TOWARD DEVELOPING NEW ANTIVIRALS AGAINST AVIAN INFLUENZA MEMBRANE GLYCOPROTEINS

这个子项目是许多研究子项目中利用 资源由NIH/NCRR资助的中心拨款提供。子项目和 调查员(PI)可能从NIH的另一个来源获得了主要资金， 并因此可以在其他清晰的条目中表示。列出的机构是 该中心不一定是调查人员的机构。 流感的膜糖蛋白，特别是神经氨酸酶，是主要的抗病毒靶标，是显著的 灵活的蛋白质。因此，新的抗病毒药物的开发很可能取决于我们解释和 围绕这种灵活性进行设计。这对药物发现界提出了一个关键的方法学挑战，并且是 我们正在积极追求。这个协作项目的总体目标是利用我们的新计算工具 优化在虚拟屏幕中发现的化合物，然后获得关键实验数据，以改善电流 大的、高度灵活的配体和受体的对接方法。 威尔逊实验室(TSRI)是确定流感蛋白质结构的先驱，目前正在测试我们的第一套 新发现的化合物，它们是使用最近开发的松弛络合方案(RCS)发现的 神经氨酸酶抑制分析中的基于集合的虚拟筛选技术(见(cheng et al.，2008))。 关于最有希望的化合物的精确结合模式的结晶学数据也将被获得。这些 化合物及其结合模式随后将用于该项目的计算机辅助药物的改进 设计(CADD)技术。根据这些结果，麦卡蒙实验室将使用一种新的 基于AutoDock的化合物优化方法，再次考虑到受体的灵活性。经过优化后， 我们在夏普莱斯实验室(TSRI)的合成合作者将合成我们预测的最有希望的化合物和 威尔逊实验室将确定它们的结合模式。设想了多轮优化，最终目标是 开发利用N1活性部位区域的灵活性的新化合物，如 与其他亚型相比。我们生成的实验数据将在验证和验证过程中发挥关键作用 改进理论方法，并将有助于开发可开发的新的先导化合物 变成了抗病毒药物。

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. The influenza membrane glycoproteins, particularly neuraminidase, which is a major antiviral target, are remarkably flexible proteins. Thus it is highly likely that development of new antivirals will depend on our ability to account for and design around this flexibility. This presents a key methodological challenge to the drug discovery community and is one that we are actively pursuing. The overall goals of this collaborative project are to utilize our new computational tool to optimize compounds discovered in virtual screens and then obtain key experimental data in order to improve the current docking approaches for large and highly flexible ligands and receptors. The Wilson lab (TSRI) is a pioneer in determining structures of influenza proteins and is presently testing our first set of newly discovered compounds, which were discovered using the recently developed relaxed complex scheme (RCS) ensemble-based virtual screening technique (presented in (Cheng et al., 2008)), in neuraminidase inhibition assays. Crystallographic data on the precise binding modes of the most promising compounds will also be obtained. These compounds and their binding modes will subsequently be used in the refinement of the project computer-aided drug design (CADD) technique. Based on these results, the McCammon lab will then optimize the compounds using a new AutoDock-based approach to compound optimization that again takes receptor flexibility into account. After optimization, our synthetic collaborators in the Sharpless lab (TSRI) will synthesize the most promising compounds we predict and the Wilson lab will determine their binding modes. Multiple rounds of optimization are envisioned, with the ultimate goal being the development of new compounds that take advantage of the flexibility in the N1 active site region, as compared to other subtypes. The experimental data that we generate will play a critical role in the verification and refinement of the theoretical approach and will aid in the development of new lead compounds that could be developed into antiviral drugs.