AbEpiTope - 1.0

Antibody-antigen interface scoring and antibody target prediction

Submission

1. Upload a single structure file (.pdb/.cif) or a .zip file.

A .zip file may contain a maximum of 120 structure files. Each structure must contain an antibody-antigen complex, that includes an antibody chain (light, heavy or both) along with any number of antigen chains. Structure files where this is not detected will not produce a score.

Example Files

We provide five example .zip files containing modeled structures of antibodies targeting antigens from a range of diseases: SARS (PDB: 7VYR), HIV (PDB: 3LEV), Bacteria, (Meningococcal, PDB: 5O14), Cancer, (PD-1 receptor, PDB: 7E9B), and Autoimmune (grass pollen, PDB: 5OTJ). Each file includes 30 structures in PDB format generated using AlphaFold-2.3. Additionally, a sixth example .zip file contains modeled structures for four different antibodies and a HIV antigen (PDB: 3LHP). Each antibody and the HIV antigen was modeled separately, not simultaneously. One of these antibodies has been experimentally confirmed to target the HIV antigen, while the others are known to target different antigens; angiopetin 2 (PDB: 4ZFG), arrestin-2 (PDB: 7DFA), interleukin-1 beta (PDB: 7Z4T). The .zip file includes a total of 120 individually modeled structure files, all in PDB format.

SARS HIV Bacteria Cancer Autoimmune Antibody Target Prediction

2. Set antibody-antigen interface distance (default: 4Å):

Instructions

Input

1. Users can upload a single structure file (pdb/cif) or a zip file containing pdb/cif files.

Each structure file must include a light and heavy chain or a single-chain variable fragment (scFv), along with one or more antigen chains. Due to computational resource limits on the web server, we restrict uploads to a maximum of 30 files per submission. For larger batches, we recommend using the local installation (see Versions or Download)
Note: Scores will not be produced for antibody-antigen structures where this is not detected.

2. Users can set a custom Angstrom (Å) distance for defining antibody-antigen interfaces.

The default is 4 Å. The antibody-antigen interface is made up of epitoep and paratope residues. Epitope residues are any residue with at least one heavy atom (main-chain or side-chain) at a distance of 4 Å or less to any light or heavy chain. The corresponding interacting residues on the light or heavy chain are the paratope residues.
Note: Scores will not be produced for antibody-antigen structures if no epitope and paratope residues are detected at the set Å distance.

Output

See Output format

Output format

The tool generates two CSV files.

1. The first, output.csv, lists each input structure file along with its AbEpiScore-1.0 and AbEpiTarget-1.0 scores.

2. The second, interface.csv, lists each input structure file along with epitope and paratope residues used to compute these scores.

Note: If a row contains "None" in any column, it indicates that no antibody was identified, or no AbAg interface was detected within the specified Å distance.

3. The third, abag_sequence_data.fasta, is a fasta formmatted file containing the sequences in each each antibody-antigen complex. The header >FILENAME_CHAINNAMES and the sequences of each abag are joined with ':'.

4. The fourth, failed_files.csv, is an error file that only appears if an error occurs for one or more of the files in the zip file upload. Each row contains filename and reason for the error.

Abstract

AbEpiTope-1.0: Antibody-specific B-cell epitope and antibody target prediction by use of AlphaFold and inverse folding

Authors: Joakim Clifford, Eve Richardson, Bjoern Peters, Morten Nielsen

Publication:

Abstract

B-cell epitope prediction tools are crucial for the design of vaccines and disease diagnostics. However, predicting which antigens a specific antibody will bind to, and their exact binding sites (epitopes), remains challenging. Here, we present AbEpiTope-1.0, a computational tool for antibody-specific B-cell epitope prediction, utilising AlphaFold-2.3 for structural modelling and inverse folding for the machine learning models. AbEpiTope-1.0 outperforms AlphaFold’s confidence ranking in predicting the accuracy of modelled antibody-antigen interfaces. Most importantly, we show that the predicted accuracy is sensitive to antibody input, offering a reliable metric for selecting antibodies most likely to bind a given antigen. Furthermore, a variant of our model trained specifically for this task shows a significant performance improvement. The tool can evaluate hundreds of antibody-antigen structures in minutes, providing researchers with a valuable resource for antibody screening and B-cell epitope prediction. AbEpiTope-1.0 is freely available as a web server and standalone package at https://services.healthtech.dtu.dk/services/AbEpiTope-1.0.

GitHub Please visit our GitHub repository for a local installment of current version

The code and data can be used freely by academic groups for non-commercial purposes.
If you plan to use these tools for any for-profit application, you are required to obtain a separate license (contact Morten Nielsen, morni@dtu.dk)

This service offers no downloadable software

See a list of available software

GitHub Please visit our GitHub repository for a local installment of current version

GETTING HELP

If you need help regarding technical issues (e.g. errors or missing results) contact Technical Support. Please include the name of the service and version (e.g. NetPhos-4.0) and the options you have selected. If the error occurs after the job has started running, please include the JOB ID (the long code that you see while the job is running).

If you have scientific questions (e.g. how the method works or how to interpret results), contact Correspondence.

Correspondence: Technical Support: