Directed Biomineralization: Designing Peptides to Control Crystal Nucleation and Growth

非技术：该奖项由约翰霍普金斯大学材料研究部生物材料项目颁发，主要研究蛋白质控制矿物成核和生长过程的基础材料研究。受生物有机体的启发，生物有机体具有制造精美固体材料（如螺旋壳和内部骨架）的令人印象深刻的能力，其目的是表征和利用生物材料制造策略。研究者试图了解晶体生长机制及其与吸附生物分子的相互作用，这样人们可能最终使用肽来指导固体纳米材料的生长，例如用于储能应用或先进的医疗或结构材料。这种基础研究使定制材料的设计成为可能，将对制造业产生革命性的影响，特别是在纳米技术、传感、能源、医药和抗生物污染方面。计算算法将广泛分发，并可通过网络网关访问。该项目将培养一名在化学工程、生物物理学、纳米技术和材料科学等领域进行跨学科研究的研究生。蛋白质结构预测和设计教学模块将扩展到生物矿化。拓展活动将包括每周到当地一所小学参加课后STEM项目，试点一个以计算机领域女性为重点的实习项目，以及让一名高中生作为暑期实习生参与其中。技术：该项目将结合晶体成核和生长的热力学和动力学理论与计算和实验方法，通过实验测试计算设计的肽，优化引导碳酸钙生长。在计算设计和预测与实验观察交替进行的设计周期之后，结果将加速发现蛋白质如何与表面相互作用，肽如何引导非均相成核，吸附如何影响矿物生长，以及如何利用这些现象来创建原子组装材料和结构。新的多肽将通过一个渐进的层次实验测量探测成核能力，结合亲和力，步进速度和生物矿物习惯进行测试。在每个阶段，实验将为计算模型提供数据。实际上，这项工作将推动计算设计和实验的反馈循环，将可能的相互作用范围缩小到实验支持的领域。对数十种相关肽设计的实验和计算相结合，将提供一个广泛的吸附控制矿化的分子尺度图像。这些数据将为能量函数提供新的基准，并为蛋白质表面相互作用和建模提供新的见解，从而提高对成核，吸附，晶体生长，材料合成和分子工程的整体理解。

Non-technical: This award by the Biomaterials program in the Division of Materials Research to Johns Hopkins University is in developing fundamental materials research into the processes by which proteins control mineral nucleation and growth. Inspired by biological organisms that have the impressive ability to craft exquisite solid materials such as spiraled shells and internal skeletons, the aim is to characterize and utilize biological material-building strategies. The investigator seeks to understand crystal growth mechanisms and their interplay with adsorbed biomolecules, such that one might eventually use peptides to direct the growth of solid nanomaterials, for example for energy storage applications or advanced medical or structural materials. Design of custom materials, enabled by this basic research, will be transformative for manufacturing, especially in nanotechnology, sensing, energy, medicine, and anti-biofouling. The computational algorithms will be distributed broadly and made accessible through a web gateway. The PI will train a graduate student in cross-disciplinary studies in chemical engineering, biophysics, nanotechnology and materials science. Protein structure prediction and design teaching modules will be expanded to include biomineralization. Outreach will include weekly team visits to a local elementary school for an after-school STEM program, piloting of an intern program focused on women in computing, and the involvement of a high school student as a summer intern.Technical: This project will tie together thermodynamic and kinetic theories of crystal nucleation and growth with computational and experimental methods by experimentally testing computationally designed peptides that are optimized to guide calcium carbonate growth. Following a design cycle that alternates computational design and prediction with experimental observation, results will accelerate the discovery of how proteins interact with surfaces, how peptides can guide heterogeneous nucleation, how adsorbates affect mineral growth, and how these phenomena can be harnessed to create atomically-assembled materials and structures. New peptides will be tested through a progressive hierarchy of experimental measurements probing nucleation ability, binding affinities, step velocities, and biomineral habit. At each stage, the experiments will provide data to inform the computational model. In effect, this work will drive a feedback loop of computational design and experiments, narrowing the field of possible interactions to those supported by the experimentation. The combination of experiments and computations on dozens of related peptide designs will provide an extensive molecular-scale picture of adsorbate-controlled mineralization. These data will provide new benchmarks for energy functions and new insights into protein-surface interactions and modeling in general, leading to improvements in overall understanding of nucleation, adsorption, crystal growth, materials synthesis, and molecular engineering.