TCRBuilder2

Machine Learning based TCR Fv modelling

This web application is designed for small-scale structural modelling. If you would like to perform large-scale analyses, please contact: opig@stats.ox.ac.uk

UPDATE August 2024: By default TCRBuilder2 now uses the TCRBuilder2+ weights. Running TCRBuilder2 with the original weights is only possible via the ImmuneBuilder Python API. See intructions on the ImmuneBuilder GitHub repository.

• TCRBuilder2 can be used to produce models of the TCR Fv regions.
• Submit beta and alpha chain sequences to the forms below to generate a model.
• The sequence and final models will be renumbered with ANARCI
• An example of the output produced by TCRBuilder2 can be seen here.

The pre-print describing TCRBuilder2+ can be found here:

Quast, N.P., Abanades, B., Guloglu, B., Karuppiah, V., Harper, S., Raybould, M.I.J., & Deane, C.M. (2024) T-cell receptor structures and predictive models reveal comparable alpha and beta chain structural diversity despite differing genetic complexity bioRxiv, doi: https://doi.org/10.1101/2024.05.20.594940

The paper describing the original TCRBuilder2 can be found here:

Abanades, B., Wong, W.K., Boyles, F., Georges, G., Bujotzek, A. & Deane, C.M. (2023) ImmuneBuilder: Deep-Learning models for predicting the structures of immune proteins Communications biology, 6:575

Beta chain sequence:

load example

Alpha chain sequence:

load example

Job name:

my_tcr_model

Model