Browse State-of-the-Art › Antibody-antigen binding prediction

Antibody-antigen binding prediction

9 papers with code · 4 benchmarks · 3 datasets archive 2025-07-28

Antibody-antigen binding prediction involves using computational or experimental methods to assess how well an antibody interacts with its target antigen. This can be done by analyzing features such as sequence, structure, and physicochemical properties. These predictions aid in designing therapeutic antibodies, vaccines, and diagnostic tests. Validation through experimental assays ensures the accuracy of the predictions and their applicability in biomedical research and development.

The binding site prediction task is used to predict which antibody residues interact with an antigen. A residue is considered part of the paratope’s binding site if any of its heavy atoms (non-hydrogen atoms) is located within 4.5˚A of any antigen-heavy atom.

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

4 leaderboard tables shown for this task, 4 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.

Dataset	Best model (first row in archive order)	Paper	Code	Syntology	Compare
MIPE (7 rows)	ParaSurf	ParaSurf: A Surface-Based Deep Learning Approach for...	code	—	Compare
PECAN (5 rows)	ParaSurf	ParaSurf: A Surface-Based Deep Learning Approach for...	code	—	Compare
Antibody sequences against Sars-Cov-2 and Omicron BA.1 (3 rows)	XBCR-net (ACNN)	Deep learning-based rapid generation of broadly reactive...	code	—	Compare
Paragraph Expanded (2 rows)	ParaSurf	ParaSurf: A Surface-Based Deep Learning Approach for...	code	—	Compare

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

3 datasets whose archive record lists this task, ordered by the archive's paper count.

MIPE PECAN Paragraph Expanded

Subtasks archive 2025-07-28

No subtask under this task in the archive's task tree.

Parent tasks archive 2025-07-28

Binding Site Prediction Protein Function Prediction

Most implemented papers archive 2025-07-28

9 shown of 9 papers with code (10 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

ParaSurf: A Surface-Based Deep Learning Approach for Paratope-Antigen Interaction Prediction

8 Feb 2025 1 repository listed

Additionally, we conducted an extensive analysis using the largest of the three datasets employed, focusing on three key components: (1) a detailed evaluation of paratope prediction for each Complementarity-Determining…
Improving Paratope and Epitope Prediction by Multi-Modal Contrastive Learning and Interaction Informativeness Estimation

31 May 2024 1 repository listed

Additionally, the ablation studies and visualizations demonstrate the superiority of MIPE owing to the better representations acquired through multi-modal contrastive learning and the interaction patterns comprehended…
PeSTo: parameter-free geometric deep learning for accurate prediction of protein binding interfaces

18 Apr 2023 1 repository listed

Proteins are essential molecular building blocks of life, responsible for most biological functions as a result of their specific molecular interactions.
Paragraph—antibody paratope prediction using graph neural networks with minimal feature vectors

12 Oct 2022 1 repository listed

Summary: The development of new vaccines and antibody therapeutics typically takes several years and requires over $1bn in investment.
Deep learning-based rapid generation of broadly reactive antibodies against SARS-CoV-2 and its Omicron variant

27 Sep 2022 1 repository listed

The COVID-19 pandemic has been ongoing for nearly two and half years, and new variants of concern (VOCs) of SARS-CoV-2 continue to emerge, which urges the development of broadly neutralizing antibodies.
A large-scale systematic survey reveals recurring molecular features of public antibody responses to SARS-CoV-2

25 May 2022 1 repository listed

Global research to combat the COVID-19 pandemic has led to the isolation and characterization of thousands of human antibodies to the SARS-CoV-2 spike protein, providing an unprecedented opportunity to study the…
Learning context-aware structural representations to predict antigen and antibody binding interfaces

22 Apr 2020 1 repository listed

To increase prediction accuracy as well as to provide a means to gain new biological insights into these interactions, we have developed a unified deep learning-based framework to predict binding interfaces on both…
Antibody interface prediction with 3D Zernike descriptors and SVM

5 Oct 2018 1 repository listed

Roto-translationally invariant descriptors are computed from circular patches of the antibody surface enriched with a chosen subset of physico-chemical properties from the AAindex1 amino acid index set, and are used as…
Parapred: antibody paratope prediction using convolutional and recurrent neural networks

16 Apr 2018 1 repository listed

Motivation: Antibodies play essential roles in the immune system of vertebrates and are powerful tools in research and diagnostics.

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