DEVELOPMENT OF COMPUTATIONAL TOOLS TO ANALYZE INFLUENZA RECEPTOR BINDING DATA

这个子项目是许多利用资源的研究子项目之一 由NIH/NCRR资助的中心拨款提供。子项目的主要支持 而子项目的主要调查员可能是由其他来源提供的， 包括其它NIH来源。 列出的子项目总成本可能 代表子项目使用的中心基础设施的估计数量， 而不是由NCRR赠款提供给子项目或子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，必须通过开发结合人类呼吸道唾液聚糖的能力，为从动物物种传播的病毒做好准备。为此，CDC一直在使用聚糖阵列来分析来自各种动物物种的流感病毒的结合特异性。然而，聚糖阵列数据往往难以解释，因为它仅提供与给定蛋白质结合的表观相对亲和力，并且聚糖结合结果通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，以改善聚糖阵列数据的分析，并减少将实验室工作台结果转化为公共卫生决策者可操作信息所需的时间。此外，这些工具可用于兽医学中流感监测的各个方面。 所提出的生物信息学工具将能够分析聚糖阵列数据以识别真正的结合剂、其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。将聚糖阵列数据快速转化为简明实用信息的能力将大大提高CDC提供流感风险评估的能力。研究人员将获得筛选给定流感病毒的能力，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感染性。

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.