Adeno-Associated Virus Gene Therapy Vectors: Molecular Interactions on Cell Entry

项目描述 腺相关病毒（AAV）是一种领先的基因治疗载体，用于递送DNA以纠正遗传错误或遗传缺陷。 易患病的体质我们的目标是了解病毒与宿主之间的相互作用， 入境这一基础将支持广泛追求的目标，操纵细胞特异性，有效转导， 并减少脱靶副作用。这一目标激发了广泛的遗传和表型 表征，其中，与结构，提供了一个特殊的范例，一般的见解病毒进入。 我们的结合和siRNA研究对已发表的共受体产生了怀疑，激发了一种基因陷阱筛选， 单倍体细胞系在抗腺病毒突变细胞中最常发生的基因编码一种我们命名的蛋白质 以nM亲和力结合，抑制转导，并且对于所有AAV血清型和细胞类型是必需的AAVR 测试.我们已经表达了AAV结合结构域，并将通过低温冷冻来确定复合物的结构。 电子显微镜（EM），然后通过诱变进一步表征相互作用。 其他基因也被筛选出来。我们将确定哪些编码蛋白质与AAV相互作用， 通过光诱导交联、下拉和质谱鉴定相互作用的AAVR 域.这些将被表达用于结合分析和混合X射线/EM结构。基因陷阱表明 潜在的合作伙伴，不仅在细胞表面，但在AAV的运输到核周的transGolgi 这将阐明AAV的磷脂酶A2结构域如何被释放用于内体逃逸。 将开发适用于AAV的EM方法以供一般使用。为了改进混合结构，我们的 地图拟合优化将在模型灵活性上加入简约约束，以避免常见的问题 在中等分辨率下过度拟合。差异图分析将通过基于模型的 校准，以提高灵敏度与小的配体和微妙的构象变化，可以 高分辨率EM分析。这将适用于研究AAV与细胞外聚糖的连接， 或在其他实验室中与配体与离子通道、核糖体或酶复合物的结合。 在MIRA框架内，将继续对蛋白质动力学的合作研究作出贡献。这些是 结合晶体结构与NMR弛豫色散和残余偶极耦合来表征速率， 限制精氨酸激酶翻转时的毫秒/微秒蛋白质运动。我们的模型系统很有启发性 对内在运动和构象选择的一般原理知之甚少。这些基本 问题是首要目标，但研究也反馈到方法的发展。的NMR 松弛交换数据允许验证测试，我们的简约模型参数化捕获真实的 构象变化总之，我们将继续致力于挑战结构生物学， 推动广泛适用的方法的发展的基本目标和应用目标。

Project Description Adeno-associated virus (AAV) is a leading gene therapy vector for delivery of DNA to correct genetic errors or predispositions to disease. Our objective is an understanding of the virus-host interactions that mediate cell entry. This foundation will support the widely sought goal of manipulating cell specificity, efficiently transducing desired cells and reducing off-target side effects. This goal has motivated extensive genetic and phenotypic characterization, which, with structure, provide an exceptional paradigm for general insights into viral entry. Our binding and siRNA studies cast doubt on published co-receptors, motivating a gene trap screen in a haploid cell line. The gene most frequently hit in AAV-resistant mutant cells, encoded a protein that we named AAVR which binds with nM affinity, inhibits transduction, and is essential for all AAV serotypes and cell types tested. We have expressed the AAV-binding domains, and will determine a structure of the complex by cryo- electron microscopy (EM) before further characterizing the interactions through mutagenesis. Other genes were implicated by the screen. We will determine which encoded proteins interact with AAV or AAVR through photo-induced cross-linking, pull-down, and mass spectrometric identification of interacting domains. These will be expressed for binding analysis, and hybrid x-ray/EM structure. The gene trap indicates potential partners, not just at the cell surface, but during AAV's trafficking to the peri-nuclear trans Golgi network, and which will illuminate how AAV's phospholipase A2 domain is released for endosomal escape. EM methods, applicable to AAV, will be developed for general use. For refinement of hybrid structures, our map-fitting optimization will incorporate parsimony restraints on model flexibility to avoid the common problem of over-fitting at intermediate resolution. Difference map analysis will be improved, through model-based calibration, to enhance the sensitivity with which small ligands and subtle conformational changes can be analyzed by high resolution EM. This will be applicable to studies of AAV's attachment to extracellular glycans, or to the binding of ligands to ion channels, ribosomes or enzyme complexes in other laboratories. Within the MIRA framework, contributions to collaborative studies of protein dynamics will continue. These are integrating crystal structure with NMR relaxation dispersion and residual dipolar couplings to characterize rate- limiting milli-/micro-second protein motions in arginine kinase as it turns over. Our model system is illuminating poorly understood general principles of intrinsic motions and conformational selection. These fundamental questions are the primary goal, but the research also feeds back into methods development. The NMR relaxation exchange data allows validation tests that our parsimonious model parameterization captures real conformational changes. In summary, we will continue to work on challenging structural biology with both fundamental and applied goals that drive the development of widely applicable methodology.