CAREER: Computational Investigation of Structural and Dynamical Mechanisms of Protein Regulation by Post-Translational Phosphorylation

这个项目的目标是开发一种基于物理的理论来预测由磷酸化引起的蛋白质构象变化。蛋白质翻译后磷酸化是一种普遍存在的细胞调控机制，在信号转导、转运和代谢等不同过程中发挥着核心作用。中心假设是，通过将磷酸电荷的引入视为对蛋白质能量格局的扰动，可以更好地理解和系统化对磷酸化的不同反应。所采用的计算方法从量子力学到带有隐式拯救模型的分子力学。从实用的角度来看，这项研究将产生一种计算机程序，该程序能够预测许多具有已知磷酸化位点但没有实验确定的磷酸化结构的蛋白质对磷酸化的原子水平反应。该职业奖将支持物理学、计算科学和生物学的交叉学科的研究和教学活动。该研究所正在开发一门新的跨学科研究生水平的课程和实习，重点是将物理化学和计算化学应用于生物学。实习将允许实践许多建模方法，包括在此拨款和之前的NSF支持下开发的软件。所有来自实践的例子，由教师和学生生成，都将在网上提供，创造了一个广泛可用的资源。研究部分还涉及来自代表性不足群体的科学家的直接参与，以及耶希瓦大学斯特恩女子学院本科生参与的协作。最后，PI开发的所有算法都将被封装在一个易于使用的软件包中，该软件包可免费用于所有学术目的。

The objective of this project is to develop a physics-based theory for predicting protein conformational change caused by phosphorylation. Protein post-translational phosphorylation is a ubiquitous mechanism for cellular regulation that plays a central role in such diverse processes as signal transduction, transport, and metabolism. The central hypothesis is that the diverse responses to phosphorylation can be better understood and systematized by viewing the introduction of the phosphate charge as a perturbation to the protein energy landscape. The computational methods employed range from quantum mechanics to molecular mechanics with implicit salvation models. From a practical perspective, this research will result in a computer program that is capable of predicting atomic-level response to phosphorylation for many proteins with known phosphorylation sites but no experimentally determined structure in the phosphorylated form. This CAREER award will support research and teaching activities that lie at the intersection of physics, computational science, and biology. The PI is developing a new interdisciplinary graduate-level course and practicum centered on the application of physical and computational chemistry to biology. The practicum will permit hands-on experience with many modeling methods, including software developed under this grant and prior NSF support. All examples from the practicum, generated by the instructor and students, will be made available on-line, creating a broadly available resource. The research component also involves the direct participation of scientists from the underrepresented groups, as well as a collaboration involving undergraduate students at the Stern College for Women, Yeshiva University. Finally, all algorithms developed by the PI will be encapsulated in an easy-to-use software package, which is available free-of-charge for all academic purposes.