1 Matt Raybould | DPhil in Structural Immunoinformatics, Oxford University

Matt Raybould

DPhil Student in Immunoinformatics

Welcome to my academic website! I'm a researcher at the University of Oxford, working in the Oxford Protein Informatics Group (OPIG). After submitting my DPhil thesis in September 2020, I shall be staying on as a Post-Doc (through the EPRSC Doctoral Prize Scheme) until April 2021.

Research Interests: I am fascinated by the adaptive immune system, and especially 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 and elucidate core principles governing B-cell selection and response across populations. Our belief in OPIG is that coupling genetic information (clonality) with structural information (binding site geometry) will yield novel, exciting insights that can contribute to the fields of immunodiagnostics, immunosenescence, immunodeficiency/autoimmunity, allergy, and nature-inspired immunotherapeutic/vaccine design.

Academia-Industry Collaborations: We work extensively with industrial partners (including GSK, Roche, AstraZeneca, and UCB) giving us access to high-quality bespoke sequencing data, the ability to perform crucial experimental validations of our algorithms, and in return the opportunity to maximise knowledge transfer and deliver improved medicines for patients. If you are interested in setting up a collaboration, please get in touch!

Current Research (DPhil): The global market for therapeutic monoclonal antibodies (mAbs), targeting a remarkably wide range of diseases, is exploding, with ~10 new mAbs approved each year and a positive outlook for the years ahead. There is high demand for a reliable in silico protocol that can aid in designing an efficacious antibody lead against any specific protein epitope. I will aim to improve our ability to do this during my DPhil, by first looking at already-approved antibody therapeutics and deriving key design principles from them. This will lead into developing a computational pipeline that generates, from a diverse human-based starting library, a subset of specific, non-immunogenic, antigen-binders.

Academic Positions

University Education

Research Experience

I conducted research in the following groups during my Master's and DPhil degrees:

DPhil [3 Years]
- Antibody Informatics

Supervised by Prof. Charlotte Deane (Oxford Protein Informatics Group, Department of Statistics), in collaboration with GSK, Roche, MedImmune and UCB.

DPhil Rotation [3 Months]
- Molecular Dynamics of the hERG Ion Channel

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

DPhil Rotation [3 Months]
- Antibody Informatics

Supervised by Prof. Charlotte Deane (Oxford Protein Informatics Group, Department of Statistics), in collaboration with GSK, Roche, MedImmune and UCB.

Master's [9 Months]
- Mechanistic Insights into the Horner-Wadsworth-Emmons and Still-Gennari Olefinations

A Density Functional Theory (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.

Work Experience [2 Months]
- Designing a Synthesis of the [18F]-Labelled SSAO/VAP-1 Inhibitor, PXS-4681A

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.


All written research outputs, divided into preprints (papers currently in peer review with a journal, but not yet accepted), peer-reviewed papers, invited articles, and book chapters.


  • 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. bioRxiv. doi: 10.1101/2020.05.20.106294.

    [Link to Preprint]

  • Raybould, M.I.J.; Marks, C.; Kovaltsuk, A.; Lewis, A.P.; Shi, J. & Deane, C.M. (2020) Evidence of Antibody Repertoire Functional Convergence through Public Baseline and Shared Response Structures. bioRxiv. doi: 10.1101/2020.03.17.993444.

    [Links to Preprint; Datasets]

Peer-Reviewed Papers

  1. Raybould, M.I.J.; Kovaltsuk, A.; Marks, C. & Deane, C.M. (2020) CoV-AbDab: the Coronavirus Antibody Database. Bioinformatics doi: 10.1093/bioinformatics/btaa739

    [Links to Paper; Database]

  2. 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]

  3. 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]

  4. 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]

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

    [Link to Paper]

  6. 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]

Joint authorship

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):28-33.

    [Link to Article]

Book Chapters

  1. Raybould, M.I.J. & Deane, C.M. (2020) The Therapeutic Antibody Profiler for Computational Developability Assessment in Houen, G. (ed.) Methods in Molecular Biology: Therapeutic Antibodies. Humana Press.

    [Awaiting Publication]



  • European Antibody Congress
    Basel, Switzerland
    2nd-4th November 2020

    Invited Talk: Public Baseline and Response Antibody Structures and their Application to Screening Library Design [Agenda]


  • Intelligent Systems for Molecular Biology (ISMB) 2020
    Virtual Conference
    13th-16th July 2020

    Talk: CoV-AbDab: the Coronavirus Antibody Database [COVID-19]
    Talk: Evidence of Antibody Repertoire Functional Convergence through Public Baseline and Response Structures [3DSIG]

  • CASSS Higher Order Structure
    Gaithersburg MD, USA
    20th-22nd April 2020
    Invited Talk: "Five computational developability guidelines for therapeutic antibody profiling" (cancelled due to COVID-19)

  • Intelligent Systems for Molecular Biology (ISMB)
    Chicago IL, USA
    6th-10th July 2018

    Poster Presentation: "The Therapeutic Antibody Profiler: Five Computational Developability Guidelines".


Since October 2017, I have tutored the first year Merton biochemists in organic chemistry. I have also mentored students through the first (Prelims) and third (Finals, Part IB) year chemistry courses at Merton. I am always eager for new teaching opportunities, so please contact me if you require a tutor in chemistry. All tutorial problem sets are available via Canvas. Until further notice, I will be using videoconferencing software for all tutorials.


Email and LinkedIn are the best ways to contact me. Feel free to ask me about anything on the website!


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