What if, instead of trying to predict properties of every molecule, we focus on simply ranking them? After all, when running Bayesian optimization (BO) for drug/materials discovery, what matters is picking the best candidates first. Paper: doi.org/10.1063/5.02... Code: github.com/gkwt/rbo [1/5]

CACHE 7 is launched with support from the @gatesfoundation.bsky.social and unpublished data from Damian Young at @bcmhouston.bsky.social, Tim Willson @thesgc.bsky.social and Neelagandan Kamaria InSTEM.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

New Practical Cheminformatics Post patwalters.github.io/Three-Papers...

New @chemrxiv.bsky.social preprint! RoboChem-Flex is a powerful, low-cost (<5k EUR), modular self-driving lab for chemical synthesis We showcase 6 studies (photochemistry, biocatalysis, cross coupling, ee ...), all optimized with different configurations & ML 🔗 chemrxiv.org/engage/chemr...

1/4 🚀 Announcing the 2025 Protein Engineering Tournament. This year’s challenge: design PETase enzymes, which degrade the type of plastic in bottles. Can AI-guided protein design help solve the climate crisis? Let’s find out! ⬇️ #AIforBiology #ClimateTech #ProteinEngineering #OpenScience

Closing the loop on #GenAI for #GPCR #SBDD www.nature.com/articles/s41... tinyurl.com/yeyhfr7j

Now in JCIM: pubs.acs.org/doi/full/10....

🚀 After two+ years of intense research, we’re thrilled to introduce Skala — a scalable deep learning density functional that hits chemical accuracy on atomization energies and matches hybrid-level accuracy on main group chemistry — all at the cost of semi-local DFT ⚛️🔥🧪🧬

CACHE4 results are out! All previously known CBLCB ligands shared the same scaffold. Congrats to Keunwan Park who successfully designed a chemically novel series, to the experimental team at @thesgc.bsky.social and thanks to @conscience-network.bsky.social for greasing the wheels! bit.ly/4mYNe3r

This week's cover of @rsc.org @chemicalscience.rsc.org AIMNet2: a neural network potential to meet your neutral, charged, organic, and elemental-organic needs. pubs.rsc.org/en/content/a... #compchem #chemsky

Excited to unveil Boltz-2, our new model capable not only of predicting structures but also binding affinities! Boltz-2 is the first AI model to approach the performance of FEP simulations while being more than 1000x faster! All open-sourced under MIT license! A thread… 🤗🚀

#compchem #machinelearning If you want to know more about #FeNNix-Bio1, the first foundation model able to perform accurate - long timescale- condensed phase molecular simulations of biological systems at quantum accuracy, join me in incoming live presentations: www.linkedin.com/feed/update/...

Our new preprint PharmacoForge: Pharmacophore Generation with Diffusion Models is out now! PharmacoForge quickly generates pharmacophores for a given protein pocket that identify key binding features and find useful compounds in a pharmacophore search. Check it out! 🧪 doi.org/10.26434/che...

The Open Molecules 2025 dataset is out! With >100M gold-standard ωB97M-V/def2-TZVPD calcs of biomolecules, electrolytes, metal complexes, and small molecules, OMol is by far the largest, most diverse, and highest quality molecular DFT dataset for training MLIPs ever made 1/N

Check out AceFF 1.1 huggingface.co/Acellera/Ace...

#compchem New preprint: "A Foundation Model for Accurate Atomistic Simulations in Drug Design" FeNNix-Bio1, a foundation #machinelearning model for biosimulations doi.org/10.26434/che... #compchemsky #biosky Great work by T. Plé & the teams @lct-umr7616.bsky.social & @qubit-pharma.bsky.social

👋 🤖 Meet El Agente–an autonomous AI for performing computational chemistry, made by the Matter Lab @uoft.bsky.social. This #LLM-powered multi-agent system making computational chemistry more accessible will soon be available worldwide. Sign up 4 the launch: acceleration.utoronto.ca/news/meet-el...

@thesgc.bsky.social is generating large/open screening data and inviting data scientists to train their ML models via DREAM challenges: 1- train your model on DEL data 2- retrospectively predict 138 ASMS true positives 3- predict new hits. We will test them and publish together. bit.ly/3YXVKoT

"De novo prediction of protein structural dynamics" I'll be presenting an overview of the field tomorrow at a workshop. Link to a PDF copy of the presentation: delalamo.xyz/assets/post_...

Encode protein structures as a series of discrete tokens, train a language model, and sample protein structural conformations given the sequence. arxiv.org/abs/2410.18403

AlphaFold is amazing but gives you static structures 🧊 In a fantastic teamwork, @mcagiada.bsky.social and @emilthomasen.bsky.social developed AF2χ to generate conformational ensembles representing side-chain dynamics using AF2 💃 Code: github.com/KULL-Centre/... Colab: github.com/matteo-cagia...

New preprint: Finding Drug Candidate Hits With a Hundred Samples: Ultra-low Data Screening With Active Learning doi.org/10.26434/che... #compchem

The future of AI-drug discovery hinges on large, high-quality, standards-based datasets. No country or firm can build this alone. We need to construct datasets together in the open: www.science.org/doi/10.1126/... @tridentpct.bsky.social @conscience-network.bsky.social @mcgilluniversity.bsky.social

Run BioEmu in Colab - just click "Runtime → Run all"! Our notebook uses ColabFold to generate MSAs, BioEmu to predict trajectories, and Foldseek to cluster conformations. Thanks @jjimenezluna.bsky.social for the help! 🌐 colab.research.google.com/github/sokry... 📄 www.biorxiv.org/content/10.1...

AlphaFold, the revolutionary, Nobel prize-winning tool for predicting protein structures, has a problem: it’s running low on data https://go.nature.com/3FJRyTd

🚀One week left to register for our Symposium on Open Drug Discovery! Join us in Montreal April 7-8 for an exciting program showcasing how open science and AI are driving drug discovery. Some sessions are already sold out, so register now! Register by April 2nd: conscience.ca/symposium2025

This is a remarkable paper! A gigantic dataset of highly precise, highly accurate first-principles data. This builds on years of work on @fhi-aims.bsky.social - enabling dispersion-corrected hybrid DFT that covers a huge swath of chemical space. Congrats to the authors! doi.org/10.1038/s415...

🚀 100 scientists. 31 countries. And we’re just getting started. #MAINFRAME is uniting global experts to drive AI-powered hit finding. ML models trained on real experimental data. Predictive tools tested in the lab. 🔗 Now is the time to join: aircheck.ai/mainframe

New Perspective on Community Benchmarking in Structure-Based Drug Design (SBDD)! #SBDD predictions need reliable benchmarks - diverse targets, high-quality affinity & structural data, and blinded validation. Let’s make it happen! 🔗 Read more: doi.org/10.1021/acs.... #DrugDiscovery #CompChem

The code & camera-ready version of our #ICLR2025 paper on "Multi-domain Distribution Learning for De Novo Drug Design" are now available 📚 Paper: openreview.net/forum?id=g3V... 💻 Code: github.com/LPDI-EPFL/Dr... (1/4)

...and kudo to Karina Machado and @dkoes.compstruct.org for their winning predictions and to @karlasatchell.bsky.social for the unwinding assays!

The CACHE #2 preprint is now online: bit.ly/3DyCmHN Active learning and fragment growing delivered confirmed hits. A citizen scientist using the Fold-it gaming interface designed the top compound! Kudos to Sasha and Madhushika @thesgc.bsky.social at the bench. @conscience-network.bsky.social

Today's #RDKit blog post is a tutorial on using the AdjustQueryProperties function to have more control over substructure queries greglandrum.github.io/rdkit-blog/p...

Stand with UKRAINE! #standWithUkraine

Very excited for this Symposium on Open Drug Discovery in Montreal, many thanks to @conscience-network.bsky.social for the opportunity to talk about our work in Cache2! #compchem

From flat to sat, and back: About that “Escape from Flatland” paper… open.substack.com/pub/medchema...

✨Symposium session reveal✨ Featuring @albertantolin.bsky.social and @karmencj.bsky.social, this session highlights initiatives enabling communities to come together to solve some of the biggest challenges in drug discovery. Register here: conscience.ca/symposium2025

Watch out for an upcoming bluetorial/tweetorial on this work from the amazing @alisiafadini.bsky.social! www.biorxiv.org/content/10.1...

The BioEmu-1 model and inference code are now public under MIT license!!! Please go ahead, play with it and let us know if there are issues. github.com/microsoft/bi...

🌍 In the world of drug discovery, knowing a drug's residence time (τ) on its target can significantly impact its efficacy. Our new study presents innovative methods for predicting τ efficiently and accurately! 🧵🧵🧵

Excited to share our latest preprint evaluating AlphaFold3, Boltz-1, Chai-1 and Protenix for predicting protein-ligand interactions, featuring our newly introduced benchmark dataset 🌹Runs N’ Poses🌹! www.biorxiv.org/content/10.1... 🧵👇 (1/n)

We're changing the field of #compchem by creating free and open-source software for performing alchemical free energy calculations. Our flagship protocol calculates relative binding free energies of protein-ligand systems. Try it out in your browser: colab.research.google.com/github/OpenF...

Fun listening to Karina Machado tell the story about how her team did so well in the #Cache compound prediction challenge. Scientists in the global south can compete with anyone on the planet if given a level playing field!

Seeing a lot of this lately...

A Perspective from Xiaoyu Zhang, Gabriel Simon, and Benjamin Cravatt discusses recent strategies to expand the E3 ligase landscape and the scope of targeted protein degradation www.nature.com/articles/s41...

Grappa is out: pubs.rsc.org/en/content/a... We are looking forward to feedback from and extensions by the community! Try it out for your favorite (bio)molecules - ligands, post-translational modifications, metal-enzymes, DNA, ...

Machine Learning in Drug Discovery Resources page updated for 2025. github.com/PatWalters/r...

Helpful!

Thinking about attending? There's still time to take advantage of our Early Bird discount until January 31st! We're also offering $50 tickets for students and postdocs (that's 75% off!) and we'll be opening abstract submissions early next week - so stay tuned!

We’re excited about the potential of seeing these datasets and benchmarks integrated into Polaris. Stay tuned for updates! 👀 Read the paper: arxiv.org/abs/2411.09820