Related papers: Conformation-Aware Structure Prediction of Antigen-Recognizing Immune Proteins

Conformation-Aware Structure Prediction of Antigen-Recognizing Immune Proteins

URL: http://arxiv.org/abs/2507.09054v1
Date: Fri, 11 Jul 2025 22:09:03 GMT
Title: Conformation-Aware Structure Prediction of Antigen-Recognizing Immune Proteins
Authors: Frédéric A. Dreyer, Jan Ludwiczak, Karolis Martinkus, Brennan Abanades, Robert G. Alberstein, Pan Kessel, Pranav Rao, Jae Hyeon Lee, Richard Bonneau, Andrew M. Watkins, Franziska Seeger,
Abstract summary: We introduce Ibex, a pan-immunoglobulin structure prediction model.<n>It achieves state-of-the-art accuracy in modeling the variable domains of antibodies, nanobodies, and T-cell receptors.
Score: 4.747546562792329
License: http://creativecommons.org/licenses/by/4.0/
Abstract: We introduce Ibex, a pan-immunoglobulin structure prediction model that achieves state-of-the-art accuracy in modeling the variable domains of antibodies, nanobodies, and T-cell receptors. Unlike previous approaches, Ibex explicitly distinguishes between bound and unbound protein conformations by training on labeled apo and holo structural pairs, enabling accurate prediction of both states at inference time. Using a comprehensive private dataset of high-resolution antibody structures, we demonstrate superior out-of-distribution performance compared to existing specialized and general protein structure prediction tools. Ibex combines the accuracy of cutting-edge models with significantly reduced computational requirements, providing a robust foundation for accelerating large molecule design and therapeutic development.

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