Predicting cross-reactivity of protein antigens using 3D motifs

使用 3D 基序预测蛋白质抗原的交叉反应性

• 批准号: 8299900
• 负责人: WERNER A BRAUN
• 金额: $ 34万
• 依托单位: UNIVERSITY OF TEXAS MED BR GALVESTON
• 依托单位国家: 美国
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-02-01 至 2013-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8299900
• 关键词: Agriculture; Allergens; Allergic; Amino Acid Sequence; Antibodies; Antibody Formation; Antigen-Antibody Complex; Antigens; Archives; Area; B-Lymphocyte Epitopes; Binding; Bioinformatics; Biomedical Research; Common Epitope; Communities; Computer Analysis; Computing Methodologies; Coupled; Data; Data Correlations; Data Set; Databases; Dengue; Descriptor; Docking; Engineering; Environment; Epitopes; Family; Flavivirus; Food; Food Safety; Funding; Goals; Guidelines; Homologous Protein; Homology Modeling; IgE; Individual; Knowledge; Literature; Marketing; Membrane Proteins; Methods; Modeling; Mutation; Organism; Process; Property; Proteins; Public Health; Regulation; Research; Scheme; Screening procedure; Sequence Analysis; Software Tools; Structural Protein; Structure; Surface; Symptoms; T-Lymphocyte Epitopes; Testing; Training; United States National Institutes of Health; Vaccine Design; Vaccines; Viral; Viral Antigens; Viral Proteins; Virus; West Nile virus; Work; base; chemical property; clinically relevant; computerized tools; cross reactivity; data mining; design; experience; flexibility; improved; innovation; neutralizing antibody; novel; novel vaccines; prevent; programs; protein complex; protein structure; relational database; structural biology; three dimensional structure; three-dimensional modeling; tool; vaccine candidate; vaccine development; viral resistance; virtual