in the lab, and observe a >15% hit rate. In just 2 weeks, we generate molecules, and synthesize + characterize them in the lab, without any iterative optimization or high-throughput lab screening.
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"OpenBind will deploy automated chemistry . to eventually generate more than 500,000 protein - ligand complex structures and affinity measurements over 5 years. This would represent a 20-fold increase over all public data produced in the last half-century.".
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We're excited to partner with the UK Government on OpenBind, an effort to create the largest open dataset of drug-protein interactions in history. More data → smarter AI models → better medicines.
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RT @SeqeraLabs: Exciting news! 🎉You can now try Chai-1, the SOTA model for biomolecular structure prediction by @chaidiscovery, with Seqera….
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RT @StephaneRedon: Excited to announce the general availability of Chai-1 in SAMSON! Like AlphaFold 3, Chai-1 is a state-of-the-art foundat….
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RT @ClementDelangue: So excited to see more biology open-source models!. Chai by @chaidiscovery does structure predictions at AlphaFold3 le….
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RT @joshim5: Folding proteins on Modal with @chaidiscovery Chai-1. Comprehensive guide with working code samples from the @modal_labs team….
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We've released a new version (v0.5.0) of the chai-lab Python package that:.- Improves automatic MSA generation.- Adds support for specifying covalently bound ligands. This feature should be particularly helpful for modeling glycosylation and tinkering with modifications that.
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RT @kenbwork: Chai-1 is available on Latch. This is a big model that predicts the properties and interactions of many types of molecules.….
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You can download Chai from our GitHub repo, our use it on channels like @tamarindbio, @LatchBio, @SeqeraLabs, and many others.
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Since our launch 2.5 months ago, we've been blown away by the many ways in which the academic community has leveraged Chai-1. Today, we're making this same technology available to companies everywhere for free.
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Chai-1 has always been available for commercial use via our server. Today, we're also making Chai-1(r) code and weights available under an Apache 2.0 license, which permits broad commercial use.
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