Nature's Rotary Molecular Dynamos: A Systematic Modeling Framework

大自然的旋转分子发电机：系统建模框架

• 批准号: 1715823
• 负责人: Daniel Zuckerman
• 金额: $ 75万
• 依托单位: Oregon Health & Science University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-07-01 至 2022-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1715823&HistoricalAwards=false
• 关键词: Nature; Rotary; Molecular; Dynamos; Systematic

The workings of every biological cell are carried out by "molecular machines" made up of proteins, RNA or combinations of these. This project will investigate how such machines function using physics-based computational methods. The project's focus will be the "rotary ATPases", which can convert one type of chemical energy into another - from a transmembrane pH difference into ATP, the well-known "molecular fuel" of the cell. The project will develop mathematical models of the machines in order to: (i) understand the biophysics of how these machines function (and malfunction) over a wide range of conditions encountered by the cell; and (ii) develop more powerful modeling approaches that are transferable to the study of other machines. The project will also continue development of an online textbook covering the biophysics of the cell's molecular machines.The work will enhance physics-based strategies for modeling molecular machines. Novel elements include systematic exploration of alternative mechanisms, evolution-motivated constrained optimization in place of parameter fitting, examination of reversibility, and consideration of a wide range of conditions and stoichiometries. Biologically, the work can provide optimal and limiting ranges for many uncertain parameters, and explicitly disentangle adaptations in the wide range of species-specific stoichiometries and organelle-specific directionality (synthesis vs. pumping). The consideration of alternative and hypothetical mechanisms could also contribute to understanding the evolutionary history of ATP synthesis, prior to the advent of the rotary synthase, as well as aiding the study of other families of molecular machines. The project will also lead to further development of a free online cell biophysics book (PhysicalLensOnTheCell.org), expanding the topics covered and adding interactive numerical models, based in part on the research to be performed.

每个生物细胞的工作都是由蛋白质、RNA或它们的组合组成的“分子机器”进行的。这个项目将研究如何使用基于物理的计算方法，这些机器的功能。 该项目的重点将是“旋转ATP酶”，它可以将一种类型的化学能转化为另一种-从跨膜pH值差异转化为ATP，即众所周知的细胞“分子燃料”。 该项目将开发机器的数学模型，以便：（i）了解这些机器在细胞遇到的各种条件下如何运作（和故障）的生物物理学;（ii）开发更强大的建模方法，可转移到其他机器的研究中。 该项目还将继续开发一本涵盖细胞分子机器生物物理学的在线教科书，这项工作将增强基于物理学的分子机器建模策略。新的元素包括系统的探索替代机制，进化动机的约束优化代替参数拟合，可逆性的检查，并考虑到广泛的条件和化学计量。在生物学上，这项工作可以为许多不确定的参数提供最佳和限制范围，并明确地在广泛的物种特异性化学计量和细胞器特异性方向性（合成与泵）中解开适应。考虑替代和假设的机制也有助于理解ATP合成的进化历史，在旋转合成酶出现之前，以及帮助研究其他家族的分子机器。 该项目还将导致进一步开发一本免费的在线细胞生物物理学书籍（PhysicalLensOnTheCell.org），扩大所涵盖的主题，并增加互动式数值模型，部分基于将要进行的研究。

项目成果

A kinetic mechanism for enhanced selectivity of membrane transport

• DOI: 10.1371/journal.pcbi.1007789
• 发表时间: 2020-07-01
• 期刊: PLOS COMPUTATIONAL BIOLOGY
• 影响因子: 4.3
• 作者: Bisignano, Paola;Lee, Michael A.;Rosenberg, John M.
• 通讯作者: Rosenberg, John M.

Should Virus Capsids Assemble Perfectly? Theory and Observation of Defects

病毒衣壳应该完美组装吗？

• DOI: 10.1016/j.bpj.2020.09.021
• 发表时间: 2020
• 期刊: Biophysical Journal
• 影响因子: 3.4
• 作者: Spiriti, Justin;Conway, James F.;Zuckerman, Daniel M.
• 通讯作者: Zuckerman, Daniel M.

High-throughput, single-particle tracking reveals nested membrane domains that dictate KRasG12D diffusion and trafficking

• DOI: 10.7554/elife.46393
• 发表时间: 2019-11-01
• 期刊: ELIFE
• 影响因子: 7.7
• 作者: Lee, Yerim;Phelps, Carey;Nan, Xiaolin
• 通讯作者: Nan, Xiaolin

Connexin 46 and connexin 50 gap junction channel properties are shaped by structural and dynamic features of their N-terminal domains.

• DOI: 10.1113/jp281339
• 发表时间: 2021-07
• 期刊: The Journal of physiology
• 作者: Yue B;Haddad BG;Khan U;Chen H;Atalla M;Zhang Z;Zuckerman DM;Reichow SL;Bai D
• 通讯作者: Bai D

Key biology you should have learned in physics class: Using ideal-gas mixtures to understand biomolecular machines

您应该在物理课上学习的关键生物学：使用理想气体混合物来理解生物分子机器

• DOI: 10.1119/10.0000634
• 发表时间: 2020
• 期刊: American Journal of Physics
• 影响因子: 0.9
• 作者: Zuckerman, Daniel M.