Postdoctoral Fellowship: MPS-Ascend: Coarse-Grained Modeling of Aggrecan- Mimetic Copolymers: Polymer Design and Architecture Effects on Structure and Phase Behavior

拟议的工作将导致材料设计框架的发展，该框架使用分子动力学模拟和机器学习来设计模仿生物分子聚合体的候选聚合物材料。骨胶凝蛋白存在于软骨组织中，骨胶凝蛋白的降解与骨性关节炎的发生和发展有关。骨关节炎是一种折磨关节的疾病，关节的软骨组织恶化，导致关节疼痛、炎症和功能障碍。这种疾病尤其影响老年人，据信有10%的60岁以上人口受到影响，每年给美国经济造成的损失超过600亿美元。聚集蛋白模拟聚合物被认为是骨关节炎再生治疗的一种很有前途的方法。在使用聚合蛋白模拟物开发治疗方法的过程中，有几个必须克服的挑战。候选疗法必须具备克服这些挑战的关键特性，包括可注射性、生物相容性和治疗区域内的固定性。这项工作将开发计算方法，使用模拟和机器学习来设计候选聚合物，这些聚合物具有用于软骨治疗所需的性能。这种设计框架可以进一步用于设计各种健康和消费产品的材料。PI将与他们的导师和机构合作，通过为有抱负的材料科学家建立的培训计划，以及旨在为社区大学生提供STEM研究生教育和研究指导和接触的外展活动，扩大代表性不足群体的参与。PI为扩大代表性不足群体在STEM领域的参与所做的这些努力，也将借鉴他们过去参与多元化、公平和包容项目以及过去作为社区大学生的经历。技术概述：本研究的目标是开发一种用于设计聚类共聚物的计算模型，该模型使用粗粒度分子模拟和机器学习方法，并通过实验数据进行验证。所提出的共聚物将由热响应组分和带电组分组成，以有效地模拟蛋白多糖聚集体，同时实现用作注射处理的必要材料特性。候选药物必须具有生物相容性，可注射性，一旦进入治疗区域，并且必须在目标组织中保持不动。PI提出了一种由生物相容性和带电聚合物聚（4-苯乙烯磺酸钠）（PSSNa）和热响应性聚合物聚（n -异丙基丙烯酰胺）（PNIPAm）制成的共聚物。目标是设计一种共聚物，具有聚集蛋白的电荷密度，并在生理温度下经历溶胶-凝胶转变。后者将确保材料在室温下可注射，并在治疗区域以体温固定。PI将为所提议的共聚物开发一个粗粒度模型，该模型将被参数化，并通过所提议项目的合作者提供的实验结果进行验证。PI将使用分子动力学模拟中的粗粒度模型来模拟具有多种共聚物设计参数的共聚物，如共聚物结构、侧链接枝密度、侧链长度和分子量。模拟和实验数据将用于开发数据驱动的正演和反演模型，该模型可以预测理想溶液行为和聚合物链构象性质的最佳聚合物设计。模拟和数据驱动模型将用于生成候选材料，作为潜在的注射治疗，用于修复因骨关节炎进展而受损的软骨。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

NON-TECHNICAL SUMMARY The proposed work will lead to the development of a materials design framework that uses molecular dynamics simulations and machine learning to design candidate polymeric materials that mimics the biomolecule aggrecan. Aggrecan is found in cartilage tissue, and the degradation of aggrecan has been implicated in the onset and progression of the disease osteoarthritis. Osteoarthritis is a disease that afflicts the joints, where the cartilage tissue in the joint is deteriorated leading to pain, inflammation, and dysfunction of the joint. This disease affects senior citizens in particular, and it is believed to affect 10% of the population over the age of 60 and costs the US economy over $60 billion dollars annually. Aggrecan mimetic polymers are seen as a promising approach to regenerative treatment for osteoarthritis. There are several challenges in developing treatments using aggrecan mimics that must be overcome. Key properties the candidate treatments must possess to overcome these challenges include injectability, biocompatibility, and immobility once in the treatment area. This work will develop computational methods, using simulation and machine learning to design candidate polymers that possess the desired properties for use in cartilage treatment. This design framework can be further utilized to design materials for a variety of challenges in health and consumer products. The PI will work with their mentor and institution to broaden participation amongst underrepresented groups through an established training program for aspiring materials scientists as well as outreach activities aimed at providing community college students with guidance and exposure to STEM graduate education and research. These efforts of the PI to broaden participation of underrepresented groups in STEM will also be informed by their past participation in diversity, equity and inclusion programs and past experiences as a community college student.TECHNICAL SUMMARYThe goal of the proposed work is to develop a computational model for designing aggrecan mimetic copolymers, that uses coarse-grained molecular simulations and machine learning methods, and is informed and validated by experimental data. The proposed copolymer will be made up of a thermoresponsive component and a charged component to effectively mimic the proteoglycan aggrecan, while achieving necessary material properties for use as an injection treatment. The candidate must be biocompatible, injectable, and once in the treatment area, and must remain immobile in the target tissue. The PI proposes a copolymer made with the biocompatible and charged polymer poly(sodium-4-styrene sulfonate) (PSSNa) and the thermoresponsive polymer poly(N-isopropylacrylamide) (PNIPAm). The goal is to design a copolymer that possesses the charge density of aggrecan and undergoes a sol-gel transition at physiological temperatures. The latter will ensure that the material is injectable at room temperature and is immobilized at body temperature in the treatment area. The PI will develop a coarse-grained model for the proposed copolymer, that will be parameterized and validated by experimental results provided by the collaborator on the proposed project. The PI will use the coarse-grained model in molecular dynamics simulations to model copolymers with a variety of copolymer design parameters, such as the copolymer architecture, sidechain grafting density, side chain length, and molecular weight. The simulation and experimental data will be used to develop a data-driven forward and inverse model that can predict optimal polymer design for desired solution behavior and polymer chain conformation properties. The simulation and data-driven models will be used to generate candidate materials to serve as potential injection treatments for restoring cartilage damaged by the progression of osteoarthritis.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.