AI x Bio | prev. PhD @Cambridge_Uni, MSc @ETH_physics
London, UK
Joined April 2020
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Simon Mathis retweeted
Today we're launching Latent-Y: the world's first autonomous agent for drug design, lab-validated end to end.
Give it a research goal. Latent-Y reasons, designs, iterates, and delivers lab-ready antibodies, autonomously or collaboratively, with the biological reasoning of a PhD protein design expert.
Technical report: tinyurl.com/latent-y-techrep…
Blog post: latentlabs.com/latent-y
Apply for access: platform.latentlabs.com
Simon Mathis retweeted
Join us next Tuesday and ask questions/discuss research!
Next Tues (3/24) at 4PM ET, @DidiKieran
and Danny Reisenbach will present "Proteina-Complexa: Scaling Atomistic Protein Binder Design with Generative Pretraining and Test-Time Compute"
Papers: research.nvidia.com/labs/gen…
Sign up on our website for zoom links!
Simon Mathis retweeted
📢 We’re launching Proteina-Complexa — and after the Jensen keynote mention, we definitely had to post this thread now ;)
Atomistic binder design with generative pretraining + test-time compute, plus large-scale wet-lab validation.
Project page: research.nvidia.com/labs/gen…
🧵 1/n
Simon Mathis retweeted
Introducing Latent-X2 — AI-generated antibodies with drug-like developability and low immunogenicity in human panels, zero-shot.
Technical report: tinyurl.com/latent-X2-report
Blog: latentlabs.com/latent-x2
Apply for access: [email protected]
Simon Mathis retweeted
Today, we report a method for design of active enzymes, RFdiffusion2, in @naturemethods. For the first time, we are able to design enzymes with native-range catalytic activity.
We also are releasing our next frontier model, RFdiffusion3, code 👇
Simon Mathis retweeted
Come do a PhD with me 😀! Promise of fun science and great coffee ☕
Simon Mathis retweeted
🚨New package alert!
🧬 Introducing Pocketeer: A lightweight, fast protein pocket finder in pure Python!
I built this as a Pythonic version of fpocket because I wanted something that could easily calculate subpockets.
> pip install pocketeer
Link at end of the thread 🧵(1/7)
Simon Mathis retweeted
We sought to make proteins both potent and FAST. We used #proteindesign to design precise control over protein interaction lifetimes, enabling us to construct rapid-response circuits, biosensors, and switchable cytokines. Now published @Nature! Links to paper and tutorial below.
Simon Mathis retweeted
We asked ourselves what could we do if we worked cooperatively as a team to create a single model that could design any biomolecular interactions.
Yesterday, we reported details of RFdiffusion3, the next step towards building functional proteins straight from the computer.
Simon Mathis retweeted
Very excited to share our paper "De novo Design of All-atom Biomolecular Interactions with RFdiffusion3", now on BioRXiv. biorxiv.org/content/10.1101/… 1/n
Simon Mathis retweeted
La-Proteina open source now, excited to see what people build with it!
Simon Mathis retweeted
Thrilled to announce I'm starting as a Principal Investigator at #Aithyra in Vienna! We'll be developing generative models to understand cell biology and design proteins.
I'm hiring PhDs, Postdocs, & Visiting Researchers! PhD applications by Sept 10: apply.cemm.at
Simon Mathis retweeted
Check out our new perspective "Illuminating the universe of enzyme catalysis in the era of artificial intelligence" now out in @CellSystemsCP !
We discuss a vision and path forward for genetically encoding almost all chemistry, powered by new AI tools:
authors.elsevier.com/c/1lg4h…
Simon Mathis retweeted
Where are all the de novo designed therapeutics? In a guest post by @frdreyer, we break down what the actual bottlenecks, challenges, and opportunities are in building and deploying purely in silico drug discovery engines, with a focus on antibody structure.
Link below 👇
Simon Mathis retweeted
Today, we're releasing a software suite to train biomolecular neural networks called AtomWorks. We have already used it to train performant networks in our group -- we hope that others find it as useful as we do!
Check it out at github.com/RosettaCommons/at…
AtomWorks is out! Building upon @biotite_python, we built for a toolkit for all things biomolecules and trained RF3 with it. All open-source, test it via `pip install atomworks`!
AtomWorks: github.com/RosettaCommons/at…
RF3: github.com/RosettaCommons/mo…
Paper: tinyurl.com/y2w4z65b
1/6
Simon Mathis retweeted
Atomsworks and RF3 is finally here!!
I was very fortunate to get early access to atomworks and it really lowers the activation energy todo some really cool stuff with the PDB very quickly. Might share fun examples later
Huge congrats to @SimMat20 and team!!! ✨
Simon Mathis retweeted
RosettaFold 3 is here! 🧬🚀
AtomWorks (the foundational data pipeline powering it) is perhaps the really most exciting part of this release!
Congratulations @SimMat20 and team!!! ❤️
Simon Mathis retweeted
RNA-FrameFlow has found a new home in TMLR @TmlrPub 🥳
Over the past one year, we've spent quite some time making our method faster, developing more intricate evaluation pipelines, thinking about conditional design, and assessing/ablating our modeling choices
Here are some updates 👇🏻🧵
🧬🤖 Introducing RNA-FrameFlow –– an unconditional generative model for 3D RNA backbone design!
📑: arxiv.org/abs/2406.13839
🧰: github.com/rish-16/rna-backb…
Our method generates ≥ 40% self-consistent *all-atom* RNA backbones that are globally and locally realistic 💪🏻
1/9
Simon Mathis retweeted
Introducing Latent-X — our all-atom frontier AI model for protein binder design.
State-of-the-art lab performance, widely accessible via the Latent Labs Platform.
Free tier: platform.latentlabs.com
Blog: latentlabs.com/latent-x/
Technical report: tinyurl.com/latent-X
Simon Mathis retweeted
Check out La-Proteina, our new model for all-atom structure generation at scale! Was a very fun project to work on with @tomasgeffner and the rest of the team. Two things I am particularly excited about in 🧵 1/n
