The ChEMBL-og

Slides and recordings from the recent ChEMBL UGM are starting to appear on the meeting website. Here I want to draw attention to the presentation by Nicolas Bosc and myself on " SureChEMBL: Your next source of research data ". Ever since my NextMove Software days, I've been aware of the large amount of scientific data available in patents. This includes everything from large sets of chemical analogs, to bioactivity values, reactions, and NMR spectra. US patents in particular are a rich source of data as they are (a) born digital, and (b) freely available, and thus automated tools to extract relevant data can generate substantial high quality datasets. For example, here's a graph I did back in 2017 to illustrate a NextMove Software blog post entitled "Are more bioactivities available from patents than from the academic literature?". This compared the data deposited from papers into ChEMBL and that extractable by LeadMine from patents (see the talk linked fr...

The Chemical Biology Services team invites applications for a 3-year ARISE2 Postdoctoral Fellowship – a unique postdoctoral opportunity that combines advanced research training with hands-on experience in developing innovative technologies and methods to enhance scientific services. Why apply? Make an Impact: Collaborate on high-impact projects that will directly shape and improve the scientific services we provide. Tailored to You: Each fellowship project is developed in collaboration with the fellow and the host team – possibly even involving an industry partner – to ensure a project that combines your ideas with the vision of of the host. Prepare for the Future: The ARISE2 Fellowship is designed to prepare fellows for dynamic careers within research infrastructures, providing both technical depth and professional development. If this sounds interesting, please get in touch by the end of August at oboyle@ebi.ac.uk with your CV. Note that we recruit worldwide. Here is...

We are looking for a highly motivated Computational Biologist / Bioinformatician (*) to join the Chemical Biology Resources team at the European Bioinformatics Institute (EMBL-EBI), located on the Wellcome Genome Campus near Cambridge, as part of the Wellcome Trust funded LIGMAP project, a multi-disciplinary collaboration between University College London and EMBL-EBI. LIGMAP is an ambitious multiyear project, led by University College London, to identify the endogenous ligands of the many proteins of unknown function in the proteome using AI-based methods as well as classical machine learning. You will work closely with the PDBe team at EMBL-EBI, as well as leading researchers in structural biology and machine learning at University College London, to deliver the goals of the project. You will develop descriptors to characterise the binding site of proteins in terms of their ability to recognise ligands, and use these to assess druggability of protein binding sites.   This positi...

ChEMBL 37 arrives with nearly three million compounds, a new modality field for capturing targeted protein degraders, and a wave of data quality improvements.    A new field for targeted protein degradation Around 29,000 bioactivity data points have been annotated with     ACTIVITIES.MODALITY  = “Targeted Protein Degradation” , including around 3,000 legacy bioactivities from approximately 1,200 remapped assays. This marks ChEMBL’s first systematic effort to flag TPD data across the database.        Extensive update of literature data Scientific literature remains the backbone of ChEMBL, and ChEMBL 37 brings one of the more substantial literature updates in recent releases. Compared to ChEMBL 36, the literature source gained approximately 79,000 new assays, 270,000 new bioactivity data points, and 52,000 new compound records — pushing the total literature-derived activity count past 9.55 million. Twelve new c...

  ChEMBL extracts data from the core medicinal chemistry literature and therefore reflects ongoing developments in drug discovery. One area currently attracting high interest is targeted protein degradation: compounds that direct disease-causing proteins to the cell’s degradation machinery.  These modalities are both present and rapidly increasing within ChEMBL, providing an important data source for the community.   Targeted Protein Degradation Data in ChEMBL However, new and emerging modalities bring new challenges. Data should be well structured and FAIR, but for newer modalities, controlled vocabularies may not exist or adequately cover the breadth of data being reported. Cu ration effort in this area supports our broader goals towards generating bespoke datasets and improving AI-readiness.  W e recently had the opportunity to attend the first ISCB UK conference where we presented our work towards the capture and annotatio...

The full programme for the  ChEMBL UGM (June 10-11) is now available on our website. If you are interested in registering, you need to be quick as registration closes on 18th May. See you there.

  Dear ChEMBL and SureChEMBL Community, As you know we are dedicated to keeping ChEMBL and SureChEMBL world-class resources for the scientific community, but to do that effectively, we need to hear from you.  To ensure we are consistently meeting your research needs, we are excited to launch our latest ChEMBL User Survey . Why Your Feedback Matters As we plan the next phases and future developments for our platforms, this survey is your opportunity to have a direct impact. By sharing how you interact with our data, you help us understand what works, what doesn't, and what you need next. Your insights will allow us to: Refine the interface: Make navigating and extracting data smoother and more intuitive. Prioritize new features: Focus our development efforts on the tools that will best support your drug discovery and research processes. Evolve with you: Ensure that ChEMBL and SureChEMBL stay in sync with the...

I'm very excited. We now have a list of confirmed speakers for the upcoming ChEMBL UGM (June 10-11). Uday Abu-Shehab, University of Vienna Katie Beckwith, Ignota Labs Evan Bolton, PubChem Giovanni Cincilla, Healx Wei Dai, Queen Mary University of London Wim Dehaen, University of Chemistry and Technology Prague Luca Falciola, SCIBILIS Thierry Hanser, Ixelis Tobias Harren, Universität Hamburg Greg Landrum, ETH Zurich John Mayfield, NextMove Software John Overington, DrugHunter Carl Schiebroek, ETH Zurich Chris Southan, University of Edinburgh Brandon Walts, SciBite I think it's going to be a really exciting line-up covering a diverse range of topics.  If you still haven't signed up , note that the closing date for in-person registration is 18th May. Note also that we have a limit in numbers for Day Two, and it's first come, first served.

Just a quick note to say that Daniel Lowe has released OPSIN v.2.9.0 , the first release since Oct 2023. This is now available via the EMBL-EBI OPSIN server . The release notes describe a mixture of minor bug fixes and improvements: Support for IUPAC recommended primed number-letter locants e.g. 2''a Command-line output now includes warnings e.g. ambiguity SMILES writer now starts from a * atom if one is present Added numbering to nicotine Correctly interpretation of locanted perhalo terms and perhaloalkylalkanes Improved additive bond formation for phosphoryl Corrected locants on tolyl and assume p-tolyl if unspecified triazine is now interpreted as 1,3,5-triazine if unspecified Corrected interpretation of dithiazolium Fixed rare SMILES writing bug where slashes could be inconsistent Fixed ylidenethenylidene being parsed as [ylidene][thenylidene] instead of [yliden][ethenylidene] Fixed bug in spiro superscript inferring when a bridge is length 0 

I recently prepared a few slides on OPSIN for an internal presentation, and was looking for a simple use case. The first thing I tried turned out to be more interesting that I expected. If you visit the OPSIN website , there are three examples provided to illustrate its functionality. Daniel's original website, at the Uni of Cambridge, had 2,4,6-trinitrotoluene (TNT) as the example. With the move to EMBL-EBI and associated rewrite of the frontend, I thought about keeping this but decided that something more biologically-relevant would be appropriate. In the end, I comprised by keeping the 2,4,6- as a nod to the original, but used a saccharide instead: 2,4,6-tri-O-methyl-D-glucopyranose. Now click on "Search Google", to do a search using the InChIKey. My attention was drawn to the AI summary results, which I captured at the time (maybe you can tell when?) in the screenshot below: "The string  UTLUVTKMAWSZKV-NEIVSKJXSA-N is an InChIKey (International Chemical Identifie...

This is a reminder that the 2nd ChEMBL User Group Meeting will take place on June 10-11 on the Wellcome Genome Campus, Hinxton, near Cambridge, UK. This event is dedicated to building and supporting the ChEMBL and SureChEMBL user communities. This is a two day event; while hybrid attendance on Day 1 is possible, we really encourage in-person participation to allow you to meet the team, present your work, network, and to take part in Day 2 setting the scene for the future direction of the group. The deadline for speaker registration is two weeks from now, on 18th March so register now . We hope to see you there.

  A week ago, I had the pleasure of presenting SureChEMBL2.0 at the  Cambridge Cheminformatics Network Meeting , organised by Andreas Bender and kindly hosted by the  Cambridge Crystallographic Data Centre . It was a great opportunity to introduce one of the latest freely available databases of scientifically annotated patents to a broad scientific audience. The recording of the talk is now available  online , along with the  slides . What did I cover during this 30-minute talk? Why scientists should pay attention to patent data Why patents are challenging to work with What SureChEMBL is and what it does How we identify chemical compounds in patent documents What SureChEMBL 2.0 has recently introduced How we annotate patents for genes/proteins and diseases How we are improving the quality of structures extracted from images What you can download from the SureChEMBL core datasets — and what they contain Examples of queries that SureChEMBL h...

  AI-driven bioassay annotation strategy The continued expansion of ChEMBL bioactivity data makes high-quality, structured assay metadata essential for reproducible analysis and machine-learning applications aligned with FAIR principles. Recent work by our team  published in J. Cheminf. describes coordinated manual and AI-driven strategies to enhance the annotation, classification, and interoperability of ChEMBL bioassays.  In this work, we have developed a spaCy-based named entity recognition (NER) model trained on manually curated assay descriptions to identify the Experimental Method within ChEMBL assay descriptions. The model achieved cross-validated precision, recall, and F1-scores of approximately 0.93, 0.95, and 0.94, respectively, and detected experimental methods in ~57 % of binding and functional assays in ChEMBL 35. Extracted method terms were subsequently mapped to the Bioassay Ontology (BAO) , demonstrating good precision at higher confidence thresholds bu...

We are excited to announce the start of the LIGAND-AI project, a 5-year project involving 18 partners to find ligands for thousands of understudied protein targets. This project, led by the SGC (Structural Genomics Consortium) and Pfizer, is part of the SGC Target 2035 strategy to discover chemical modulators for every human protein by the year 2035. There are press releases on the EMBL-EBI and SGC webpages with additional information. Let's begin with chemical probes. These are potent and selective small molecules used to pharmacologically modulate a protein's function. These are not necessarily the starting point of a drug discovery campaign (though they may be); what they allow is the study of the target and investigation of its function. The key point is that for many protein targets we do not have a chemical probe, nor do we know their function. Targets without a chemical probe tend to be understudied as the lack of a chemical probe rules out many studies, and it ca...

    Drug modalities continue to evolve and the capture of data from recent literature ensures that ChEMBL remains up-to-date with recent developments. Drugs and clinical candidates in ChEMBL undergo enhanced curation , including annotation of their drug mechanisms (the therapeutic target with a role in disease efficacy and the action type of the drug against the entity, e.g. INHIBITOR). Classical small-molecule modulators typically bind to the active site of a target, leading to either a loss or, in some cases, an increase in protein function. More recently, emerging strategies such as Targeted Protein Degradation (TPD) have gained traction and instead remove (degrade) the target. The growing body of TPD data in ChEMBL will be discussed in this blog post.    Targeted Protein Degraders ( PROTACs ) from the ChEMBL database. To explore TPD data in ChEMBL, we’ve used a combination of TPD-relevant keywords and effector protein accessions (UniProt). If you’re interested in...

I am delighted to announce that registration is open for the 2nd ChEMBL User Group Meeting , which is dedicated to building and supporting the ChEMBL and SureChEMBL user communities. The last meeting took place in 2011, so it feels like it might be time for a second :-). The UGM will take place on 10-11 June here on the Wellcome Genome Campus, Hinxton, near Cambridge, UK. It is a two-day event, with participant numbers limited for Day 2. Day 1 (Hybrid, in-person recommended): Talks, discussions, and networking, followed by an evening reception with drinks. Lunch will be provided. Day 2 (In-person only): A chance to influence the future development of ChEMBL and SureChEMBL. Deeper community sessions together with the ChEMBL and SureChEMBL teams, discussion of collaboration opportunities. As a community event, we encourage poster and oral presentations from community members on any topic related to the use of ChEMBL or SureChEMBL. Please indicate when registering if you would like...

Over the years, ChEMBL has accepted 336 datasets deposited by the community. In fact, these data now comprise around 50% of the bioactivity data points. This is in addition to ChEMBL’s core data, bioactivity data extracted from the medicinal chemistry literature, and drug and clinical candidate data curated from regulatory authorities and clinical trials. However, ChEMBL - like many other open access databases - is currently facing a reduction in funding. While we remain committed to maintaining the core of ChEMBL’s literature-extracted bioactivity data as well as drug data annotations, these constraints mean that in the future we may not be able to accept data depositions unless they are accompanied by appropriate funding. This applies particularly to those that require extensive curation or substantial manual intervention (*). Any depositions that have been agreed or are already in progress will be handled as planned. Beyond this, we will continue to prioritise depositions that a...