Maxwell Kazman retweeted
Super excited about this work! We are finally able to not only screen binders for specificity, but design them to be specific 🤯 this will be transformational in the development of pMHC binders and therapeutics in general
Harder specificity challenges: @jBonzaniniSci designed peptide-MHC binders that bind tightly and very specifically, showing the model reasons well about the interactions formed. 20/30
4
9
204
Maxwell Kazman retweeted
Looking for a how-to blog on using RFD4-Proteina for protein design?
Start here:
developer.nvidia.com/blog/de…
12
73
3,257
RT @uwmnewsroom: RFD4-Proteina, co-developed by @UWproteindesign @UWMedicine & @NVIDIAHealth, debuts today at GTC Berlin. The open-source g…
11
2
Maxwell Kazman retweeted
Need compute to compete in protein design competitions like this one?
proteinbase.com/competitions…
RFD4-Proteina is now on Hugging Face with two weeks of NVIDIA-sponsored access. 🧵👇
2
14
58
6,753
Maxwell Kazman retweeted
Incredible privilge to work with @maxkazman, looking forward to take what we learnt with RFD4-Proteina and go far far beyond!
Great things come from great teams! Super excited to share rfd4-proteina.org, a step-function improvement in generative protein design! A year in the making with @UWproteindesign , NVIDIA GenAIR and the amazing @DidiKieran @nscorley and @RafiBrent! 🧵1/n
2
6
738
Maxwell Kazman retweeted
🔬 RFD4-Proteina joins Nemotron, Kumo, Cosmos, Alpamayo and Ising in today's NVIDIA open model release.
We’re releasing more open models to help teams across Europe build AI with their own data, on infrastructure they control.
Announced at GTC Berlin, the models help developers, researchers and enterprises build specialized AI agents, train robots, design proteins and develop quantum computers.
See what’s new: nvda.ws/4iwBMvF
1
8
36
1,603
Maxwell Kazman retweeted
It has been incredibly exciting to bring the RFdiffusion and Proteina model families together. An amazing release! 💜💚🔥🎉
And I am just as excited about the applications! 🧬
Massive congrats to @DidiKieran, @nscorley, @RafiBrent, @maxkazman and the many more contributors!
Avengers assemble: 1 year BakerLab + NVIDIA GenAIR = 🔥 rfd4-proteina.org
Presenting RFD4-Proteina, our latest protein design model, significantly better and faster than everything we compared against, both in silico and in the lab! 1/30
1
10
42
2,053
Maxwell Kazman retweeted
🚀 Today at GTC Berlin we introduced RFD4-Proteina! A close one-year collaboration between GenAIR and David Baker's group at @UWproteindesign !
🧬 Design proteins faster and send fewer, better candidates to the lab.
Introducing RFD4-Proteina, a new NVIDIA BioNeMo open model co-developed with @UWproteindesign.
▫️Fast: 13× faster generation than RFdiffusion3 at 200 residues
▫️ Smart: state-of-the-art across 12+ protein design tasks
▫️ Programmable: set your design inputs and use test-time compute on harder problems
Start with our binder-design tutorial nvda.ws/3VK9Uvr
3
9
35
1,433
Maxwell Kazman retweeted
Congratulations to @DidiKieran, @nscorley, @RafiBrent, @maxkazman, David Baker and many scientists and collaborators who made this possible! 💜💚
Avengers assemble: 1 year BakerLab + NVIDIA GenAIR = 🔥 rfd4-proteina.org
Presenting RFD4-Proteina, our latest protein design model, significantly better and faster than everything we compared against, both in silico and in the lab! 1/30
7
38
1,864
Maxwell Kazman retweeted
What a wild ride! After a fantastic collaboration between @UWproteindesign and Nvidia GenAIR, we've released the latest in the RFdiffusion and Proteina lineages, namely... RFD4-Proteina! Computationally and in the lab, the results have astonished us🧵 1/n rfd4-proteina.org/
1
7
25
1,289
Great things come from great teams! Super excited to share rfd4-proteina.org, a step-function improvement in generative protein design! A year in the making with @UWproteindesign , NVIDIA GenAIR and the amazing @DidiKieran @nscorley and @RafiBrent! 🧵1/n
1
11
31
1,276
Expect more threads in the coming days -- so much to share and so many cool learnings!
Website: rfd4-proteina.org/index.html
Paper: rfd4-proteina.org/assets/pap…
Code: github.com/RosettaCommons/RF…
Demo: huggingface.co/spaces/nvidia…
🧵n/n
1
3
64
Hear more from the team: nitter.siddz.com/nscorley/status/211289…
nitter.siddz.com/DidiKieran/status/2112…
What a wild ride! After a fantastic collaboration between @UWproteindesign and Nvidia GenAIR, we've released the latest in the RFdiffusion and Proteina lineages, namely... RFD4-Proteina! Computationally and in the lab, the results have astonished us🧵 1/n rfd4-proteina.org/
28
Was super awesome to work with the great people at NVIDIA, especially the GenAIR team - @ArashVahdat @karsten_kreis @tomasgeffner
🧬 Design proteins faster and send fewer, better candidates to the lab.
Introducing RFD4-Proteina, a new NVIDIA BioNeMo open model co-developed with @UWproteindesign.
▫️Fast: 13× faster generation than RFdiffusion3 at 200 residues
▫️ Smart: state-of-the-art across 12+ protein design tasks
▫️ Programmable: set your design inputs and use test-time compute on harder problems
Start with our binder-design tutorial nvda.ws/3VK9Uvr
4
7
703
Maxwell Kazman retweeted
A step change in protein design: RFD4-Proteina is enables everyone today.
We partenered with @huggingface to make available a free space.
You can solve your hardest biology problem right now. No CS degree required: huggingface.co/blog/nvidia/r…
More to come...
Avengers assemble: 1 year BakerLab + NVIDIA GenAIR = 🔥 rfd4-proteina.org
Presenting RFD4-Proteina, our latest protein design model, significantly better and faster than everything we compared against, both in silico and in the lab! 1/30
1
11
31
1,948
Maxwell Kazman retweeted
Protein design doesn’t have to stop at the canonical 20 amino acids! After our work on phosphotyrosine binders, RFD4-Proteina adds phosphoserine and phosphothreonine (below) to the repertoire, with binders that distinguish adjacent H3pS10 and H3pT11 sites in the histone H3 tail!
The unified latent space pushes specificity further: with @kinasekid we bind phosphorylated serines and threonines specifically, and even site-selectively when they sit directly next to each other on a target! 22/30
6
21
113
10,427
Maxwell Kazman retweeted
@NVIDIAHealth and the Institute for Protein Design, led by Nobel laureate David Baker, just released RFD4-Proteina today at GTC Berlin, an open model that designs a protein’s sequence and structure together against a target. Apheris is a launch distribution partner. We run RFD4-Proteina on your own GPUs, inside your environment, and you can fine-tune it on your own structures and assays to design VHHs, antibodies, binders and enzymes and customize it to your chemistry.
4
18
81
15,971
Try out the model now!
New de novo design model from Baker Lab + NVIDIA, available on Tamarind today.
We are excited to be working with @NVIDIAHealth to bring access to RFD4-Proteina on day 0.
1
4
315
Maxwell Kazman retweeted
1/n
Crossover episode! We introduce RFD4-Proteina, our latest design model - and the result of a year-long collaboration between the Baker Lab and NVIDIA GenAIR (the name says it all…). I hope you’ll agree - the results are astonishing. 🌐 Website: rfd4-proteina.org/
7
48
191
15,491
Maxwell Kazman retweeted
Avengers assemble: 1 year BakerLab + NVIDIA GenAIR = 🔥 rfd4-proteina.org
Presenting RFD4-Proteina, our latest protein design model, significantly better and faster than everything we compared against, both in silico and in the lab! 1/30
27
202
660
63,713