Models to predict protein biomaterial performance

描述（由申请人提供）：迫切需要了解组织培养刺激如何影响组织构建体的发育和功能，最终目标是消除资源密集型试错筛选。我们的目标是开发生物材料体内性能的预测评估，以便使用基于自下而上建模工具包的更合理的方法来指导所需生物材料的制备。这种新的预测方法将节省时间、动物和成本，并加速这种修复和再生系统的转化。我们提出的方法的一个重要特点是直接集成的建模和实验在多个长度尺度，并使用跨长度尺度的分层材料架构，以达到增强的材料功能。我们的假设是，生物材料性能的预测可以通过结合使用合适的实验模型来实现，以涵盖聚合物的功能（化学，分子量），加工（纤维机械性能，层次结构，降解速率）和建模在不同的长度尺度的材料结构层次（从化学到宏观）。由于该领域的一般需求，我们选择了承重应用作为重点，例如前交叉韧带、肩袖、膀胱吊带、疝补片、血管、神经导管和其他组织。两种经过充分研究的可降解聚合物系统，丝和胶原蛋白，将用于实验研究和模型构建，因为它们可直接用于高度受控的制备和加工，并涵盖一系列机械性能和降解速率。在所有情况下，我们都建立在我们对这些基于蛋白质的生物材料的广泛研究的基础上，以及开发蛋白质结构和功能的分层模型。该计划将在三个目标，（1）在体外制备和表征的蛋白质纤维为基础的生物材料通过微流控流聚焦，（2）开发多尺度模型，跨越相关的长度和时间尺度;包括量子力学、原子和分子模拟、几种粗粒和粒子方法，以及基于有限元的连续体方法，和（3）纤维基生物材料的体内表征，以评估性能以改进模型。一个跨学科的研究小组将进行研究，包括Markus Buehler（麻省理工学院）的多尺度建模和模拟，大卫卡普兰（塔夫茨大学）的聚合物设计/表征和动物研究，和乔伊斯黄（波士顿大学）的聚合物加工/表征。在所有情况下，强有力的初步数据支持计划研究的各个方面。我们的多尺度方法的独特之处在于实验与模拟在一个有凝聚力的团队中的密切联系。

DESCRIPTION (provided by applicant): There is a critical need to understand how tissue culture stimulation affects tissue construct development and function, with the ultimate goal of eliminating resource-intensive trial-and-error screening. Our goal is to develop predictive assessments of the in vivo performance of biomaterials so that a more rational approach based on a bottom-up modeling toolkit is used to guide the preparation of the required biomaterials. This new predictive approach would save time, animals, costs and accelerate the translation of such repair and regenerative systems. An important feature of our proposed approach is the direct integration of modeling and experimentation at multiple length scales, and the use of hierarchical material architectures across length scales, to reach enhanced material function. Our hypothesis is that predictions of biomaterials performance can be attained by the combined use of suitable experimental models to cover polymer features (chemistry, molecular weight), processing (fiber mechanical properties, hierarchical structure, degradation rate) and modeling at different length scales of materials structural hierarchy (from chemical to macroscopic). We have selected load bearing applications as the focus due to the generic needs in this field, such as for the anterior cruciate ligament, rotator cuff, bladder slings, hernia meshes, blood vessels, nerve guides and other tissues. Two well studied degradable polymer systems, silks and collagen, will be used for the experimental studies and model building, as they are directly amendable to highly controlled preparations and processing and cover a range of mechanical properties and degradation rates. In all cases, we build upon our extensive prior studies with these protein-based biomaterials, as well as developing hierarchical models of protein structure and function. The plans will be addressed in three Aims, (1) the in vitro preparation and characterization of the proteins in fiber-based biomaterials via microfluidic flow focusing, (2) development of multiscale models that span relevant length- and time-scales; including quantum mechanics, atomistic and molecular simulation, several coarse-grain and particle methods, and finite-element based continuum methods, and (3) in vivo characterization of fiber-based biomaterials to assess performance to refine the models. An interdisciplinary team of investigators will conduct the studies, including Markus Buehler (MIT) for multiscale modeling and simulation, David Kaplan (Tufts University) for polymer design/characterization and animal studies, and Joyce Wong (Boston University) for polymer processing/characterization. In all cases, strong preliminary data support all aspects of the planned study. What is unique in our multiscale approach is the intimate connection of experiment with simulation in a cohesive team.