Integration of Biopolymer Design and Modeling: Silk Gene Delivery Systems

描述（由申请人提供）：拟议研究的目标是整合实验和建模方法，用于设计和实施聚合物、非病毒、基因递送系统。需要有效和靶向的非病毒基因递送系统来改善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。假设通过使用综合的实验-计算-方法，可以实现指导高效基因递送系统的制备和评估的新策略。这一成功将以一个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质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。综合多尺度建模和生物工程方法将用于指导和加速设计过程。这种方法的独特之处在于通过遗传蓝图控制的高度定制的特征和计算预测的整合，以提供迭代反馈来完善基因递送的实验设计（从而提高功效）。该计划将在两个迭代目标中解决，（1）蜘蛛丝基因递送系统的体外制备和表征，以及（2）计算机多尺度建模。拟议工作的结果将是实验数据集，这些数据集将材料特征与功能结果（特异性，转染效率，释放动力学）相关联。 正如多尺度建模所预测的那样。我们预计，计划中的研究的见解将提供有用的多尺度模型，捕捉基因递送中使用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.