New Practical Cheminformatics post, "Three Papers Demonstrating That Co-folding Still Has a Ways to Go”. https://t.co/uTtjdcRuHC

New Practical Cheminformatics Post, "Useful RDKit Utils - A Mötley Collection of Helpful Routines" https://t.co/MaP7vjkQ39

Everyone: freaking out about 50-year mortgages. Me: predicting Bitcoin’s Friday price for the $10K pot like a responsible adult.

The latest Practical Cheminformatics post, “The Trouble With Tautomers,” emerged from a discussion about the impact of tautomers on machine learning model predictions. https://t.co/nylhStlG42

Integration Chembl REST API and Claude with MCP #cheminformatics #mcp #ai

The latest addition (#33) to the Practical Cheminformatics Tutorials series explores Bayesian optimization of reaction conditions. https://t.co/NEii9bKEaN

In a new Practical Cheminformatics post titled "Even More Thoughts on ML Method Comparisons," I share several plots that I find valuable for comparing machine learning methods. https://t.co/4JaGk3n8bD

Machine Learning in Drug Discovery Resources page updated for 2025.

If you are a Pulsechain KOL that would like to generate some extra cashflow to buy HEX or PLS dip, You should definitely try Partner System from XGame web3 gaming app. Some of the ones using it are starting to ramp up steadily.

ChEMBL 35 is out. Happy Holidays! https://t.co/FCJOpVV3Gs

Excellent new paper (with code) by my former colleagues Steven Kearnes and Patrick Riley describing a procedure for associating confidence levels with regression model predictions in drug discovery.

I'm not happy with the way this all went down. I have tremendous respect for Gabriele and the rest of the DiffDock authors. Their work has broken new ground and helped advance machine learning in drug discovery. If I had to do it over again, I'd do things differently.

@prof_ajay_jain's response is here.

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My "response to the response" is here.

Many of you have seen Gabriele Corso's response to our recent preprint. If you haven't, it's here.

I'm thrilled to announce a new preprint describing collaborative work with @prof_ajay_jain and Ann Cleves Jain, "Deep-Learning Based Docking Methods: Fair Comparisons to Conventional Docking Workflows". https://t.co/8WzcGYlQAQ

There’s a new Practical Cheminformatics post, “Some Thoughts on Dataset Splitting,” (with code and a robot cartoon) at

Well, @OpenAI just banned @ChatGPT from giving medical advice. @Doctronic is built different: peer-reviewed clinical validation, a network of licensed physicians across all 50 states, and partnerships that let us keep expanding. We're not pulling back. We're moving forward.

Introducing our first proposed set of guidelines for method comparison in small molecule property prediction! Crafted by the Small Molecule Steering Committee, the pre-print introduces statistically rigorous, domain-appropriate comparison protocols for small molecule predictive

Excited to introduce the first steering committee (SC) from Polaris! This group of industry experts is focused on small-molecule, predictive modelling tasks and is collaborating to develop guidelines for benchmarking best practices. At Polaris, our mission is to bring innovators

There’s a new Practical Cheminformatics blog post, “Silly Things Large Language Models Do With Molecules.” In this post, I explain why general-purpose LLMs aren’t appropriate for analog generation and suggest better alternatives.

Thanks to everyone who attended the AI in Drug Discovery Workshop at the RSC 7th Symposium on AI in Chemistry.  We’ve made the materials (slides, Jupyter notebooks, resource list) from the three hour workshop available on GitHub.  #AIChem24 https://t.co/2Seu2PcNgj

Crypto has never reached mass adoption. Why is that? Endless complexity. High costs? Siloed chains? Scams & blockchains that mimic legacy systems? Satoshi gave us P2P cash. Others had a vision of a world computer. Can we have both & unite crypto? 1/14

BindingDB in 2024: a FAIR Knowledgebase of Protein-Small Molecule Binding Data - This paper provides an update on BindingDB, a critical resource offering 2.9 million protein-small molecule binding data points across 1.3 million compounds, significantly expanding since 2016. -