DEVELOPMENT OF COMPUTATIONAL TOOLS TO ANALYZE INFLUENZA RECEPTOR BINDING DATA

开发分析流感受体结合数据的计算工具

• 批准号: 8361841
• 负责人: ROBERT J WOODS
• 金额: $ 0.18万
• 依托单位: UNIVERSITY OF GEORGIA
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-02-01 至 2012-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8361841
• 关键词: Affinity; Animals; Binding; Bioinformatics; Centers for Disease Control and Prevention (U.S.); Data; Development; Funding; Grant; Human; Influenza; Laboratories; Learning; Ligands; National Center for Research Resources; Polysaccharides; Principal Investigator; Proteins; Public Health; Relative (related person); Reporting; Research; Research Infrastructure; Research Personnel; Resources; Risk Assessment; Source; Specificity; Time; Translating; United States National Institutes of Health; Veterinary Medicine; Virus; base; computerized tools; cost; improved; influenzavirus; pandemic influenza; receptor binding; tool

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. A key lesson learned from the 2009-2010 influenza pandemic was the importance of being prepared for viruses that jump from animal species by developing the ability to bind the sialoglycans of the human airway. Toward this end, the CDC has been using glycan arrays to analyze the binding specificity of influenza viruses from various animal species. Glycan array data, however, tends to be difficult to interpret because it provides only apparent relative affinities for binding to a given protein, and the glycan binding results are often riddled with false positives and negatives. This project aims to develop the bioinformatic tools necessary to improve analysis of glycan array data and reduce the time needed to convert laboratory bench results into actionable information for public health decision-makers. In addition, the tools may be employed in veterinary medicine for various aspects of influenza surveillance. The proposed bioinformatic tools will be capable of analyzing glycan array data to identify true binders, their minimal motifs, and binding affinity, as well as performing structural assessment to elucidate the basis for binding or non-binding. The ability to rapidly translate glycan array data into concise, practical information will greatly improve the CDC's ability to provide influenza risk assessment. Researchers would gain the ability to screen a given influenza virus and immediately report its specificity based on the types of ligands it binds and assess its infectivity based on relative binding affinity.

这个子项目是利用资源的许多研究子项目之一。 由NIH/NCRR资助的中心拨款提供。对子项目的主要支持 子项目的首席调查员可能是由其他来源提供的， 包括美国国立卫生研究院的其他来源。为子项目列出的总成本可能 表示该子项目使用的中心基础设施的估计数量， 不是由NCRR赠款提供给次级项目或次级项目工作人员的直接资金。 从2009-2010年流感大流行中吸取的一个关键教训是，必须通过发展与人类呼吸道唾液多聚糖结合的能力，为从动物物种中传播的病毒做好准备。为此，疾控中心一直在使用多糖阵列来分析来自不同动物物种的流感病毒的结合特异性。然而，糖阵列数据往往很难解释，因为它只提供了与给定蛋白质结合的明显相对亲和力，并且糖结合结果经常充满假阳性和假阴性。该项目旨在开发必要的生物信息学工具，以改进对多糖阵列数据的分析，并减少将实验室结果转化为公共卫生决策者可采取行动的信息所需的时间。此外，这些工具可用于兽医对流感监测的各个方面。 建议的生物信息学工具将能够分析糖链阵列数据，以确定真正的结合剂、它们的最小基序和结合亲和力，以及进行结构评估，以阐明结合或非结合的基础。将糖链阵列数据快速转换为简明、实用信息的能力将极大地提高疾控中心提供流感风险评估的能力。研究人员将获得筛选特定流感病毒的能力，并根据其结合的配体类型立即报告其特异性，并根据相对结合亲和力评估其传染性。