Matthieu Schapira
mattschap.bsky.social
Matthieu Schapira
@mattschap.bsky.social
Prof @ U. Toronto - PI @ SGC - CACHE challenges - Computational chemistry- Structural bioinformatics - Biophysics
Reposted by Matthieu Schapira
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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August 21, 2025 at 8:05 PM
CACHE 7 is launched with support from the @gatesfoundation.bsky.social and unpublished data from Damian Young at @bcmhouston.bsky.social, Tim Willson @thesgc.bsky.social and Neelagandan Kamaria InSTEM.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
August 12, 2025 at 7:07 PM
Reposted by Matthieu Schapira
New Practical Cheminformatics Post
patwalters.github.io/Three-Papers...
July 22, 2025 at 1:40 PM
Reposted by Matthieu Schapira
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...
July 10, 2025 at 3:06 PM
Reposted by Matthieu Schapira
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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
July 8, 2025 at 4:26 PM
June 20, 2025 at 2:36 PM
Reposted by Matthieu Schapira
🚀 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 ⚛️🔥🧪🧬
June 18, 2025 at 11:24 AM
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
June 16, 2025 at 4:14 PM
Reposted by Matthieu Schapira
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
June 11, 2025 at 6:18 PM
Reposted by Matthieu Schapira
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… 🤗🚀
June 6, 2025 at 1:46 PM
Reposted by Matthieu Schapira
#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
June 7, 2025 at 11:52 AM
Reposted by Matthieu Schapira
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...
May 27, 2025 at 7:11 PM
Reposted by Matthieu Schapira
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
May 14, 2025 at 8:52 PM
Reposted by Matthieu Schapira
#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
May 6, 2025 at 7:35 AM
Reposted by Matthieu Schapira
👋 🤖 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...
May 6, 2025 at 1:27 PM
@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
May 5, 2025 at 1:58 PM
Reposted by Matthieu Schapira
"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
April 27, 2025 at 2:16 PM
Reposted by Matthieu Schapira
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
April 25, 2025 at 9:11 PM
Reposted by Matthieu Schapira
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...
April 17, 2025 at 7:11 PM
Reposted by Matthieu Schapira
New preprint: Finding Drug Candidate Hits With a Hundred Samples: Ultra-low Data Screening With Active Learning doi.org/10.26434/che... #compchem
April 18, 2025 at 11:01 AM
Reposted by Matthieu Schapira
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
April 10, 2025 at 8:16 PM
Reposted by Matthieu Schapira
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
March 29, 2025 at 9:50 AM
Reposted by Matthieu Schapira
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
March 27, 2025 at 11:06 AM