Multiscale studies of HIV infection and treatment

描述（由申请人提供）：本申请的长期目标是开发用于优化融合抑制疗法治疗HIV的物理模型和数学工具。病毒体-受体相互作用的动力学数据将用于基于融合性（存在不同的CD 4和CCR 5受体表面浓度）对HIV毒株进行定量分类。将提出对艾滋病毒株混合物的测定。具体目标包括： (1)开发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。这些模型将用于分析动力学测量值并估计宿主内病毒群体模型中使用的参数。(2)基于动力学结合和融合数据开发用于菌株分类的统计测量。将使用两种方法：主成分分析和聚类分析。PCA将直接应用于数据，以找到其融合性在受体/辅助受体中跨越足够范围的病毒株（例如，CD 4/CCR 5）浓度。将使用目标（1）中推导的动力学模型代表聚类分析中的动力学数据。 (3)利用分支过程理论和从目标（1）和（2）中获得的信息，开发和改进HIV进化模型。将研究确定性和随机模型。(4)开发用于基因治疗的确定性模型（通过修改，例如，CD 4/CCR 5表达），以确定所提出的干细胞基因疗法在面对突变时的功效。确定性病毒种群模型将与目标（3）中开发的随机理论相结合，以计算低浓度、基因治疗抗性菌株的出现和灭绝概率。拟议的研究代表了一种系统的，定量的方法，艾滋病毒受体/辅助受体相互作用的基础研究，并将有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.