Designing Unnatural-Amino-Acid-Enabled Second-Generation Biomaterials: Advanced Surfaces, Biocatalysts and Biotherapeutics - An Integrated Computational/Experimental Approach

非技术：蛋白质以一种或另一种形式参与维持生命的所有过程，可用于控制细胞功能（例如药物）或在细胞外用于赋予材料高级功能（例如识别细菌的探测器或在工业环境中催化反应）。在蛋白质在其天然环境外使用之前，必须采取措施稳定分子以防止降解。将蛋白质附着在固体底物上或在分子上添加聚合物链可以克服降解效应，但这些方法并不总是有效的，因为这种改变有许多不同的选择。本研究使用最新开发的计算模型和最先进的实验方法来识别和瞄准蛋白质上最稳定的位置。这些知识将被用于创建具有特定功能的生物材料的快速开发过程。成功实现这项研究的目标对社会的潜在好处是巨大的，并改善许多领域，包括可持续化学加工，国家竞争力，国防和医疗保健。在医疗领域的一个例子是改进和具有成本效益的处方药。许多新开发的药物都是以蛋白质为基础的，但它们的功效有限，因为它们在体内很快就会降解。在正确的位置将聚合物附着在蛋白质上（这将由本研究提供）将增加药物在体内停留的时间，并通过减少治疗所需的蛋白质量来降低医疗成本。另一个来自国防领域的例子是危险探测。对国土安全的许多潜在威胁来自武器化的化学品或生物制剂（如芥子气、炭疽、埃博拉等）。在保留功能的位置将蛋白质附着在固体基质上，为开发基于芯片的探测器铺平了道路，这种探测器可以放置在邮件处理中心、机场、体育场馆等脆弱区域，也可以缝到士兵的制服上。对社会的其他好处包括创建动手模块，在K-12教室教授生物材料，增加大一前活动的参与度。技术：将非天然氨基酸（UAAs）掺入蛋白质中，代替天然氨基酸，可用于将聚合物系在蛋白质上或将蛋白质附着在所需的任何位置的表面。挑战在于选择保留功能的正确位置，因为这种替代会破坏蛋白质的稳定，目前还没有方法来预测最终的行为。由于成本和时间的原因，组合方法在大多数情况下无法使用，因此本研究的目标是创建一种集成的计算和实验技术，以快速预测和验证用于新型生物材料的蛋白质上的最佳残基。这项工作将首先确定UAA结合对功能的影响，因为这一点尚未完全了解。一旦完成，将努力优化聚合物-蛋白质相互作用的稳定性，活性位点的可及性等。该项目的最后阶段将是通过优化蛋白质表面相互作用来生产生物催化剂和智能表面。完成计算工作的关键是通过开发uaa模型来建立PI在粗粒蛋白质建模方面的专业知识。该模型将参数化，并根据co-PI的新型UAA掺入和生物功能化方法（称为PRECISE （Protein残基显式共价固定化稳定性增强））产生的实验数据进行验证。这项工作将训练两名研究生和两至四名本科生在跨学科、实验/计算团队环境中使用最先进的技术正确应用科学方法。

Nontechnical:Proteins, in one form or another, are involved in all processes sustaining life and can be used to control cellular function (e.g. pharmaceuticals) or be used outside of cells to impart advanced function to materials (e.g. detectors to identify bacteria or catalyzing reactions in an industrial setting). Before using proteins outside of their native environment, steps must be taken to stabilize the molecule to prevent degradation. Attaching the protein to a solid substrate or adding polymer chains to the molecule can overcome degrading effects, but such methods are not always effective because of the many different options available for such alterations. This research uses recently-developed computational models together with state-of-the-art experimental methods to identify and target the most stabilizing locations on proteins. This knowledge will then be used to create a process for rapid development of biomaterials with specific function.The potential benefits to society of successfully achieving the goals of this research are huge and improve many fields including sustainable chemical processing, national competitiveness, defense, and medical care. An example in the medical field is improved and cost-effective prescription drugs. Many newly-developed pharmaceuticals are protein based, but their efficacy is limited because they are quickly degraded in the body. Attaching polymers to the proteins at the correct location (that would be provided by this research) would increase the time that the drug remains in the body and reduce healthcare costs by decreasing the amount of protein needed for a treatment. Another example from the defense field is hazard detection. Many potential threats to homeland security come from weaponized chemicals or biological agents (e.g. mustard, anthrax, ebola, etc.). Attaching proteins to solid substrates, at the location that preserves function, paves the way for the development of chip-based detectors that can be placed in vulnerable areas such as mail processing centers, airports, sports venues, etc. or could be sewed into the uniforms of soldiers. Other benefits to society include creating hands-on modules to teach biomaterials in K-12 classrooms and increased participation in pre-freshman activities. Technical:Incorporating unnatural amino acids (UAAs) into proteins, in place of their natural counterparts, can be used to tether polymers to proteins or attach the protein to a surface at any location desired. The challenge is to select the correct location that preserves function because such substitution can destabilize the protein and no method currently exists to predict the ultimate behavior. A combinatorial approach cannot be used in most instances due to costs and time, so the objective of this research is to create an integrated computational and experimental technology that rapidly predicts and validates the optimal residues on a protein to be used in a novel biomaterial. The work will proceed by first determining the effects of UAA incorporation on function because such is not fully understood. Once this is accomplished, efforts will be done to optimize polymer-protein interactions for stability, active site accessibility, etc. The final stage of the project will be to produce biocatalysts and smart surfaces by optimizing protein-surface interactions. The key to accomplishing the computational work is to build on the PI's expertise in coarse-grain protein modelling by developing such a model for UAAs. This model will be parameterized and validated against experimental data produced with the co-PI's novel method of UAA incorporation and biofunctionalization called PRECISE (Protein Residue-Explicit Covalent Immobilization for Stability Enhancement). This work will train two graduate students and two to four undergraduate students on proper application of the scientific method using state-of-the-art techniques in an interdisciplinary, experimental/computational team environment.