Clustering hundreds of millions of molecules in a single workstation is now a possibility! Check the new code: github.com/mqcomplab/bb...

Very nice!

A compelling review of how ML/AI could help in the quest to find an enzyme for every reaction. @jsunn-y.bsky.social @francescazfl.bsky.social Yueming Long @francesarnold.bsky.social www.cell.com/cell-systems...

Preprint: De-novo design of proteins that inhibit bacterial defenses Our approach allows silencing defense systems of choice. We show how this approach enables programming of “untransformable” bacteria, and how it can enhance phage therapy applications Congrats Jeremy Garb! tinyurl.com/Syttt 🧵

Glad to share the final version of our story about the UBR4 complex, an E4 ligase protein quality control hub @science.org. Now with more cryo-EM structures and a deeper dive into substrate recognition, especially escaped mitochondrial proteins @clausenlab.bsky.social www.science.org/doi/10.1126/...

#CCPBioSim will be running their annual training week of hands-on workshops in basic biomolecular simulation techniques from the 13th-17th October, in Sheffield. For more details, visit www.ccpbiosim.ac.uk/training2025 The registration link there will open shortly! #compchem

New degrader paper using the immunoproteasome. Congrats Cody Loy and Tim Harris! pubs.acs.org/doi/full/10....

encapsulate your target proteins for cryoEM structural determination within highly hydrophilic, structurally homogeneous, and stable protein shells 🤩 www.biorxiv.org/content/10.1...

We're excited to present our latest article in Nature Machine Intelligence - Boosting the predictive power of protein representations with a corpus of text annotations. Link: www.nature.com/articles/s42... [1/4]

CACHE 7 is launched with support from the @gatesfoundation.bsky.social and unpublished data from Damian Young at @bcmhouston.bsky.social, Tim Willson @thesgc.bsky.social and Neelagandan Kamaria InSTEM. Design selective PGK2 inhibitors. We'll test them experimentally. bit.ly/4lnVYOs

📢 Ready for this? A new way to think about Gene Regulation! 🚨A new coregulator complex, Zincore, acts as a "MOLECULAR GRIP", stabilizing TFs at DNA binding sites across the genome!🧬 💪Proud to be part of this work led by @daaninthelab.bsky.social Read more: science.org/doi/10.1126/science.adv2861

🚀 My first Cryo-EM structures are OUT on the PDB! 🎉Super excited about this milestone as PhD, it’s been a journey, and I’m grateful to finally have these as my first Cryo-EM structures! 🙌 🔁Thank you for sharing!❤️ Read @daaninthelab.bsky.social et. al.: www.science.org/doi/10.1126/... ⬇️ 2nd video

🚨It’s out @embojournal.org 🚨 Cardiolipin inhibits Caspase-4/11! Huge thanks to my brilliant supervisors Kate & Pablo, to @s-burgener.bsky.social & Mercedes and all the @inflammasomelab.bsky.social, it was a joy working and laughing with you, and to @brozlab.bsky.social & Si Ming lab.

We have a new collection of protein structure generative models which we call Protpardelle-1c. It builds on the original Protpardelle and is tailored for conditional generation: motif scaffolding and binder generation.

Switching next to protein protein interactions, we used arguably my favorite protein A34F GB1 to demonstrate that these glycopolymers stabilize protein protein interactions in a similar fashion to protein folding, via chemical interactions.

Interested in solvation free energies of small molecules and proteins? The latest @livecomsjournal.bsky.social tutorial by Egger-Hoerschinger et al provides a guide to quantifying hydration thermodynamics using Grid Inhomogeneous Solvation Theory (GIST): doi.org/10.33011/liv... #compchem

Pushing down to the structures of ever-smaller proteins (and ever-smaller crystals!)

Happy to share the latest from the lab, led by Daniel Alvarez, in collaboration with @lizconibear.bsky.social‬. In this AA-MD tour-de-force, we delve deep into the mechanism and energetics of lipid uptake by bridge-like lipid transfer proteins, and we learn a few interesting things along the way...

Thrilled to share my first corresponding author paper as a project leader in @hillerlab.bsky.social ‪ Amazing work from first author @annaleder.bsky.social We discovered multi-chaperone condensates in the ER that revolutionise the current vision of protein folding! www.nature.com/articles/s41...

Our latest Best Practices article "Developing Monte Carlo Methodologies in Molecular Simulations" is out now and describes how to derive acceptance probabilities for a variety of Monte Carlo moves: doi.org/10.33011/liv... #compchem

A benchmark dataset of 614 experimentally characterized de novo designed monomers from 11 different design studies shows that: - deep learning structural metrics only weakly predict success - The score distribution is different for different types of structures @grocklin.bsky.social

Physics-based design of efficient Kemp eliminases @lynnkamerlin.bsky.social www.nature.com/articles/s41...

All all-atom diffusion model of protein sequences. www.biorxiv.org/content/10.1...

Very excited about our latest all-atom generative model proteina, check out the project page (research.nvidia.com/labs/genair/...) and stay tuned for the code release soon!

Transferring Knowledge from MM to QM: A Graph Neural Network-Based Implicit Solvent Model for Small Organic Molecules | Journal of Chemical Theory and Computation pubs.acs.org/doi/10.1021/...

Our work on rationally engineering allosteric protein switches is now out in Nature Methods: www.nature.com/articles/s41... Thanks a lot to @grunewald.bsky.social and @noahholzleitner.bsky.social for the comprehensive news and views: www.nature.com/articles/s41...

Excited to share work with Zhidian Zhang, @milot.bsky.social, @martinsteinegger.bsky.social, and @sokrypton.org biorxiv.org/content/10.1... TLDR: We introduce MSA Pairformer, a 111M parameter protein language model that challenges the scaling paradigm in self-supervised protein language modeling🧵

One for the Apicomplexa peeps: ever wonder how does the IMC grow so fast during progeny formation? Where do all the lipids come from? In our latest work on malaria RBC stages we implicate this monster protein (~6000 residues!) and ER contact sites. Happy+proud to share and keen to hear thoughts!

If you’re interested in learning more about protein folding and misfolding, I’ve created a convenient reading list with a few essential papers: scholar.google.com/citations?us... scholar.google.com/citations?us...

Not my area at all, but how cool are these cryoEM structures of purely RNA-based assemblies! www.nature.com/articles/s41...

Our review on machine learning methods to study sequence–ensemble–function relationships in disordered proteins is now out in COSB authors.elsevier.com/sd/article/S... Led by @sobuelow.bsky.social and Giulio Tesei

actifpTM: a refined confidence metric of AlphaFold2 predictions involving flexible regions arxiv.org/abs/2412.15970

We @prescientdesign.bsky.social Genentech pre-printed our "Lab-in-the-loop for therapeutic antibody design." We built a general ML system to accelerate molecule design for challenging, therapeutically relevant targets. www.biorxiv.org/content/10.1...

CALVADOS-RNA is now published doi.org/10.1021/acs.... This is a simple model for flexible RNA that complements and works with the CALVADOS protein model. Work led by Ikki Yasuda who visited us from Keio University. Try it yourself using our latest code for CALVADOS github.com/KULL-Centre/...

Structural biology is in an era of dynamics & assemblies but turning raw experimental data into atomic models at scale remains challenging. @minhuanli.bsky.social and I present ROCKET🚀: an AlphaFold augmentation that integrates crystallographic and cryoEM/ET data with room for more! 1/14.

I've been hoping that someone would attempt to train a structure prediction model against experimental data (rather than 3D coordinates), and hopefully this is a step in that direction SFCalculator: connecting deep generative models and crystallography doi.org/10.1101/2025...

So seems like the group is on a roll this month! Here’s our latest work on parametrising coarse-grained models of sugars (disaccharides) by Astrid Brandner & in collaboration with Iain Smith, @pauloctsouza.bsky.social and @cg-martini.bsky.social pubs.acs.org/doi/10.1021/... #glycotime

I'm organizing a Keystone symposium, along with Liz Kellogg and @possuhuanglab.bsky.social, on machine learning and macromolecules. Mar 23-26 in Keystone, Colorado. We have a great lineup and deadlines are coming up soon!

Our paper on computational design of chemically induced protein interactions is out in @natureportfolio.bsky.social. Big thanks to all co-authors, especially Anthony Marchand, Stephen Buckley and Bruno Correia! t.co/vtYlhi8aQm

Deep learning methods aid in de novo design of proteins to neutralize lethal snake venom toxins in vitro and protect mice from a lethal neurotoxin challenge. www.nature.com/articles/s41... #NBThighlight

Microsoft researchers introduce MatterGen, a model that can discover new materials tailored to specific needs—like efficient solar cells or CO2 recycling—advancing progress beyond trial-and-error experiments. www.microsoft.com/en-us/resear...

A framework for evaluating how well generative models of protein structure match the distribution of natural structures. @possuhuanglab.bsky.social www.biorxiv.org/content/10.1...

If you use generative #DeepLearning for molecule design, check out our latest work, where we perform a large scale analysis (~1 B designs!) and find ‘traps’, ‘treasures’ and ‘ways out’ in the jungle of generative drug discovery. 🌴 🐒 Paper: arxiv.org/abs/2501.05457 Code: github.com/molML/jungle...

Thanks for siting my blog post ;) www.sciencedirect.com/science/arti...

We compared the calibration of various machine learning uncertainty estimation methods for protein engineering. No method excels across all scenarios, and uncertainty-based strategies for optimization often did not outperform methods without uncertainty.

Favourite paper of 2018 "Developing a molecular dynamics force field for both folded and disordered protein states" by Robustelli et al. (1/4) www.pnas.org/doi/10.1073/...

Cryptic pockets are hidden binding sites in proteins that are not visible in their standard ("apo") structure and only stable in the presence of the right ligand. Here, Bemelmans et al. review how scientists use computer algorithms to detect them. www.sciencedirect.com/science/arti... 🧪 #CompChem

Deep learning for proteins tutorial: github.com/Graylab/DL4P...

CAZyme3D: a database of 3D structures for carbohydrate-active enzymes https://www.biorxiv.org/content/10.1101/2024.12.27.630555v1

Merry Christmas and a Happy New Year, everyone! I hope you’ve had a wonderful year and wish you all an even better one ahead!