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Learn more about Boltz-2, the new open source AI model from MIT and Recursion capable of predicting protein binding affinity with unprecedented speed, scale and accuracy. ▪️ Boltz-2 is the first model to combine structure and binding affinity prediction, approaching the accuracy of physics-based free energy perturbation (FEP) calculations...

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Recursion

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15,593 görüntüleme • 1 yıl önce •via X (Twitter)

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Learn more and explore Boltz-2 here:

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Unveiling the Future of Prompt Engineering for Better AI Interactions #tech

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Excited to unveil Boltz-2, our new model capable not only of predicting structures but also binding affinities! Boltz-2 is the first AI model to approach the performance of FEP simulations while being more than 1000x faster! All open-sourced under MIT license! A thread… 🤗🚀
0:39

Excited to unveil Boltz-2, our new model capable not only of predicting structures but also binding affinities! Boltz-2 is the first AI model to approach the performance of FEP simulations while being more than 1000x faster! All open-sourced under MIT license! A thread… 🤗🚀

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From sequence to structure, in one sentence.⚡ Today’s Agent Spotlight: Boltz-2 Structure Prediction Agent on ASI:One. Built on Massachusetts Institute of Technology (MIT)’s cutting-edge Boltz-2 model and deployed via NVIDIA's API, this agent generates 3D biomolecular structures just from a natural language prompt. Supports proteins, DNA, RNA, ligands, constraints, and even MSA data. Ideal for drug discovery, molecular biology, and biotech research. Try now: Link to Agent: Watch 👇
2:09

From sequence to structure, in one sentence.⚡ Today’s Agent Spotlight: Boltz-2 Structure Prediction Agent on ASI:One. Built on Massachusetts Institute of Technology (MIT)’s cutting-edge Boltz-2 model and deployed via NVIDIA's API, this agent generates 3D biomolecular structures just from a natural language prompt. Supports proteins, DNA, RNA, ligands, constraints, and even MSA data. Ideal for drug discovery, molecular biology, and biotech research. Try now: Link to Agent: Watch 👇

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Here's how to predict binding of tens or hundreds of small molecules to protein assemblies using Boltz 2 in ChimeraX. Accuracy depends on how similar the ligands and binding pockets are to existing experimental structures.
2:57

Here's how to predict binding of tens or hundreds of small molecules to protein assemblies using Boltz 2 in ChimeraX. Accuracy depends on how similar the ligands and binding pockets are to existing experimental structures.

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Boltz-2 was released recently. It is an Open Source protein-ligand co-folding model, which means it can predict the structure of a protein along with the ligand. It has various applications from drug discovery to protein design. I thought why not make a OSS web app for it.
2:00

Boltz-2 was released recently. It is an Open Source protein-ligand co-folding model, which means it can predict the structure of a protein along with the ligand. It has various applications from drug discovery to protein design. I thought why not make a OSS web app for it.

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Wohoo!! 🎉 You can now generate 3D structures of proteins, RNA, DNA, and small molecules. 🚀 Check out BOLTZ! — the first open-source and commercially available model to achieve AlphaFold3-level accuracy in biomolecular structure prediction. 🧪 Try it yourself on Gradio ! Explore and generate different proteins and viruses: For faster inference, check it out here (on L4): 👉 Let's make biology more open on Hugging Face ! If there’s anything to fear, it’s tech being closed :) !
0:23

Wohoo!! 🎉 You can now generate 3D structures of proteins, RNA, DNA, and small molecules. 🚀 Check out BOLTZ! — the first open-source and commercially available model to achieve AlphaFold3-level accuracy in biomolecular structure prediction. 🧪 Try it yourself on Gradio ! Explore and generate different proteins and viruses: For faster inference, check it out here (on L4): 👉 Let's make biology more open on Hugging Face ! If there’s anything to fear, it’s tech being closed :) !

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Today we’re previewing NeuralPLexer3 Beta: demonstrating unprecedented accuracy and speed in predicting protein-drug complexes, with instant and accurate structural insights across the full range of protein classes and drug molecules. Learn more:
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🔹 AI drug discovery, validated. Recursion recently announced the first clinical validation of its AI-enabled drug discovery platform – positive Phase 1b/2 data for the ongoing TUPELO study evaluating its AI-identified drug, REC-4881, in Familial Adenomatous Polyposis (FAP). This progressive rare disease affects more than 50,000 people in the U.S. and EU and has no FDA-approved treatments. It results in hundreds to thousands of polyps developing in the colon, and requires a lifetime of invasive surveillance and surgery. Recursion used AI not only to deliver the first potential treatment for this disease but also to quantify – for the first time at scale – the true natural progression of polyp burden in the trial-relevant population. It demonstrates the incredible breakthroughs that can come from merging proprietary data and AI – and the tangible impact on patient lives. 👉 See the full study results here:

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China is once again unsettling its American competitors in the AI race. Chinese labs have returned to the spotlight with the unveiling of GLM 5.2, described as the most powerful AI model ever trained in China — and one of the leading open‑source models worldwide. 🔍 Key highlights of “GLM 5.2”: ♦️ It is considered the strongest AI model developed in China to date, and ranks among the smartest open‑source models available. ♦️ It operates at a cost less than one‑tenth that of Anthropic’s latest models, making it a far more economical option. ♦️ It is likely to attract developers and companies seeking powerful, low‑cost models — especially amid growing technical and geopolitical restrictions. ♦️ Some evaluations place the model among the top globally, trailing OpenAI’s models while outperforming several competitors in specialized benchmarks and performance tests.

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Introducing a small portion of proprietary phenomics data from Recursion into the training of MolGPS, our foundation model for molecular property prediction, led to massive performance increases on new & existing benchmarks. Learn more about the impact of data & scale.

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