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Thrilled to announce a preprint describing collaborative work between our group and James Fraser (A$AP J), @BShoichet, and Adam Renslo. The paper shows a practical application of the Thompson Sampling method we published earlier this year. biorxiv.org/content/10.110…

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. -

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 github.com/volkamerlab/ai…

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. practicalcheminformatics.blogspot.com/2024/10/silly-…

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

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

There’s a new Practical Cheminformatics post, “Some Thoughts on Dataset Splitting,” (with code and a robot cartoon) at practicalcheminformatics.blogspot.com/2024/11/some-t…

I'm thrilled to announce a new preprint describing collaborative work with Ajay Jain and Ann Cleves Jain, "Deep-Learning Based Docking Methods: Fair Comparisons to Conventional Docking Workflows". arxiv.org/abs/2412.02889

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. pubs.acs.org/doi/10.1021/ac…

ChEMBL 35 is out. Happy Holidays! chembl.blogspot.com/2024/12/heres-…

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

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. practicalcheminformatics.blogspot.com/2025/03/even-m…

The latest addition (#33) to the Practical Cheminformatics Tutorials series explores Bayesian optimization of reaction conditions. github.com/PatWalters/pra…

Integration Chembl REST API and Claude with MCP #cheminformatics #mcp #ai iwatobipen.wordpress.com/2025/05/04/int…

The latest Practical Cheminformatics post, “The Trouble With Tautomers,” emerged from a discussion about the impact of tautomers on machine learning model predictions. patwalters.github.io/The-Trouble-Wi…

New Practical Cheminformatics Post, "Useful RDKit Utils - A Mötley Collection of Helpful Routines" patwalters.github.io/Useful-RDKit-U…