Structural and Dynamical Determinants of Influenza Pathogenicity and Virulence

正如最近在2009年“猪流感”大流行期间所表明的那样，新型甲型流感病毒可能在研制出疫苗之前就从动物宿主中出现，并在全球范围内传播。因此，在潜在的大流行毒株出现之前确定和评估它们所构成的威胁是非常有兴趣的。然而，鉴于在自然界中发现的甲型流感病毒种类繁多，目前尚不清楚应该关注哪些潜在的大流行前毒株，也不清楚如何对其在人类中的传播和致病性潜力进行安全研究。最近对这个问题的高度争议的方法是使用基因工程和人工选择高致病性H5N1 ？禽流感吗?获得能够在雪貂（人类流感的首选动物模型）之间呼吸道传播的病毒突变体。人们非常担心这些病毒有可能从实验室逃逸出来。通过这项工作，将开发一个虚拟的计算机“实验室”，在其中研究宿主-病原体相互作用的基本特性，而不会对公共卫生造成风险。由于流感病毒有丰富的序列和结构信息，这些技术适用于研究大范围的突变和遗传背景。此外，虚拟实验室的创建将扩大有能力研究这些现象的研究人员的数量，因为那些无法进入昂贵的、专门为高风险研究设计的实验实验室的研究人员将被这些方法赋予权力。这项工作解决了流感生物学中的一个基本问题：通过流感神经氨酸酶（NA）表面蛋白的缺失增强毒力的机制是什么？先前在Amaro实验室进行的单个流感膜糖蛋白血凝素（HA）和神经氨酸酶（NA）的MD模拟已经确定了实验验证的抗病毒化合物，这些化合物与以前从未被实验技术捕获的新糖蛋白口袋结合。这项工作在使实验数据合理化和以前瞻性方式驱动实验设计方面的能力是显著的。然而，流感糖蛋白是一个更大的病毒粒子表面的组成部分，共同参与宿主识别和感染过程。为此，建立了基于全病毒粒子低温电子层析数据的原子水平模型系统；这些完整的病毒颗粒模拟将是迄今为止进行的最大的原子模拟，并允许研究人员在现实环境中探索表面糖蛋白分布。此外，与宿主细胞受体结合的HA和通过末端唾液酸残基切割而消除受体结合的NA的功能平衡尚未得到充分表征。一种假设是，可变的HA/NA分布模式和突变产生独特的静电特性，改变药理学和内源性配体的结合动力学，从而促进毒力。这一假设将在为期一年的整个病毒结构的最先进的MD模拟中进行测试。

As illustrated most recently during the 2009 "swine flu" pandemic, novel strains of influenza A may emerge from animal reservoirs and spread globally among humans well before a vaccine against them can be developed. Thus, there is keen interest in identifying and evaluating the threat posed by potential pandemic strains before they emerge. However, given the large diversity of influenza A viruses found in nature, it is not clear which potentially pre-pandemic strains to focus on, nor how safe studies of their potential for transmissibility and pathogenicity in humans can be performed. Recent highly controversial approaches to this problem have used genetic engineering and artificial selection of highly pathogenic H5N1 ?bird flu? viruses to obtain mutants capable of respiratory transmission among ferrets, the preferred animal model for human influenza. There has been great concern over the possibility of these viruses escaping from the lab. A virtual, in silico "laboratory" in which to study fundamental properties of host-pathogen interaction without risk to public health will be developed with this work. The techniques are applicable to study of a wide range of mutations and genetic backgrounds due to the wealth of sequence and structural information available for the influenza virus. Furthermore, the creation of a virtual lab will expand the number of researchers who are able to investigate such phenomena, as researchers who do not have access to expensive, specially designed experimental laboratories for high risk research will be empowered by these approaches.The work addresses a fundamental question in influenza biology: What is the mechanism by which virulence is enhanced by deletions in the stalk of the influenza neuraminidase (NA) surface protein? MD simulations of the individual influenza membrane glycoproteins hemagglutinin (HA) and neuraminidase (NA), carried out previously in the Amaro Lab, have identified experimentally validated antiviral compounds that bind to new glycoprotein pockets never before captured by experimental techniques. This work has been remarkable in its ability to rationalize experimental data and drive experimental design in a prospective fashion. However, influenza glycoproteins are components of a much larger virion surface that collectively participates in host recognition and infection processes. To study this, atomic level model systems were built based on cryo-electron tomographic data of full viral particles; these full virus particle simulations will be the largest atomistic simulations performed to date and allow researchers to explore the surface glycoprotein distributions in realistic context. Additionally, the functional balance of HA, which binds to host-cell receptors, and NA, which abrogates receptor binding via cleavage of terminal sialic-acid residues, has not yet been fully characterized.  One hypothesis is that variable HA/NA distribution patterns and mutations produce unique electrostatic properties that alter the binding kinetics of both pharmacological and endogenous ligands, thereby contributing to virulence. This hypothesis will be tested in state-of-the-art MD simulations of entire viral constructs over a one-year period.