M. I. J. Raybould

This paper presents a microfluidics-based method to rapidly discover monoclonal antibodies from antigen-specific antibody secreting cells, achieving high-affinity and neutralizing antibodies against SARS-CoV-2.

The paper profiles T-cell receptor-mimetic antibodies (TCRms) against pMHC complexes to quantify their TCR-likeness and identify molecular differences in antigen recognition.

This paper introduces a computational method to profile epitopes of coronavirus-binding antibodies using structural modeling, revealing that sequence-dissimilar antibodies can bind the same epitope.

The paper analyzes B cell receptor repertoires from COVID-19 patients to identify convergent immune signatures associated with disease outcome.

The paper introduces CoV-AbDab, a database of antibodies against SARS-CoV-2 and related betacoronaviruses, providing metadata and analysis tools for research applications.

The paper investigates functional convergence in human antibody repertoires by analyzing structural commonality in baseline and response antibodies, finding high structural similarity across individuals.

The paper structurally characterizes B-cell receptor paratopes in humans and mice, showing structural differences across B-cell differentiation stages and conservation in naive repertoires.

Thera-SAbDab tracks therapeutic antibodies and nanobodies, linking them to structural data and metadata for sequence and target analysis.