Matt Raybould

Postdoctoral Researcher in Immunoinformatics

Welcome to my academic website! I'm currently a Postdoctoral Researcher at the University of Oxford, working in the Oxford Protein Informatics Group (OPIG).

Research Interests: I am fascinated by the adaptive immune system and am driven to understand the efficiency of the naive/baseline antibody repertoire, whose relatively sparse diversity can instigate immune responses against almost any antigen. We aim to harness the growing body of antibody repertoire sequencing data to elucidate core principles governing B-cell selection and response across populations. Our belief in OPIG is that combining genetic information (clonality), amino acid chemistry, and structural information (binding site topography) will yield exciting discoveries that can contribute to the fields of immunodiagnostics, immunosenescence, immunodeficiency/autoimmunity, allergy, and nature-inspired immunotherapeutic/vaccine design.

Academic Positions


Student Research Experience

Therapeutic Antibody Discovery
(DPhil Project, 2017-2020)

Thesis title: "Structure-Aware Tools for the Development of Therapeutic Antibodies from Natural Immunoglobulins". Supervised by Prof. Charlotte Deane in the Department of Statistics, in collaboration with GSK, Roche, AstraZeneca (then MedImmune) and UCB.

Antibody Informatics
(Rotation Project, 2017)

Supervised by Prof. Charlotte Deane in the Department of Statistics, in collaboration with GSK, Roche, MedImmune and UCB.

Molecular Dynamics of the hERG Ion Channel
(Rotation Project, 2017)

Jointly supervised by Dr. Phillip Stansfeld and Prof. Mark Sansom in the Department of Biochemistry, in collaboration with UCB.

Mechanistic Insights into the Horner-Wadsworth-Emmons and Still-Gennari Olefinations
(Master's Project, 2015-2016)

A DFT computational study into the intra- and inter-molecular interactions governing diastereoselectivity in these two closely related organic systems. Master's project conducted in Prof. Robert Paton's group.

Designing a Synthesis of the [18F]-Labelled SSAO/VAP-1 Inhibitor, PXS-4681A
(Summer Project, 2014)

Working towards a new [18F]-labelled synthesis of a potential anti-inflammatory drug desired by oncology departments. Vacation project conducted in Prof. Véronique Gouverneur's group.


You can view my publications on Google Scholar or ResearchGate.

Alternatively, below is an updated list of preprints (papers currently in peer review with a journal, but not yet accepted), peer-reviewed papers, invited articles, and book chapters:


  • Fischer, K.; Lulla, A. and So, T. and Pereyra-Gerber, P. and Raybould, M.I.J.; Kohler, T.N.; Kaminski, T.S.; Yam-Puc, J.C.; Hughes, R.; Leiss-Maier, F.; Brear, P.; Matheson, N.J.; Deane, Charlotte M.; Hyvonen, M.; Thaventhiran, J.; Hollfelder, F. (2023) Microfluidics-enabled fluorescence-activated cell sorting of single pathogen-specific antibody secreting cells for the rapid discovery of monoclonal antibodies. bioRxiv. doi: 10.1101/2023.01.10.523494.

    [Link to Preprint]

Peer-Reviewed Papers

  1. Raybould, M.I.J.; Nissley, D.A.; Kumar, S.; Deane, C.M. (2023) Computationally profiling peptide:MHC recognition by T-cell receptors and T-cell receptor-mimetic antibodies. Front. Immunol. 13:1080596.

    [Link to Paper; Datasets]

  2. Schneider, C.; Raybould, M.I.J.; Deane, C.M. (2022) SAbDab in the Age of Biotherapeutics: Updates including SAbDab-nano, the Nanobody Structure Tracker. Nucleic Acids Res. 50(D1):D1368-D1372.

    [Link to Paper; SAbDab-Nano]

  3. Robinson, S.A. and Raybould, M.I.J.; Schneider, C.; Wong, W.K.; Marks, C.; Deane, C.M. (2021) Epitope Profiling using Computational Structural Modelling Demonstrated on Coronavirus-Binding Antibodies. PLoS Comput. Biol. 17(12):e1009675.

    [Link to Paper; Code]

  4. Raybould, M.I.J.; Rees, A.R.; Deane, C.M. (2021) Current Strategies for Detecting Functional Convergence across B-cell Receptor Repertoires. MAbs. 13(1):1996732.

    [Link to Review]

  5. Raybould, M.I.J.; Marks, C.; Kovaltsuk, A.; Lewis, A.P.; Shi, J. & Deane, C.M. (2021) Public Baseline and Shared Response Structures Support the Theory of Antibody Repertoire Functional Commonality. PLoS Comput. Biol. 17(3):e1008781.

    [Links to Paper; Datasets]

  6. Raybould, M.I.J.; Kovaltsuk, A.; Marks, C. & Deane, C.M. (2021) CoV-AbDab: the Coronavirus Antibody Database. Bioinformatics. 37(5):734-735.

    [Links to Paper; Database]

  7. Galson, J.D.; Schaetzle, S.; Bashford-Rogers, R.J.M.; Raybould, M.I.J.; Kovaltsuk, A.; Kilpatrick, G.J.; Minter, R.; Finch, D.K.; Dias, J.; James, L.; Thomas, G.; Lee, W.-Y.J.; Betley, J.; Cavlan, O.; Leech, A.; Deane, C.M.; Seoane, J.; Caldas, C.; Pennington, D.; Pfeffer, P.; Osbourn, J. (2020) Deep Sequencing of B cell Receptor Repertoires from COVID-19 Patients Reveals Strong Convergent Immune Signatures. Front. Immunol. 11:605170.

    [Link to Paper]

  8. Kovaltsuk, A.; Raybould, M.I.J.; Wong, W.K.; Marks, C.; Kelm, S.; Snowden, J.; Trück, J. & Deane, C.M. (2020) Structural Diversity of B-cell Receptor Repertoires along the B-cell Differentiation Axis in Humans and Mice. PLoS Comp. Bio. doi: 10.1371/journal.pcbi.1007636.

    [Link to Paper; Code]

  9. Raybould, M.I.J.; Marks, C.; Lewis, A.P.; Shi, J.; Bujotzek, A.; Taddese, B. & Deane, C.M. (2020) Thera-SAbDab: the Therapeutic Structural Antibody Database. Nucleic Acids Res. 48(1):D383-D388.

    [Links to Paper; Database]

  10. Krawczyk, K.; Raybould, M.I.J.; Kovaltsuk, A.; Deane, C.M. (2019) Looking for Therapeutic Antibodies in Next-Generation Sequencing Repositories. MAbs 11(7):1197-1205.

    [Link to Paper]

  11. Raybould, M.I.J. and Wong, W.K.; Deane, C.M. (2019) Antibody-Antigen Complex Modelling in the Era of Immunoglobulin Repertoire Sequencing. Mol. Syst. Des. Eng. 4(4):679-688.

    [Link to Review]

  12. Raybould, M.I.J.; Marks, C.; Krawczyk, K.; Taddese, B.; Nowak, J.; Lewis, A.P.; Bujotzek, A.; Shi, J.; Deane, C.M. (2019) Five Computational Developability Guidelines for Therapeutic Antibody Profiling. Proc. Natl. Acad. Sci. USA. 116(10):4025-4030.

    [Links to Paper; Web Application]

Invited Articles

  1. Raybould, M.I.J.; Deane C.M. (2019) Structural Information to Aid in silico Therapeutic Antibody Design from Next-Generation Sequencing Repertoires. Am. Pharm. Rev. 22(5):30-35.

    [Link to Article]

Book Chapters

  1. Raybould, M.I.J.; Deane C.M. (2022) The Therapeutic Antibody Profiler for Computational Developability Assessment. Chapter in: Therapeutic Antibodies (Methods in Molecular Biology). vol 2313, pp. 115-125.

    [Link to Chapter]





  • December: NeurIPS, Learning Meaningful Representations of Life track (Virtual). Invited talk.
    "Applications of machine learning for antibody drug discovery"
  • November: European Antibody Congress (Basel, Switzerland). Invited talk.
    "Epitope profiling of coronavirus-binding antibodies using computational structural modelling"
  • July: RSC Antibody Workshop, CICAG (Virtual). Community engagement talk.
    "The OPIG Antibody Modeling Tools"
  • April: Meeting Minds Global (Virtual). Outreach talk.
    "How a database of coronavirus-binding antibodies (CoV-AbDab) can help us control SARS-CoV-2"
  • April: CASSS Higher Order Structure (Virtual). Invited talk.
    "Five computational developability guidelines for therapeutic antibody profiling"


  • November: BioDataScience101 (Virtual). Invited talk.
    "Antibody sequence analysis to better understand SARS-CoV-2 infection"
  • November: European Antibody Congress (Virtual). Invited talk.
    "Public Baseline and Shared Response Structures and their Application for Screening Library Design"
  • July: Intelligent Systems in Molecular Biology (Virtual). Accepted talks.
    "CoV-AbDab: the Coronavirus Antibody Database"
    "Evidence for Antibody Functional Convergence through Public Baseline and Shared Response Structures"


  • July: Intelligent Systems in Molecular Biology (Chicago IL, USA). Poster.
    "The Therapeutic Antibody Profiler; Five Computational Developability Guidelines"


Since 2017 I have tutored the first year Merton biochemists in organic chemistry/mechanistic biochemistry and have also mentored students through the first (Prelims) and third (Finals, Part IB) year chemistry courses. Throughout the year I also run graduate-level modules at the Doctoral Training Centre, in topics such as organic chemistry, programming, cells and systems, structural biology and drug discovery. I am always eager for new teaching opportunities, so please contact me if you have a relevant opening.



24-29 St Giles'
Department of Statistics
University of Oxford