Fabian Spoendlin

GitHub - oxpig/ANARCII: A language model suite for numbering antigen receptor sequences. A language model suite for numbering antigen receptor sequences. - oxpig/ANARCII

We have released the successor to ANARCI - ANARCII - a suite of Seq2Seq language models trained to number antibody (or TCR) sequences!

Read the paper: biorxiv.org/content/10.1...

Play with the webtool: opig.stats.ox.ac.uk/webapps/sabd...

Documentation and codebase: github.com/oxpig/ANARCII

Predicting the conformational flexibility of antibody and T-cell receptor CDRs Many proteins are highly flexible and their ability to adapt their shape can be fundamental to their functional properties. We can now computationally predict a single, static protein structure with h...

Check out the preprint at: www.biorxiv.org/content/10.1...

Thanks to my co-authors Monica Fernández-Quintero, Sai Raghavan, Hannah Turner, Anant Gharpure, Johannes Loeffler, Catherine Wong, Guy Georges, Alexander Bujotzek, Andrew Ward, and Charlotte Deane

2. We introduce ITsFlexible, a tool that predicts CDR3 flexibility with high accuracy evaluated on crystal structure and MD data. Furthermore, we experimentally validate predictions of three challenging case studies using cryo-EM providing fruther evidence for ITsFlexible’s predictive accuracy.

In our latest work, focusing on antibody and TCR CDRs, we take a step towards addressing this challenge:

1. We release ALL-conformations, a large dataset of 1.2 million structures capturing all experimentally observed conformational states of CDR3 loops and related loop motifs.

Predicting protein conformational flexibility remains a major challenge in structural biology. While we can now accurately model static protein structures, understanding their dynamics is still difficult, largely due to a lack of suitable training data.