A compact vocabulary of paratope-epitope interactions enables predictability of antibody-antigen binding
Loading...
Authors
Akbar, Rahmad
Pavlovic, Milena
Snapkov, Igor
Slabodkin, Andrei
Scheffer, Lonneke
Haff, Ingrid Hobaed
Tryslew Haug, Dag Trygve
Lund-Johanson, Fridtjof
Safonova, Yana
Author (Corporation)
Publication date
16.03.2021
Typ of student thesis
Course of study
Type
01A - Journal article
Editors
Editor (Corporation)
Supervisor
Parent work
Cell Reports
Special issue
DOI of the original publication
Link
Series
Series number
Volume
34
Issue / Number
11
Pages / Duration
1-21
Patent number
Publisher / Publishing institution
Cell Press
Place of publication / Event location
Cambridge
Edition
Version
Programming language
Assignee
Practice partner / Client
Abstract
Antibody-antigen binding relies on the specific interaction of amino acids at the paratope-epitope interface. The predictability of antibody-antigen binding is a prerequisite for de novo antibody and (neo-)epitope design. A fundamental premise for the predictability of antibody-antigen binding is the existence of paratope-epitope interaction motifs that are universally shared among antibody-antigen structures. In a dataset of non-redundant antibody-antigen structures, we identify structural interaction motifs, which together compose a commonly shared structure-based vocabulary of paratope-epitope interactions. We show that this vocabulary enables the machine learnability of antibody-antigen binding on the paratope-epitope level using generative machine learning. The vocabulary (1) is compact, less than 104 motifs; (2) distinct from non-immune protein-protein interactions; and (3) mediates specific oligo- and polyreactive interactions between paratope-epitope pairs. Our work leverages combined structure- and sequence-based learning to demonstrate that machine-learning-driven predictive paratope and epitope engineering is feasible.
Keywords
antibody, antigen, paratope, epitope, structure, prediction, deep learning, machine learning
Subject (DDC)
Event
Exhibition start date
Exhibition end date
Conference start date
Conference end date
Date of the last check
ISBN
ISSN
2639-1856
2211-1247
2211-1247
Language
English
Created during FHNW affiliation
Yes
Strategic action fields FHNW
Publication status
Published
Review
Peer review of the complete publication
Open access category
Gold
License
Citation
Miho, E., Akbar, R., Pavlovic, M., Snapkov, I., Slabodkin, A., Scheffer, L., Haff, I. H., Tryslew Haug, D. T., Lund-Johanson, F., Safonova, Y., Greiff, V., Robert, P., Jeliazkov, J., Weber, C., & Sandve, G. (2021). A compact vocabulary of paratope-epitope interactions enables predictability of antibody-antigen binding. Cell Reports, 34(11), 1–21. https://doi.org/10.1016/j.celrep.2021.108856