Deane, Charlotte M.

Structurally mapping antibody repertoires

Krawczyk, K., Kelm, S., Kovaltsuk, A., Galson, J. D., Kelly, D., Trück, J., Regep, C., Leem, J., Wong, W. K., Nowak, J., et al. (2018) · Frontiers in Immunology

Monoclonal and Polyclonal Antibodies Researchvaccines and immunoinformatics approaches

Cited by 42

Towards the accurate modelling of antibody−antigen complexes from sequence using machine learning and information-driven docking

Giulini, M., Schneider, C., Cutting, D., Desai, N., Deane, C. M., & Bonvin, A. M. J. J. (2024) · Bioinformatics

Protein Structure and Dynamicsvaccines and immunoinformatics approaches

Cited by 41

Towards the accurate modelling of antibody-antigen complexes from sequence using machine learning and information-driven docking

Giulini, M., Schneider, C., Cutting, D., Desai, N., Deane, C. M., & Bonvin, A. M. J. J. (2023) · Bioinformatics

Protein Structure and Dynamicsvaccines and immunoinformatics approaches

Cited by 41

Looking for therapeutic antibodies in next generation sequencing repositories

Krawczyk, K., Raybould, M., Kovaltsuk, A., & Deane, C. M. (2019) · mAbs

Monoclonal and Polyclonal Antibodies Researchvaccines and immunoinformatics approaches

Cited by 29

Robustly interrogating machine learning-based scoring functions: what are they learning?

Durant, G., Boyles, F., Birchall, K., Marsden, B., & Deane, C. M. (2023) · Bioinformatics

Computational Drug Discovery MethodsMachine Learning in Bioinformatics

Cited by 28

Improved computational epitope profiling using structural models identifies a broader diversity of antibodies that bind to the same epitope

Spoendlin, F. C., Abanades, B., Raybould, M. I. J., Wong, W. K., Georges, G., & Deane, C. M. (2023) · Frontiers in Molecular Biosciences

vaccines and immunoinformatics approachesMonoclonal and Polyclonal Antibodies Research

Cited by 26

Computational tools for aiding rational antibody design

Krawczyk, K., Dunbar, J., & Deane, C. M. (2017) · Methods in molecular biology

Monoclonal and Polyclonal Antibodies Researchvaccines and immunoinformatics approaches

Cited by 26

Improved computational epitope profiling using structural models identifies a broader diversity of antibodies that bind the same epitope

Spoendlin, F. C., Abanades, B., Raybould, M. I. J., Wong, W. K., Georges, G., & Deane, C. M. (2023) · Frontiers in Molecular Biosciences

vaccines and immunoinformatics approachesMonoclonal and Polyclonal Antibodies Research

Cited by 26

The therapeutic antibody profiler for computational developability assessment

Raybould, M. I. J., & Deane, C. M. (2022) · Methods in molecular biology

Monoclonal and Polyclonal Antibodies Researchvaccines and immunoinformatics approaches

Cited by 25

T-cell receptor structures and predictive models reveal comparable alpha and beta chain structural diversity despite differing genetic complexity

Quast, N. P., Abanades, B., Guloglu, B., Karuppiah, V., Harper, S., Raybould, M. I. J., & Deane, C. M. (2024) · Communications Biology

vaccines and immunoinformatics approachesProtein Structure and Dynamics

Cited by 22

T-cell receptor structures and predictive models reveal comparable alpha and beta chain structural diversity despite differing genetic complexity

Quast, N. P., Abanades, B., Guloglu, B., Karuppiah, V., Harper, S., Raybould, M. I. J., & Deane, C. M. (2025) · Communications Biology

vaccines and immunoinformatics approachesProtein Structure and Dynamics

Cited by 22

Antibody side chain conformations are position-dependent

Leem, J., Georges, G., Shi, J., & Deane, C. M. (2018) · Proteins Structure Function and Bioinformatics

Protein Structure and DynamicsMonoclonal and Polyclonal Antibodies Research

Cited by 22

Predicting the conformational flexibility of antibody and T cell receptor complementarity-determining regions

Spoendlin, F. C., Fernández-Quintero, M. L., Raghavan, S. S. R., Turner, H. L., Gharpure, A., Loeffler, J. R., Wong, W. K., Bujotzek, A., Georges, G., Ward, A. B., et al. (2025) · Nature Machine Intelligence

Protein Structure and Dynamicsvaccines and immunoinformatics approaches

Cited by 20

Predicting the conformational flexibility of antibody and T-cell receptor CDRs

Spoendlin, F. C., Fernández-Quintero, M. L., Raghavan, S. S. R., Turner, H. L., Gharpure, A., Loeffler, J. R., Wong, W. K., Bujotzek, A., Georges, G., Ward, A. B., et al. (2025) · Nature Machine Intelligence

Protein Structure and Dynamicsvaccines and immunoinformatics approaches

Cited by 20

Quantifying conformational changes in the TCR:pMHC-I binding interface

McMaster, B., Thorpe, C. J., Rossjohn, J., Deane, C. M., & Koohy, H. (2024) · Frontiers in Immunology

vaccines and immunoinformatics approachesT-cell and B-cell Immunology

Cited by 17

Assessing AF2’s ability to predict structural ensembles of proteins

Riccabona, J. R., Spoendlin, F. C., Fischer, A.-L. M., Loeffler, J. R., Quoika, P. K., Jenkins, T. P., Ferguson, J. A., Smorodina, E., Laustsen, A. H., Greiff, V., et al. (2024) · Structure

Protein Structure and DynamicsEnzyme Structure and Function

Cited by 17

Exploring the ability of machine learning-based virtual screening models to identify the functional groups responsible for binding

Hadfield, T. E., Scantlebury, J., & Deane, C. M. (2023) · Journal of Cheminformatics

Computational Drug Discovery MethodsMachine Learning in Materials Science

Cited by 9

Exploring The Ability Of Machine Learning-Based Virtual Screening Models To Identify The Functional Groups Responsible For Binding

Hadfield, T. E., Scantlebury, J., & Deane, C. M. (2023) · Journal of Cheminformatics

Computational Drug Discovery MethodsMachine Learning in Materials Science

Cited by 9

Investigating the ability of deep learning-based structure prediction to extrapolate and/or enrich the set of antibody CDR canonical forms

Greenshields-Watson, A., Abanades, B., & Deane, C. M. (2024) · Frontiers in Immunology

Protein Structure and Dynamicsvaccines and immunoinformatics approaches

Cited by 7

Investigating the ability of deep learning-based structure prediction to extrapolate and/or enrich the set of antibody CDR canonical forms

Greenshields-Watson, A., Abanades, B., & Deane, C. M. (2023) · Frontiers in Immunology

Protein Structure and Dynamicsvaccines and immunoinformatics approaches

Cited by 7

Assessing AF2’s ability to predict structural ensembles of proteins

Riccabona, J. R., Spoendlin, F. C., Fischer, A.-L. M., Loeffler, J. R., Quoika, P. K., Jenkins, T. P., Ferguson, J. A., Smorodina, E., Laustsen, A. H., Greiff, V., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory)

Protein Structure and DynamicsEnzyme Structure and Function

Cited by 2