CAREER: Development and Application of Multi-scale Modeling for Biomolecular Association

职业：生物分子关联多尺度模型的开发和应用

• 批准号: 1350401
• 负责人: Chia-en Chang
• 金额: $ 58.84万
• 依托单位: University of California-Riverside
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-05-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1350401&HistoricalAwards=false
• 关键词: CAREER; Development; Application; Multi; scale

The objective of this project is to investigate complex interactions among molecules, including proteins, enzymes and nanoparticles using computer modeling. Understanding association processes will increase fundamental understanding of protein-ligand binding and its applications. Along with binding, molecule's kinetic behavior - how they move - also plays a crucial role in understanding how rapidly they interact, undergo change, and bind with one another. Traditional approaches in protein binding and enzymology typically focus on a final chemical-protein structure, instead of the kinetic and binding processes that precede that final stage. Yet, exploring binding processes deepens our understanding of how molecules recognize binding partners, and will guide molecular designs and engineering of enzymes for more efficient chemical catalysis. Simulations have provided powerful tools to study molecular associations. However, real molecular systems are quite complicated, and these tools are usually either very time consuming or tend to over-simplify a biological system. This project will combine multi-level coarse-grained and atomistic simulations to efficiently and accurately model molecular associations and kinetic enhancement of the enzymes and nanoparticle systems. Reliable and efficient molecular simulations play an ever-increasing role in studying binding kinetics. They provide unique insights into the mechanisms of biomolecular activity, an in the integration and interpretation of experiments. In addition, understanding binding kinetics contributes to the design of novel molecules and engineering enzymes and enzyme complexes for more efficient chemical activity. Successful completion of this research will improve understanding of protein-ligand binding kinetics and assist the design of nanostructures, nanoparticles and engineered enzymes.This project will train young scientists, including graduate, undergraduate, and high school students. Seminars and summer courses will be organized to train students from the local colleges, high schools and UC Riverside. The outreach program will broaden participation of underrepresented groups by supporting under-represented minority students in science. Summer courses and seminars will introduce the field of computational chemistry and provide hands-on help for students doing research in the PI's laboratory. The results of this project will be integrated into regular courses at UCR and in special courses/seminars. The methods developed in the project will deepen understanding of protein-ligand recognition and binding kinetics. These are important in molecular design; therefore, the work will have practical benefits in various areas such as chemistry, biology, engineering and environmental sciences.

该项目的目标是使用计算机建模研究分子之间复杂的相互作用，包括蛋白质、酶和纳米粒子。 了解关联过程将增加对蛋白质-配体结合及其应用的基本了解。除了结合之外，分子的动力学行为（它们如何移动）对于理解它们相互作用、发生变化和相互结合的速度也起着至关重要的作用。蛋白质结合和酶学的传统方法通常关注最终的化学蛋白质结构，而不是最后阶段之前的动力学和结合过程。然而，探索结合过程加深了我们对分子如何识别结合伙伴的理解，并将指导酶的分子设计和工程，以实现更有效的化学催化。模拟为研究分子关联提供了强大的工具。然而，真正的分子系统相当复杂，这些工具通常要么非常耗时，要么往往过于简化生物系统。该项目将结合多层次的粗粒度和原子模拟，以高效、准确地模拟酶和纳米粒子系统的分子关联和动力学增强。可靠且高效的分子模拟在研究结合动力学中发挥着越来越重要的作用。他们为生物分子活性机制以及实验的整合和解释提供了独特的见解。此外，了解结合动力学有助于设计新型分子以及工程酶和酶复合物，以获得更有效的化学活性。这项研究的成功完成将提高对蛋白质-配体结合动力学的理解，并协助纳米结构、纳米粒子和工程酶的设计。该项目将培训年轻科学家，包括研究生、本科生和高中生。 将组织研讨会和暑期课程来培训来自当地大学、高中和加州大学河滨分校的学生。该外展计划将通过支持科学领域代表性不足的少数族裔学生来扩大代表性不足群体的参与。 暑期课程和研讨会将介绍计算化学领域，并为在 PI 实验室进行研究的学生提供实践帮助。该项目的成果将被纳入加州大学河滨分校的常规课程和特殊课程/研讨会中。该项目开发的方法将加深对蛋白质配体识别和结合动力学的理解。这些对于分子设计很重要；因此，这项工作将在化学、生物学、工程和环境科学等各个领域产生实际效益。