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.
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)
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…
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
Oxford Protein Informatics Group (OPIG) retweeted
AI is changing the discipline of Biology- but can it crack one of science’s hardest problems: drug discovery? At the center of that challenge is Professor Charlotte Deane, who joins us at #ISMBECCB2025! @iscb @OPIGlets youtu.be/PyZbeoLsLuQ
Oxford Protein Informatics Group (OPIG) retweeted
Our work exploring the ability of and requirements for ML to predict the effects of mutations on antibody–antigen binding affinity (ΔΔG) is out now in @NatComputSci!
Out now! @AlissaHummer, @OPIGlets and colleagues present Graphinity, a method to predict change in antibody-antigen binding affinity (∆∆G). Featuring synthetic datasets of ~1 million FoldX-generated and >20,000 Rosetta Flex ddG-generated ∆∆G values!
nature.com/articles/s43588-0…
Oxford Protein Informatics Group (OPIG) retweeted
Out now! @AlissaHummer, @OPIGlets and colleagues present Graphinity, a method to predict change in antibody-antigen binding affinity (∆∆G). Featuring synthetic datasets of ~1 million FoldX-generated and >20,000 Rosetta Flex ddG-generated ∆∆G values!
nature.com/articles/s43588-0…
Oxford Protein Informatics Group (OPIG) retweeted
MolSnapper: Conditioning Diffusion for Structure-Based Drug Design #DrugDesign
pubs.acs.org/doi/10.1021/acs…
@YaeliZiv @fergus_imrie @bmarsden19 @OPIGlets
#JCIM Vol65 Issue9 #MachineLearning #DeepLearning
Oxford Protein Informatics Group (OPIG) retweeted
🚀 LLMs can now do chemistry! Our new preprint shows that state-of-the-art reasoning models can now perform advanced chemical reasoning tasks, without any assistance from external tools. Here’s what o3-mini can already do👇 (1/🧵)
Oxford Protein Informatics Group (OPIG) retweeted
Do you wish working with T-cell receptor structures was easier?
Us too!
STCRpy, our software suite for TCR structure parsing, interaction profiling and machine learning dataset preparation is now available!
Github: github.com/npqst/stcrpy/
Pre-print: doi.org/10.1101/2025.04.25.6…
1/3
Oxford Protein Informatics Group (OPIG) retweeted
Was an honour for our collaboration with Sarosh Irani's group to be recognised with the PNAS Cozzarelli Prize #immunoinformatics #encephalitis #autoreactivity #bcells
Join us in celebrating our 2024 Cozzarelli Prize Class IV: Biomedical Sciences winning paper, “Ultrahigh frequencies of peripherally matured LGI1- and CASPR2-reactive B cells characterize the cerebrospinal fluid in autoimmune encephalitis.” Read more: ow.ly/SyAL50VyXLV
ALT ALT/Caption: 2024 Cozzarelli Prize Winner. Class II Winner: “Ultrahigh frequencies of peripherally matured LGI1- and CASPR2-reactive B cells characterize the cerebrospinal fluid in autoimmune encephalitis” Authors: Jakob Theorell, Ruby Harrison, Robyn Williams, et al.
Oxford Protein Informatics Group (OPIG) retweeted
3-year postdoc opportunity as part of the Novo Nordisk - Oxford Fellowship programme!
Develop machine learning approaches for drug discovery with me, Charlotte Deane (Oxford), and Christos Nicolaou (Novo Nordisk).
1 week left to apply! Details in next post
Oxford Protein Informatics Group (OPIG) retweeted
AF2χ: Predicting protein side-chain rotamer distributions with AlphaFold2
Oxford Protein Informatics Group (OPIG) retweeted
I'm so excited to join this interdisciplinary community as a 2025 Schmidt Science Fellow!
After years behind a keyboard, I will be pivoting toward the wet lab. To unlock the true potential of ML for biology/biomedicine, we need high-quality data and robust evaluation 🔬🧫🧪
We are excited to announce our 2025 Schmidt Science Fellows! 32 early career researchers, nominated by the world’s leading research universities, who will take an interdisciplinary approach to advancing discovery schmidtsciencefellows.org/ne…
Oxford Protein Informatics Group (OPIG) retweeted
Really happy that our work on conditioning diffusion models is published - have a read if you fancy hearing how we tried to encourage models to generate more physically plausible compounds by training conditionally with synthetic, distorted molecules!
In this week's first featured article Deane et al. introduce an approach for improving generative molecular design. Distorted molecules with quality labels are added to training data, allowing the model to distinguish unfavourable conformations. Read more: doi.org/10.1039/D4DD00331D
ALT A distorted training dataset is added to an original traning dataset. A comparison of molecules from the trained models is provided.
Oxford Protein Informatics Group (OPIG) retweeted
I am happy to say this work is now published in Frontiers in Immunology!
frontiersin.org/journals/imm…
Again, I would like to thank my supervisors @hashemkoohy and @OPIGlets for their guidance and @drchristhorpe and @Jamie_Rossjohn for their collaboration on this work.
Oxford Protein Informatics Group (OPIG) retweeted
Happy to share that Humatch, @OPIGlets new humanisation tool, is now available at mAbs - doi.org/10.1080/19420862.202…
Please also check out the code on GitHub (web server coming soon!) - github.com/oxpig/Humatch
Highlights🧵in previous tweet - x.com/LewisChinery/status/18…
Prefer your antibodies to be human? Then please check out Humatch!
Preprint - doi.org/10.1101/2024.09.16.6…
Code - github.com/oxpig/Humatch
Data - zenodo.org/records/13764770
@OPIGlets
Oxford Protein Informatics Group (OPIG) retweeted
AlphaFold2+MD simulations = powerful insights into protein conformational ensembles, but can it capture all experimental structural variations? Great collaborative effort!! @Structure_CP @RRiccabona @OPIGlets @scrippsresearch @DTUtweet #compchem sciencedirect.com/science/ar…
Oxford Protein Informatics Group (OPIG) retweeted
Prefer your antibodies to be human? Then please check out Humatch!
Preprint - doi.org/10.1101/2024.09.16.6…
Code - github.com/oxpig/Humatch
Data - zenodo.org/records/13764770
@OPIGlets