CovEpiAb: a comprehensive database and analysis resource for immune epitopes and antibodies of human coronaviruses.
Xue ZhangJingCheng WuYuanyuan LuoYilin WangYujie WuXiaobin XuYufang ZhangRuiying KongYing ChiYisheng SunShuqing ChenQiaojun HeJian ZhangZhan ZhouPublished in: Briefings in bioinformatics (2024)
Coronaviruses have threatened humans repeatedly, especially COVID-19 caused by SARS-CoV-2, which has posed a substantial threat to global public health. SARS-CoV-2 continuously evolves through random mutation, resulting in a significant decrease in the efficacy of existing vaccines and neutralizing antibody drugs. It is critical to assess immune escape caused by viral mutations and develop broad-spectrum vaccines and neutralizing antibodies targeting conserved epitopes. Thus, we constructed CovEpiAb, 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; and (4) offering site-level annotations of key functional features, including antibody binding, immunological epitopes, SARS-CoV-2 mutations and conservation across HCoVs. In addition, we developed an integrated pipeline for epitope prediction named COVEP, which is available from the webpage of CovEpiAb. CovEpiAb is freely accessible at https://pgx.zju.edu.cn/covepiab/.
Keyphrases
- sars cov
- respiratory syndrome coronavirus
- public health
- endothelial cells
- copy number
- induced pluripotent stem cells
- dengue virus
- adverse drug
- gene expression
- healthcare
- squamous cell carcinoma
- small molecule
- hiv infected
- electronic health record
- wastewater treatment
- coronavirus disease
- cancer therapy
- machine learning
- big data
- social media
- pluripotent stem cells
- single molecule
- dna methylation
- lymph node metastasis
- drug delivery
- health information
- antiretroviral therapy