Quantitative Exploration of Molecular Machine Mechanisms

该项目将研究执行生物细胞关键任务的纳米级“分子机器”，从输入营养物质到调节隔室pH值水平再到合成生物分子;此外，一些教育工作将伴随着研究。 分子机器由于其在细胞生物学中的重要性而受到了严格的科学审查，但它们的复杂功能一直难以定量描述。 该项目将使用尖端的计算和数据分析方法，在量化方面取得关键进展。 计算分析也将用于设计进一步的实验，以完善这些关键系统的知识。 教育工作将补充研究包括开发一个在线定量生物物理学课程，开发其他几个在线教育资源，并与来自经济困难背景的高中生进行外展计划。更详细地说，研究项目将追求什么可以被称为分子机器的系统生物学方法，试图利用先进的计算来研究大量的机械可能性。 机器可以执行不止一种功能，这一点已经得到了很好的证实，我们假设，当定量分析时，微观过程的基本序列将被证明是异质的。 将开发一个贝叶斯推理（BI）管道，从实验数据中推断定量模型，该研究将尝试改进BI，以解决具有约10个参数的重要问题。 研究的主要系统是交替进入转运体（alternating-access transporters）和旋转ATP酶（rotary ATP ases），前者利用离子梯度为小分子转运提供动力，后者完成激活ATP分子的关键最后一步，并利用ATP衍生的自由能泵送离子。该奖项反映了NSF的法定使命，通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

The project will investigate the nanoscale ‘molecular machines’ that perform key tasks of biological cells, from importing nutrients to regulating compartment pH levels to synthesizing biomolecules; moreover, a number of educational efforts will accompany the research. Molecular machines have received intensive scientific scrutiny because of their importance in cell biology, but their complex functions have been difficult to characterize in a quantitative way. This project will use cutting-edge computational and data-analysis methods to make key strides toward quantification. The computational analysis will also be used to design further experiments to refine knowledge of these critical systems. Educational efforts that will supplement the research include developing an online quantitative biophysics course, developing several other online educational resources, and conducting an outreach program with high school students from economically disadvantaged backgrounds.In further detail, the research project will pursue what can be termed a systems biology approach to molecular machines, attempting to investigate a large set of mechanistic possibilities using advanced computations. It is already well-established that machines may perform more than one function, and we hypothesize that the underlying sequences of microscopic processes will prove to be heterogeneous when analyzed quantitatively. A Bayesian inference (BI) pipeline will be developed to infer quantitative models from experimental data, and the research will attempt to improve upon BI for the important class of problems with ~10 parameters. The main systems to be studied are alternating-access transporters, which use ion gradients to power small-molecule transport, and rotary ATPases, which perform the key final step in activating ATP molecules and also use ATP-derived free energy to pump ions.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.