Sign in

Marta Skreta

@martaowesyou.bsky.social
174 followers 50 following 20 posts

UofT CompSci PhD Student in Alán Aspuru-Guzik's #matterlab and Vector Institute | prev. Apple

PostsRepliesMedia
Marta Skreta @martaowesyou.bsky.social · 08/04/2026
... @k-neklyudov.bsky.social, @yoshuabengio.bsky.social, @alextong.bsky.social, @francesarnold.bsky.social, and Cheng-Hao Liu at @caltech.edu and @mila-quebec.bsky.social 🤗
110
Marta Skreta @martaowesyou.bsky.social · 08/04/2026
So grateful for this incredible collaboration with @jarridrb.bsky.social, @tlambert99.bsky.social @daro9000.bsky.social ky.social, Yueming Long, Zi-Qi Li, Xi Zhang, @mirunacretu.bsky.social, @francescazfl.bsky.social, Tanvi Ganapathy, Emily Jin, @joeybose.bsky.social, Jason Yang, ...
ky.social
110
Marta Skreta @martaowesyou.bsky.social · 08/04/2026
Not only are the enzymes functional, they're also evolvable starting points. One round of mutagenesis on dCT-H11 yielded a 4x activity increase for spirocyclopropanation and even inverted stereoselectivity. The chemistry nature never explored is now within reach! 🌍
100
Marta Skreta @martaowesyou.bsky.social · 08/04/2026
Take the top design, dCT-H11. Its closest structural match (PDB 3CRJ) is a non-enzymatic transcription factor from a Dead Sea extremophile. DISCO completely repurposed this fold for carbene chemistry with a novel active-site geometry and very low sequence identity. 🦠🔬
110
Marta Skreta @martaowesyou.bsky.social · 08/04/2026
Perhaps the most interesting property? These active sites don't exist in nature. When searched against 200M+ structures in the AlphaFold Database, the majority of DISCO's generated binding motifs have no close natural homologs.
110
Marta Skreta @martaowesyou.bsky.social · 08/04/2026
The success continued with B–H insertion. A single DISCO design achieved 5,170 TTN, outperforming three rounds of laboratory directed evolution by over 2x. 🤯
110
Marta Skreta @martaowesyou.bsky.social · 08/04/2026
It mastered selective C(sp³)–H insertion, one of the most challenging transformations in organic chemistry. A single computational step reached 2,360 TTN, exceeding the endpoint of a previous 14-round directed evolution campaign. 🎯
110
Marta Skreta @martaowesyou.bsky.social · 08/04/2026
The ultimate test is the wet lab. 🧪 DISCO was challenged to design enzymes for carbene-transfer reactions—chemistry alien to the natural world.
110
Marta Skreta @martaowesyou.bsky.social · 08/04/2026
Because DISCO generates sequence & structure together, it unlocks multimodal inference-time steering. 🧭 Deriving multimodal Feynman-Kac Correctors, DISCO steers generation on the fly—like forcing the creation of dense disulfide bonds (FKC-MM) or binding a target while avoiding a decoy (FKC-SG). 🎯🚫
120
Marta Skreta @martaowesyou.bsky.social · 08/04/2026
How does it work? DISCO aligns sequence & structure bidirectionally via cross-modal recycling, self-correction, and noisy guidance. It also introduces an entropy-adaptive sequence temperature to properly balance information across modalities during generation! ⚖️
120
Marta Skreta @martaowesyou.bsky.social · 08/04/2026
Introducing the 💃🕺Studio-179 benchmark 🕺 💃: DISCO outperforms baselines on 178/179 targets, along with sequence-specific DNA and RNA binders! 📈 It also shines in unconditional design, generating highly diverse, novel, and co-designable proteins.
110
Marta Skreta @martaowesyou.bsky.social · 08/04/2026
Evolution is an amazing chemist, but the reactions it has explored represent a remarkably narrow slice of what is possible. Existing AI models require predefined theozymes & generate backbones before sequences. DISCO generates both sequence & structure simultaneously without the need for theozymes.
110
Marta Skreta @martaowesyou.bsky.social · 08/04/2026
14 rounds of directed evolution and over a year of wet lab work. That's what it took to engineer an enzyme for selective C(sp³)–H insertion, one of the most challenging transformations in organic chemistry. DISCO surpasses this with a single plate.
110
Marta Skreta @martaowesyou.bsky.social · 08/04/2026
What if AI could invent enzymes that nature hasn’t seen? 👩‍🔬🧑‍🔬 Introducing 🪩 DISCO: Diffusion for Sequence-structure CO-design 📝 Blog: disco-design.github.io 📄 Paper: arxiv.org/abs/2604.05181 💻 Code: github.com/DISCO-design...
15918
Reposted by Marta Skreta
Rocío Mercado Oropeza @rociomer.bsky.social · 05/08/2025
📄📄📄 The AI4Mat-NeurIPS-2025 workshop is now open for submissions until August 22, 2025 (AOE)! Consider submitting full-length papers or shorter-length findings. We also have a special track for papers on benchmarking AI for materials design. sites.google.com/view/ai4mat/...
273
Reposted by Marta Skreta
Rocío Mercado Oropeza @rociomer.bsky.social · 28/04/2025
Thanks to all the speakers and participants for the engaging discussions today, and for making the AI4Mat@ICLR 2025 workshop a great success! Thanks also to Santiago, @martaowesyou.bsky.social, and the rest of the co-organizing team for the effort putting this together. Great to be a part of it!
Singapore EXPO sign outside of the convention center where ICLR was held.Co-organizer photo with Santiago, myself, and Marta at the end of the workshop.
0111
Reposted by Marta Skreta
Stefan P. Schmid @spschmid.bsky.social · 03/03/2025
🚀 Looking for reaction conditions that work well for multiple substrates? CurryBO can help🍛 Now out on arXiv: arxiv.org/abs/2502.18966 A short explanation thread 👇
arxiv.org
One Set to Rule Them All: How to Obtain General Chemical Conditions via Bayesian Optimization over Curried Functions
General parameters are highly desirable in the natural sciences - e.g., chemical reaction conditions that enable high yields across a range of related transformations. This has a significant practical...
11410
Reposted by Marta Skreta
Alán Aspuru-Guzik @aspuru.bsky.social · 24/01/2025
We at @digital-discovery.bsky.social are very happy to announce a new paper type called "Commit". Inspired by version control systems such as git, the idea is that if you have an update on a short and pointed publication, you can send it as a commit. We envision commits to be co-cited with the
88515
Reposted by Marta Skreta
Alán Aspuru-Guzik @aspuru.bsky.social · 21/01/2025
Excited to have #selfdrivinglaboratories listed as one of the seven technologies to watch in 2025 by @nature.com Thanks to the #matterlab, the @accelerationc.bsky.social and of course all the global community on SDLs! @uoft.bsky.social @vectorinst.bsky.social l www.nature.com/articles/d41...
nature.com
Self-driving laboratories, advanced immunotherapies and five more technologies to watch in 2025
Sustainability and artificial intelligence dominate our seventh annual round-up of exciting innovations.
04316
Reposted by Marta Skreta
lebellig @lebellig.bsky.social · 05/01/2025
"The Superposition of Diffusion Models using the Îto Density Estimator" (@martaowesyou.bsky.social, @lazaratan.bsky.social et al.) It's nice to see an easy-to-compute log-likelihood estimator for SDE sampling of diffusion models (not just ODE) 📄 arxiv.org/abs/2412.17762 🐍 github.com/necludov/sup...
0224
Reposted by Marta Skreta
Joey Bose @joeybose.bsky.social · 28/12/2024
New paper just dropped! How do you combine pre-trained diffusion models without having to train a new one 🤓? Turns out you can use our all new Ito density estimator 🔥 to compute densities under a diffusion model efficiently 🚀!
0205
Marta Skreta @martaowesyou.bsky.social · 28/12/2024
Work with an absolute dream of a team: @lazaratan.bsky.social @joeybose.bsky.social @alextong.bsky.social and @k-neklyudov.bsky.social 🤗🚀⚡️ 📄Paper: arxiv.org/abs/2412.17762 💻Code: github.com/necludov/sup... 🤗HuggingFace: huggingface.co/superdiff
arxiv.org
The Superposition of Diffusion Models Using the Itô Density Estimator
The Cambrian explosion of easily accessible pre-trained diffusion models suggests a demand for methods that combine multiple different pre-trained diffusion models without incurring the significant co...
062
Marta Skreta @martaowesyou.bsky.social · 28/12/2024
Super super excited to share our work SuperDiff 🦹‍♀️ for superimposing pretrained diffusion models at inference time 💪 Check out the 🧵 to see how we superimposed proteins as well as images, all thanks to a fast new density estimator. Curious to see what 🍩 & 🗺️ would produce?
1243
Marta Skreta @martaowesyou.bsky.social · 18/12/2024
exciting new workshop announcement!! join us in Singapore for Frontiers in Probabilistic Inference: Learning Meets Sampling 🌏⚡️😃 details below 👇 #ICLR2025
092
Marta Skreta @martaowesyou.bsky.social · 09/12/2024
3/3 🧵Work with my fellow Matter Lab quantum tunnelers: Philipp Schleich, Lasse B. Kristensen, @rovargash.bsky.social, @aspuru.bsky.social 📜 buff.ly/4iu8w6M 💻 buff.ly/3D9HaD2 See you at NeurIPS!
011
Marta Skreta @martaowesyou.bsky.social · 09/12/2024
2/3 🧵Here, we enter the quantumverse with deep equilibrium networks, where we demonstrate that a single layer of a quantum circuit can perform as well or better than multiple independent layers when trained like a DEQ.
100
Marta Skreta @martaowesyou.bsky.social · 09/12/2024
1/3 🧵Quantum conundrum: we want expressive circuits, but current hardware only allows short coherence times, and so more parameters = more problems. Check out our #NeurIPS2024 paper “Quantum Deep Equilibrium Models”.
1136