| 项目编号: | 1703438
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| 项目名称: | Combined molecular simulation and experimental study to discover, predict and control enzyme immobilization in polymeric nanoparticles |
| 作者: | W. James Pfaendtner
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| 承担单位: | University of Washington
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| 批准年: | 2017
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| 开始日期: | 2017-09-01
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| 结束日期: | 2020-08-31
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| 资助金额: | 331264
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| 资助来源: | US-NSF
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| 项目类别: | Standard Grant
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| 国家: | US
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| 语种: | 英语
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| 特色学科分类: | Engineering - Chemical, Bioengineering, Environmental, and Transport Systems
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| 英文关键词: | enzyme
; study enzyme loading
; polymer nanoparticle
; enzyme robustness
; successful enzyme encapsulation
; enzyme/polymer interaction
; enzyme/polymer system
; molecular scale simulation
; enzyme activity
; enzyme/polymer interface
; fast molecular dynamics simulation
; computer simulation
; combined study
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| 英文摘要: | Enzymes, protein-based biological catalysts, have enormous potential to revolutionize the way we transform chemicals to useful products, treat disease, or detoxify environmental contaminants. However, the use of enzymes in practice is limited by their tendency to lose their activity through a variety of mechanisms. One common strategy to improve enzyme robustness is to immobilize and encapsulate it in a polymer, a large molecule composed of many repeated subunits. This strategy holds great promise, but the polymer properties, encapsulation technique, and enzyme/polymer interactions all play important roles in determining the success of a particular encapsulation strategy. This research project aims to compare and contrast computer simulations with experimental results to help develop an efficient means of predicting beneficial encapsulation strategies. Working with students through the UW College of Engineering Math Academy, the researchers are providing many opportunities for enriching the training of graduate students, improving education, and engaging undergraduates from a local community college (Bellevue College) in research.
To date, successful enzyme encapsulations have been discovered largely via extensive trial and error experimentation and serendipity. This project, a combined study of molecular scale simulations and experimental measurement of enzyme activity and release in various matrices, seeks to build a rational design framework to discover, predict, and control the essential governing driving forces at the enzyme/polymer interface. Specifically, this project is demonstrating a comprehensive strategy, using fast molecular dynamics simulations paired with statistical machine learning, to identify sequence level descriptors of strong and weak binding of enzymes encapsulated in polymer nanoparticles. Complementary experiments are being performed that study enzyme loading, release and activity under a wide range of conditions. The ability to rationally design such interactions would be a transformative advance that could be applied to hydrogels, inorganic surfaces, or other types of enzyme/polymer systems. The strong interplay between the experiments and simulations will ensure that the results are accurate and potentially help to identify areas of improvement for molecular dynamics force fields and high throughput experimental design. |
| 资源类型: | 项目
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| 标识符: | http://119.78.100.158/handle/2HF3EXSE/89023
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| Appears in Collections: | 全球变化的国际研究计划
科学计划与规划
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| Recommended Citation: | |
W. James Pfaendtner. Combined molecular simulation and experimental study to discover, predict and control enzyme immobilization in polymeric nanoparticles. 2017-01-01.
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