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Cellular crowding effects on biomolecular stability and dynamics

细胞拥挤对生物分子稳定性和动力学的影响

基本信息

批准号：
1817307
负责人：
Michael Feig
金额：
$ 70万
依托单位：
Michigan State University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2018
资助国家：
美国
起止时间：
2018-08-01 至 2022-07-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1817307&HistoricalAwards=false
关键词：
Cellular crowding effects biomolecular stability

项目摘要

The research will connect the highly detailed atomistic views of the interior of biological cells with their overall functional behavior. The ultimate outcome is a model of biological cells based on basic physical principles that can be queried to gain a comprehensive understanding of biological processes across a wide range of scales. The research at interdisciplinary boundaries between physics, chemistry, and biochemistry and between simulation, modeling, and experiment provides unique opportunities for training future generations of scientists. The involvement of undergraduate students is a central theme. Teams of undergraduate students from different disciplines will come together under co-mentorship by a graduate student and postdoctoral researcher to begin first research experiences with a strong interdisciplinary perspective. The involvement of women and underrepresented minorities is a major focus.Cellular environments consist of dense, heterogeneous solutions of biomolecules where interactions are unavoidable yet molecules have to remain fluid and in their native states to carry out biological function. Computer simulations are combined with spectroscopic experiments to characterize the effects of crowding on biomolecular dynamics, stability, and diffusive properties. Dense protein solutions are studied along with systems involving membranes, chromosomal DNA structures, and metabolites. The focus of this project is on characterizing the transient interactions that occur under such conditions and how they affect biomolecular behavior. That insight will allow the construction of predictive models that can relate protein chemistry to dynamic and diffusive behavior, and ultimately biological function, under in vivo conditions.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.

这项研究将把生物细胞内部的高度详细的原子论观点与它们的整体功能行为联系起来。最终结果是一个基于基本物理原理的生物细胞模型，可以对其进行查询，以获得对广泛范围内的生物过程的全面理解。物理、化学和生物化学之间以及模拟、建模和实验之间的跨学科边界的研究为培养未来一代科学家提供了独特的机会。本科生的参与是一个中心主题。来自不同学科的本科生团队将在研究生和博士后研究员的共同指导下聚集在一起，以强烈的跨学科视角开始第一次研究体验。妇女和代表性不足的少数群体的参与是一个主要焦点。细胞环境由密集的、不同种类的生物分子溶液组成，其中相互作用是不可避免的，但分子必须保持流体和天然状态才能发挥生物功能。计算机模拟与光谱实验相结合，以表征拥挤对生物分子动力学、稳定性和扩散特性的影响。致密的蛋白质溶液与涉及膜、染色体DNA结构和代谢物的系统一起被研究。这个项目的重点是描述在这种条件下发生的瞬时相互作用以及它们如何影响生物分子的行为。这一洞察力将允许构建预测模型，该模型可以将蛋白质化学与体内条件下的动态和扩散行为，并最终与生物功能联系起来。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

期刊论文数量（13）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Physics at the Molecular and Cellular Level (P@MCL): A New Curriculum for Introductory Physics

分子和细胞水平的物理学（P@MCL）：物理学入门新课程

DOI：
10.35459/tbp.2019.000138
发表时间：
2020
期刊：
The Biophysicist
影响因子：
0
作者：
Lapidus, Lisa J.
通讯作者：
Lapidus, Lisa J.

The effect of polymer length in liquid-liquid phase separation

DOI：
10.1016/j.xcrp.2023.101415
发表时间：
2023-05
期刊：
Cell reports. Physical science
影响因子：
0
作者：
Gilberto Valdés-García;Kasun Gamage;Casey R. Smith;K. Martirosova;M. Feig;Lisa J. Lapidus
通讯作者：
Gilberto Valdés-García;Kasun Gamage;Casey R. Smith;K. Martirosova;M. Feig;Lisa J. Lapidus

The road less traveled in protein folding: evidence for multiple pathways

蛋白质折叠中少有人走的路：多种途径的证据

DOI：
10.1016/j.sbi.2020.10.012
发表时间：
2021
期刊：
Current Opinion in Structural Biology
影响因子：
6.8
作者：
Lapidus, Lisa J
通讯作者：
Lapidus, Lisa J

Clustering and dynamics of crowded proteins near membranes and their influence on membrane bending

DOI：
10.1073/pnas.1910771116
发表时间：
2019-12-03
期刊：
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
影响因子：
11.1
作者：
Nawrocki, Grzegorz;Im, Wonpil;Feig, Michael
通讯作者：
Feig, Michael

Modeling Concentration-dependent Phase Separation Processes Involving Peptides and RNA via Residue-Based Coarse-Graining

通过基于残基的粗粒度对涉及肽和 RNA 的浓度依赖性相分离过程进行建模