Author

Martin Buttenschoen

University of OxfordORCID 0000-0002-5455-4207Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Research Focus:protein structure prediction· 2 Research Focus:drug response / drug discovery· 1 Assay:protein structure· 1 Approach:statistical model· 1

Frequent Co-Authors

Charlotte Mary DeaneiD· 2 shared Anna CarberyiD· 1 shared Brian D. MarsdeniD· 1 shared F. von DelftiD· 1 shared Lukas Scheiblerger· 1 shared R. SkyneriD· 1 shared Yael ZiviD· 1 shared

Activity by Year

2024-2025 · peak 1/yr

Co-Author Collaboration Network

7 top collaborators · 12 mutual co-author links

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2 shared papersMolecular Biology

Charlotte Mary DeaneORCID

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2 papers

Recent·Most cited

INTERPOLATION-BASED CONDITIONING OF FLOW MATCHING MODELS FOR BIOISOSTERIC LIGAND DESIGN

Yael Ziv, Martin Buttenschoen, Lukas Scheiblerger, Brian D. Marsden, Charlotte Mary Deane

The paper introduces two conditioning strategies for flow-matching models to generate bioisosteric 3D molecules without retraining, demonstrating effectiveness on drug-relevant tasks.

bioRxiv · Oct 20, 2025 · PreprintMolecular Biology

Learnt representations of proteins can be used for accurate prediction of small molecule binding sites on experimentally determined and predicted protein structures

Anna Carbery, Martin Buttenschoen, R. Skyner, F. von Delft, Charlotte Mary Deane

The paper introduces IF-SitePred, a method for predicting protein-ligand binding sites using learned protein representations, showing improved performance on predicted structures and simulated novel proteins.

Journal of Cheminformatics · Mar 14, 2024Peer-reviewedBioinformatics