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Reposted by Matthieu Schapira

The Matter Lab @thematterlab.bsky.social · Aug 21

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
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Matthieu Schapira @mattschap.bsky.social · Aug 12

CACHE 7 is launched with support from the @gatesfoundation.bsky.social and unpublished data from Damian Young at @bcmhouston.bsky.social, Tim Willson @thesgc.bsky.social and Neelagandan Kamaria InSTEM.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

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Pat Walters @wpwalters.bsky.social · Jul 22

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

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Noel Research Group @noelgroupuva.bsky.social · Jul 10

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...

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Reposted by Matthieu Schapira

The Align Foundation @alignbio.bsky.social · Jul 8

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🚀 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

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Chris de Graaf @cdg-gpcr.bsky.social · Jul 2

Closing the loop on #GenAI for #GPCR #SBDD

www.nature.com/articles/s41...

tinyurl.com/yeyhfr7j

Identification of nanomolar adenosine A2A receptor ligands using reinforcement learning and structure-based drug design - Nature Communications

Here the authors combine a deep generative model with structure-based drug design and prospectively validate functionally active, nanomolar, A2A adenosine receptor ligands and solve their crystal stru...

www.nature.com

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Matthieu Schapira @mattschap.bsky.social · Jun 20

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

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Jan Hermann @jan.hermann.name · Jun 18

🚀 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 ⚛️🔥🧪🧬

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Matthieu Schapira @mattschap.bsky.social · Jun 16

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

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Olexandr Isayev 🇺🇦 🇺🇸 @olexandr.bsky.social · Jun 11

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

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Gabriele Corso @gcorso.bsky.social · Jun 6

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… 🤗🚀

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Jean-Philip Piquemal @jppiquem.bsky.social · Jun 7

#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/...

#fennix #machinelearning #gtc25 #cecam #watoc #vivatech #ai #docking #gpu… | Jean-Philip Piquemal

If you want to know more about #FeNNix-Bio1, the first #machinelearning foundation model able to perform accurate - long timescale- condensed phase molecular simulations of biological systems at quant...

www.linkedin.com

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Reposted by Matthieu Schapira

Emma Flynn @emmaflynn.bsky.social · May 27

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...

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Sam Blau @samblau.bsky.social · May 14

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

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Gianni De Fabritiis @gdefabritiis.bsky.social · May 7

Check out AceFF 1.1

huggingface.co/Acellera/Ace...

Acellera/AceFF-1.1 · Hugging Face

We’re on a journey to advance and democratize artificial intelligence through open source and open science.

huggingface.co

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Jean-Philip Piquemal @jppiquem.bsky.social · May 6

#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

A Foundation Model for Accurate Atomistic Simulations in Drug Design

Neural network potentials now offer robust alternatives to electronic structure and empirical force fields computations for the on-the-fly production of the potential energy surfaces required in atomi...

doi.org

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Reposted by Matthieu Schapira

Acceleration Consortium @accelerationc.bsky.social · May 6

👋 🤖 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...

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Matthieu Schapira @mattschap.bsky.social · May 5

@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

First DREAM Target 2035 Drug Discovery Challenge

'First DREAM Target 2035 Drug Discovery Challenge' (Synapse ID: syn65660836) is a project on Synapse. Synapse is a platform for supporting scientific collaborations centered around shared biomedic...

bit.ly

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Diego del Alamo @delalamo.xyz · Apr 27

"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_...

delalamo.xyz

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Kevin K. Yang 楊凱筌 @kevinkaichuang.bsky.social · Apr 25

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

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Kresten Lindorff-Larsen @lindorfflarsen.bsky.social · Apr 17

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...

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Jan H. Jensen @janhjensen.bsky.social · Apr 18

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

a depiction of the active learning cycle: smaple-train-predict-repeat

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E. Richard Gold @richardgold.bsky.social · Apr 10

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

AI drug development’s data problem

The future of drug discovery may be artificial intelligence (AI), but its present is not. AI is in its infancy in the field. To help AI mature, developers need nonproprietary, open, large, high-qualit...

www.science.org

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Martin Steinegger 🇺🇦 @martinsteinegger.bsky.social · Mar 29

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...

Google Colab

colab.research.google.com

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Nature @nature.com · Mar 27

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

AlphaFold is running out of data — so drug firms are building their own version

Thousands of 3D protein structures locked up in big-pharma vaults will be used to create a new AI tool that won’t be open to academics.

go.nature.com

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