Integration of Biopolymer Design and Modeling: Silk Gene Delivery Systems

描述(由申请人提供)：拟议研究的目标是将实验和建模方法结合起来，以设计和实施聚合的、非病毒的基因传递系统。需要高效和有针对性的非病毒基因递送系统来改进细胞修饰，并避免当前非病毒和病毒基因递送系统所经历的并发症。假设通过使用集成的实验-计算方法，可以实现一种新的策略来指导高效基因递送系统的准备和评估。这样的成功将以更全面和更有效的进程改变这一领域。基于蜘蛛丝系统的基因设计的四嵌段蛋白聚合物将用于提供对颗粒大小、结合动力学和细胞靶向的特定控制。将使用集成的多尺度建模和生物工程方法来指导和加快设计过程。这种方法的独特之处在于，通过基因蓝图和计算预测的集成来提供迭代反馈，以完善基因交付的实验设计(从而提高效率)，从而实现高度定制的特征。这些计划将在两个迭代目标中进行处理，(1)蜘蛛丝基因传递系统的VITR准备和表征以及(2)Silico多尺度建模。拟议工作的结果将是将材料特性与功能结果(特异性、转染率、释放动力学)相关联的实验数据集。 正如多尺度建模所预测的那样。我们预计，计划中的研究将提供有用的多尺度模型，捕捉用于基因传递的生物材料的复杂性。

DESCRIPTION (provided by applicant): The goal of the proposed study is to integrate experimental and modeling approaches for the design and implementation of polymeric, nonviral, gene delivery systems. Nonviral gene delivery systems that are efficient and targeted are needed to improve cell modifications and to avoid complications experienced with current nonviral and viral gene delivery systems. It is hypothesized that by using an integrated experimental- computational- approach, a new strategy to guide the preparation and assessment of efficient gene delivery systems can be achieved. Such success would transform the field with a more comprehensive and efficient process. Genetically designed tetra-block protein polymers based on spider silk systems will be used to provide specific control of particle size, binding kinetics, and cell targeting. Integrated multiscale modeling and bioengineering approaches will be used to guide and accelerate the design process. The unique feature of this approach is the highly tailored features controlled via genetic blueprints and the integration of computational predictions to provide iterative feedback to refine the experimental designs (and thus the efficacy) of gene delivery. The plans will be addressed in two iterative Aims, (1) In vitr preparation and characterization of spider silk gene delivery systems and (2) In silico multiscale modeling. The outcome of the proposed work will be experimental data sets that correlate material features with functional outcomes (specificity, transfection efficiency, release kinetics) as predicted by multiscale modeling. We anticipate that the insights from the planned study would provide useful multiscale models that capture the complexity of biomaterials used in gene delivery.