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About CovEpiAb

CovEpiAb is a comprehensive database and analysis resource of human coronavirus (HCoVs) immune epitopes and antibodies. CovEpiAb contains information on over 60,000 experimentally validated epitopes and over 12,000 antibodies for HCoVs and SARS-CoV-2 variants. The database is unique in:

(1) classifying and annotating cross-reactive epitopes from different viruses and variants,

(2) providing molecular and experimental interaction profiles of antibodies, including structure-based binding sites and around 70,000 data on binding affinity and neutralizing activity,

(3) providing virological characteristics of current and past circulating SARS-CoV-2 variants and in vitro activity of various therapeutics,

(4) offering site-level annotations of key functional features, including immune epitope, antibody binding, SARS-CoV-2 mutations, receptor binding, mAb resistance and conservation.

(5) offering an integrated online pipeline for B-cell and T-cell epitope prediction, named COVEP.

Overall, CovEpiAb provides an important resource for SARS-CoV-2-related research and facilitates the development of broad-spectrum effective vaccines and neutralizing antibodies against HCoVs.

About COVEP

Integrated epitope prediction tools

COVEP is an integration of existing recognized epitope prediction tools and provides a user-friendly application and web interface.

NetMHCpan4.0, MHCflurry2.0, and DeepHLApan were employed for MHC class I T-cell epitope prediction, and MixMHC2pred and NetMHCIIpan were utilized for MHC class II epitope prediction. These tools have been validated for their accuracy in the literature and are widely used by researchers.

Seven IEDB built-in tools were used for B-cell epitope prediction, including BepiPred, BepiPred-2.0, Chou, and Fasman beta turn prediction, Emini surface accessibility scale, Karplus and Schulz flexibility scale, Kolaskar and Tongaonkar antigenicity scale, and Parker hydrophilicity prediction. They are also commonly used and recognized tools. The prediction accuracy of these tools has been validated and compared in their own papers. Users can see their papers for details.

Type Tools Length Paper✝ Citations* Webserver
B Bepipred position score Improved method for predicting linear B-cell epitopes 497 link
Bepipred-2.0 position score BepiPred-2.0: improving sequence-based B-cell epitope prediction using conformational epitopes 543 link
Chou-Fasman position score Prediction of the secondary structure of proteins from their amino acid sequence 1088 link
Emini position score Induction of hepatitis A virus-neutralizing antibody by a virus-specific synthetic peptide 411 link
Karplus-Schulz position score Prediction of chain flexibility in proteins - a tool for the selection of peptide antigens 990 link
Kolaskar-Tongaonkar position score A semi-empirical method for prediction of antigenic determinants on protein antigens 496 link
Parker position score New hydrophilicity scale derived from high-performance liquid chromatography peptide retention data: correlation of predicted surface residues with antigenicity and X-ray-derived accessible sites 374 link
MHC class I NetMHCpan-4.1 8-14mer NetMHCpan-4.0: Improved Peptide-MHC Class I Interaction Predictions Integrating Eluted Ligand and Peptide Binding Affinity Data 620 link
MHCflurry2.0 8-14mer MHCflurry 2.0: Improved Pan-Allele Prediction of MHC Class I-Presented Peptides by Incorporating Antigen Processing 79 + 96 (MHCflurry) link
DeepHLApan 8-14mer DeepHLApan: A Deep Learning Approach for Neoantigen Prediction Considering Both HLA-Peptide Binding and Immunogenicity 47 link
MHC class II NetMHCIIpan-4.0 12-25mer Robust prediction of HLA class II epitopes by deep motif deconvolution of immunopeptidomes 117 link
MixMHC2pred 12-25mer Improved Prediction of MHC II Antigen Presentation through Integration and Motif Deconvolution of Mass Spectrometry MHC Eluted Ligand Data 150 link

✝ The prediction accuracy of these tools has been validated and compared in their own papers.
* Citations as of February 1, 2024.

Usage of COVEP

COVEP offers a comprehensive set of resources for users:

1. Online Web Server: Access COVEP's functionality through a user-friendly web interface. Please refer to the tutorial for details on how to use COVEP's webserver.

2. Docker Image: Obtain the Docker image for seamless deployment and usage.

3. Source Code: Explore and download the source code directly from the project's GitHub repository. See the README file for more detailed information.

Downloads

Validated B- and T-cell epitopes against HCoVs
Experimental Validated B cell epitopes against HCoVs and their biological context. Click to save
Experimental Validated T cell epitopes against HCoVs and their biological context. Click to save
Bind and Neutralizing antibodies against HCoVs
Experimental Validated antibodies against HCoVs and their biological context. Click to save
SARS-CoV-2 variants and therapeutic data
SARS-CoV-2 variants Click to save
Virological features of SARS-CoV-2 variants Click to save
Advanced therapeutic data Click to save
Predicted epitopes for HCoVs
Predicted B cell epitopes against HCoVs. Click to save
Predicted CD8+ T cell epitopes against HCoVs. Click to save
Predicted CD4+ T cell epitopes against HCoVs. Click to save
Conservation and consensus squence of HCoVs homologous protein
Site conservation of HCoVs homologous protein. Click to save
Consensus sequence of HCoVs homologous protein. Click to save

Cite Us

Zhang X, Wu J, Luo Y, et al. CovEpiAb: a comprehensive database and analysis resource for immune epitopes and antibodies of human coronaviruses. Brief Bioinform. 2024;25(3):bbae183. https://doi.org/10.1093/bib/bbae183

Contact Us

Dr. Zhan Zhou, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China 310058 zhanzhou@zju.edu.cn