RFdiffusion A generative model for protein design
RoseTTAFold Diffusion is a guided diffusion model that can be used to generate protein structures in seconds. As reported in Nature, it excels at producing protein monomers, oligomers, binders, and more.

With prior methods, thousands of designs may have to be tested in the lab before finding a single one that performs as intended. Using RFdiffusion, we find that as little as one protein per design challenge must be tested.

To create RFdiffusion, our scientists drew inspiration from AI image generation tools like DALL-E. It was trained to iteratively remove noise from clouds of disconnected atoms, rearranging them into novel protein backbones.
diffusion_animation_C6_black.gif
https://www.ipd.uw.edu/software/ 
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EvoDiff combines evolutionary-scale data with diffusion models for controllable protein sequence generation. 

In addition to generating plausible proteins, we can scaffold structural motifs in sequence space!

Preprint: https://biorxiv.org/cgi/content/short/2023.09.11.556673v1

Code: https://github.com/microsoft/evodiff

F56KQNzXYAEtMuL.mp4

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Protein generation with evolutionary diffusion: sequence is all you need
https://www.youtube.com/watch?v=e1e-_SkyNjw
https://www.biorxiv.org/content/10.1101/2023.09.11.556673v1
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RFDiffusion: Accurate protein design using structure prediction and diffusion generative models
https://www.youtube.com/watch?v=wIHwHDt2NoI

RFdiffusion
https://www.youtube.com/watch?v=828WPIIOwaA. 
https://sbgrid.org/software/titles/rfdiffusion
https://github.com/RosettaCommons/RFdiffusion.
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AlphaFold Server Demo - Google DeepMind 
https://www.youtube.com/watch?v=9ufplEgtq8w

https://golgi.sandbox.google.com/about
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