Research group led by Charlotte Deane, based in the Department of Statistics at the University of Oxford.
Oxford, England
Joined November 2018
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Oxford Protein Informatics Group (OPIG) retweeted
I am honoured to have been awarded the Corcoran Memorial Prize from @OxfordStats for my DPhil research on ML for antibody design.
The Corcoran Memorial Prize & Lectures are named in memory of Stephen Corcoran, who was a graduate student in the Department of Statistics.
We're also happy to share that "Inferring residue level hydrogen deuterium exchange with ReX" by Oliver Crook, Charlotte Deane, and co-authors Nathan Gittens & Chun-wa Chung from GSK, was published in Communications Chemistry in the tail end of 2025.
nature.com/articles/s42004-0…
Oxford Protein Informatics Group (OPIG) retweeted
Starting off our session on Intelligent Molecular Structures with a fantastic plenary lecture by Charlotte Deane from @UniofOxford on how we can move beyond static protein structure prediction.
#NCBSAnnualTalks2026
@OPIGlets
(3/n)
Next, we are happy to announce that our pandemic preparedness orthopoxvirus antibody database “Pox-AbDab” has now been published in Frontiers in Immunology. First data update to come later in January!
Paper: doi.org/10.3389/fimmu.2025.1…
Database: opig.stats.ox.ac.uk/webapps/…
A happy new year from all at OPIG!
We start 2026 with an article in Expert Opinion on Drug Discovery by Charlotte Deane and co-founders at DaltonTx; a perspective on integrating computation into drug discovery for maximum added value & efficiency
tandfonline.com/doi/full/10.…
Oxford Protein Informatics Group (OPIG) retweeted
My first full contribution from my time in @OPIGlets is out!
We present created FlAbDab and FTCRDab: two large-scale, MD datasets to study flexibility in immune receptors. Find all the details and links to the databases in the preprint manuscript:
doi.org/10.1101/2025.11.10.6…
Excited to share our new review on deep learning for structure-based drug design! 🎉
pubs.rsc.org/en/content/arti…
Authors: @LucyVost*, Yael Ziv*, Charlotte Deane
We cover the evolution from early shape-based strategies to modern co-folding models, detailing how different representations of protein pockets (voxel and graph) can encode structural information (shape, interactions, all-atom detail) and guide molecular generation.
We highlight key advances and remaining challenges in this emerging structure-aware paradigm, and discuss how integrating protein information can enable AI to design molecules with stronger binding potential and real-world drug-like properties.
pubs.rsc.org/en/content/arti…
Recently, Prof. Charlotte Deane participated in a discussion about AI as part of the Bradford Science Festival. Read some of her (and the other participants') thoughts here:
blog.scienceandmediamuseum.o…
📜 New preprint!
Syndirella is a pipeline for proposing synthesis-directed elaborations for fragment-inspired designs with explicit routes and poses!
Preprint: chemrxiv.org/engage/chemrxiv…
Code: github.com/oxpig/syndirella
Syndirella proposes congeneric series you can actually make (multi-step, digitized routes) and explores the pocket more broadly. Additionally, by buying reactants (not products), it allows you to test far more designs for the same budget
Oxford Protein Informatics Group (OPIG) retweeted
AI models show promise for accelerating antibody drug discovery but can fall short in testing.
Research from @OPIGlets, published in Nature Computational Science highlights the need for larger, and more diverse datasets for reliable prediction.
👉 tinyurl.com/rzemvhkz
ALT 3D model of an antibody protein with dark and light blue regions showing its Y-shaped structure. Credit: Alissa Hummer
Please be aware that OPIG's website and web apps will be down for maintenance from 09:30 UTC on Tuesday 14th October 2025, and will be unavailable for approximately one hour. Apologies for any inconvenience and for the short notice of this downtime.
AIR Street Capital's "State of AI" 2025 Report references Nicholas Runcie, Charlotte Deane, and Fergus Imrie's work on Assessing the Chemical Intelligence of Large Language Models.
Read the whole report here: stateof.ai/
And preprint here: lnkd.in/gbuNXR93
🪩The one and only @stateofai 2025 is live! 🪩
It’s been a monumental 12 months for AI. Our 8th annual report is the most comprehensive it's ever been, covering what you *need* to know about research, industry, politics, safety and our new usage data.
My highlight reel:
🚨 We’re hiring!
The OPIG group is looking for multiple postdocs to join OpenBind, an open science initiative generating foundational structural biology data to power the next era of AI/ML for drug discovery.
opig.stats.ox.ac.uk/
openbind.uk/
Postdocs will contribute to:
- Developing and applying AI/ML methods for small molecule design and selection
- Running blind community challenges
- Assessing the value of large-scale structural biology datasets
If this sounds interesting, we’d love to hear from you (email [email protected] or [email protected])!
Positions available to start immediately.