AbFlex: Predicting the conformational flexibility of antibody CDRs

Fabian C Spoendlin, Wing Ki Wong, Guy Georges, Alexander Bujotzek, Charlotte Deane

Keywords: antibodies, protein structure prediction, dataset, drug discovery, geometric deep learning

TL;DR: A dataset and method to predict the conformational flexibility of antibody CDRs

Abstract:

Proteins are highly flexible macromolecules and the ability to adapt their shape is fundamental to many functional properties. While a single, 'static' protein structure can be predicted at high accuracy, current methods are severely limited at predicting structural flexibility. A major factor limiting such predictions is the scarcity of suitable training data. Here, we focus on the functionally important antibody CDRs and related loop motifs. We implement a strategy to create a large dataset of evidence for conformational flexibility and develop AbFlex, a method able to predict CDR flexibility with high accuracy.

Submission Number: 9