Quantifying the effects of ions and collective rearrangements during ribosome function

这个项目的重点是了解控制基因表达的分子因素。为此，将应用大规模模拟来研究核糖体如何准确和高效地合成蛋白质。蛋白质的生产对几乎所有的生物功能都是必不可少的，这使得核糖体成为最重要的生物机器之一。虽然现代实验可以解决核糖体的静态配置，但详细的模拟将使研究界了解分子结构如何实现特定的生物功能。这可以揭示控制细胞动力学的策略，并提供一本有助于设计新型分子规模机器的“规则手册”。该项目将包括一系列活动，将为高中生提供入门科学研讨会，为本科生和研究生研究人员提供宝贵的培训经验，并为实验研究人员提供讲习班。将开发和应用理论模型，以确定核糖体功能中局部的、“弥散的”离子的详细作用。表征延伸周期的几个关键子步骤(tRNA调节、杂化状态形成、移位和结构域旋转)将阐明离子环境如何塑造核糖体的能量格局。这将有助于揭示离子能够实现构象复杂的生物动力学的模式。由于RNA的高负电荷密度，核糖核蛋白组装的动力学严重依赖于局部扩散的离子环境，这可能导致带负电荷的RNA分子之间的吸引。因此，为了充分描述大规模生物组装的能量学，必须适当地描述离子环境的统计特性。为了应对这一挑战，将开发简化的能量模型，采用全原子分辨率，以及显式表示的单价和二价离子。能量参数的校准将通过与实验的比较和原型系统的显式溶剂模拟来建立。这些简化的模型将使核糖体中大规模(20-100埃)构象转变的模拟成为可能。这将牵涉到当地离子分布的波动/变化的影响。虽然这项研究将重点放在核糖体动力学上，但这些模型和计算方法将可以转移到广泛的生物组装上。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。

This project focuses on understanding the molecular factors that govern gene expression. To this end, large-scale simulations will be applied to study how the ribosome can accurately and efficiently synthesize proteins. The production of proteins is essential for nearly all biological functions, making the ribosome one of the most important biological machines. While modern experiments can resolve static configurations of the ribosome, detailed simulations will allow the research community to understand how molecular structure enables specific biological function. This can reveal strategies for controlling cellular dynamics, as well as provide a "rule book" that can aid in the design of novel molecular-scale machines. This project will involve a range of activities that will provide introductory science seminars for high school students, valuable training experiences for undergraduate and graduate student researcher and workshops for experimental researchers.Theoretical models will be developed and applied to identify the detailed role of localized, "diffuse" ions during ribosome function. Characterizing several critical substeps of the elongation cycle (tRNA accommodation, hybrid-state formation, translocation and domain rotations) will elucidate how the ionic environment shapes the energy landscape of the ribosome. This will help uncover the modes by which ions can enable conformationally-complex biological dynamics. With the high negative charge density of RNA, the dynamics of ribonucleoprotein assemblies rely critically on a locally diffuse ionic environment, which can lead to attraction between negatively charged RNA molecules. Accordingly, to fully characterize the energetics of large-scale biological assemblies, one must properly describe the statistical properties of the ionic environment. To address this challenge, simplified energetic models will be developed that employ all-atom resolution, as well as explicitly represented monovalent and divalent ions. Calibration of the energetic parameters will be established through comparison with experiments and explicit-solvent simulations of prototypical systems. These simplified models will then enable the simulation of large-scale (20-100 Angstroms) conformational transitions in the ribosome. This will implicate the influence of fluctuations/changes in local ionic distributions. While this study will focus on ribosome dynamics, the models and computational methods will be transferrable to a broad range of biological assemblies.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.