Machine Learning based antibody Fv modelling
This web application is designed for small-scale structural modelling. If you would like to perform large-scale analyses, please contact: firstname.lastname@example.org
- ABodyBuilder-ML can be used to produce models of the antibody Fv regions.
- Submit heavy and light chain sequences to the forms below and ABodyBuilder-ML will:
- Number the sequences with ANARCI
- Choose the best templates for the VH and VL domains separately using SAbDab
- Predict the VH-VL orientation using ABangle and place the template domains in the predicted pose
- Model the CDR loops with ABlooper(*)
- Generate side chains with PEARS
- Renumber the final models with ANARCI
- Annotate the estimated loop model quality, recognise potential sequence liabilities and visualise different regions of the structure.
- An example of the output produced by ABodyBuilder-ML can be seen here.
(*)NB: ABodyBuilder-ML uses the deep-learning approach to CDR loop modelling of ABlooper, replacing template-based modelling previously done with FREAD and Sphinx by the former ABodyBuilder pipeline. For a full description of the original ABodyBuilder pipeline, see this publication
To cite ABlooper, please refer to Abanades B, et al. ABlooper: fast accurate antibody CDR loop structure prediction with accuracy estimation, Bioinformatics (2022)