Multiscale studies of HIV infection and treatment

描述(由申请人提供)：这项申请的长期目标是开发物理模型和数学工具，用于优化融合抑制疗法对艾滋病毒的治疗。病毒粒子-受体相互作用的动力学数据将被用于基于融合性(在存在不同的CD4和CCR5受体表面浓度的情况下)对HIV毒株进行定量分类。将提出艾滋病毒混合毒株的检测方法。具体目标包括： (1)建立HIV病毒包膜蛋白-细胞受体相互作用和融合率的化学动力学模型。这些模型将被用来分析动态测量和估计宿主内病毒种群模型中使用的参数。(2)开发基于动力学结合和融合数据的菌株分类统计方法。将使用两种方法：主成分分析(PCA)和聚类分析。主成分分析将直接应用于数据，以寻找其融合能力跨越受体/辅助受体(例如，CD4/CCR5)浓度的足够范围的病毒株。在AIM(1)中导出的动力学模型将用来表示集群分析中的动力学数据。(3)利用分支过程理论和从AIMS(1)和(2)获得的信息来发展和改进HIV进化模型。既要研究确定性模型，也要研究随机模型。(4)开发基因治疗的确定性模型(例如，通过修改CD4/CCR5的表达)，以确定在面对突变时拟议的干细胞基因治疗的有效性。确定性病毒种群模型将与AIM(3)中发展的随机理论相结合，以计算低浓度、基因治疗抗药性菌株出现和灭绝的概率。这项拟议的研究代表了对HIV-受体/辅助受体相互作用的基础研究的一种系统的、定量的方法，并可能有助于优化药物治疗和基因治疗。

DESCRIPTION (provided by applicant): The long-term objective of this application is to develop physical models and mathematical tools for optimizing treatments of HIV with fusion-inhibiting therapies. Kinetic data of virion-receptor interactions will be used to quantitatively categorize HIV strains based on fusogenicity (in the presence of varying CD4 and CCR5 receptor surface concentrations). Assays for mixtures of HIV strains will be proposed. Specific aims include: (1) Developing chemical kinetic models for HIV virus envelope protein-cell receptor interactions and fusion rates. These models will be used to analyze kinetic measurements and estimate parameters used in within-host virus population models. (2) Developing statistical measures for categorizing strains based on kinetic binding and fusion data. Two approaches will be used: principal components analysis (PCA) and cluster analysis. PCA will be applied directly to the data to find the viral strains whose fusogenicities span a sufficient range in receptor/coreceptor (e.g., CD4/CCR5) concentrations. Kinetic models derived in Aim (1) will be used to represent the kinetic data in a cluster analysis. (3) Using the theory of branching processes and the information garnered from Aims (1) and (2) to develop and improve upon models of HIV evolution. Both deterministic and stochastic models will be studied. (4) Developing deterministic models for gene therapy (via modification of, e.g., CD4/CCR5 expression) to determine the efficacy of proposed stem cell gene therapies in the face of mutations. Deterministic viral population models will be coupled to the stochastic theories developed in Aim (3) to compute probabilities of emergence and extinction of low-concentration, gene therapy-resistant strains. The proposed research represents a systematic, quantitative approach to the basic study of HIV-receptor/coreceptor interactions, and will potentially aid in optimizing drug treatments and gene therapies.