ANTIPASTI: interpretable prediction of antibody binding affinity exploiting Normal Modes and Deep Learning. Michalewicz et al.
Published: 16 October 2024| Version 1 | DOI: 10.17632/j4rt98xpy7.1
Contributors:
Kevin Michalewicz, , Description
PDB files (in Chothia numbering) used to train and evaluate ANTIPASTI.
Files
Steps to reproduce
1. Go to the SAbDab database: https://opig.stats.ox.ac.uk/webapps/sabdab-sabpred/sabdab 2. Go to 'Structure Search'. 3. Click on 'Search structures by attribute'. 4. Change 'Antigen type' field to 'Any (all bound structures)'. 5. Change 'Has affinity value' field to 'True'. 6. Download the files (.zip) and consider those PDBs in the 'chothia' folder. Note: we conducted this process on 23 June 2023, meaning that new files may appear in the future.
Institutions
Imperial College London
Categories
Antibody Design
Funding
Engineering and Physical Sciences Research Council
EP/N014529/1
President's Scholarship at Imperial College London