Probing the rules governing domain formation and protein partitioning in membrane

波士顿大学的John E. Straub教授获得了化学学部化学理论、模型和计算方法（CTMC）项目的奖励，对脂质膜结构的预测进行了理论和计算研究。脂质膜在细胞的组织和功能中起着关键作用。脂质膜的系统研究对于我们理解细胞功能的基本方面是必不可少的，包括细胞运输和信号传导。目前，最先进的计算模型无法捕捉膜结构和功能的关键方面。Straub小组正在开发膜和膜蛋白的新理论模型，以期在细胞的计算建模中达到一个新的现实水平。因此，这些方法的成功开发及其应用可能会对该领域产生革命性的影响。该项目包括对本科生和研究生的培训和指导，以及模拟方法、代码和数据集的开发。一本关于“化学家的数学方法”的完整教科书正在编写中，将免费提供给教师和学生。分析多组分蛋白质混合物在非均质膜表面结构中与脂质结构域的分配是极具挑战性的。为了与实验直接比较，需要进行全原子模拟，因此自由能计算采用伞形采样和能量表示方法来提高速度和精度，在二面体空间和自由体积空间模拟回火来提高构象采样。多组分混合物是复杂的，含有胆固醇、鞘脂、糖脂和其他对确定脂相结构域很重要的试剂。本研究的目的是使膜结构域形成和膜蛋白分配的首次从头研究使用原子模型。这些模型是针对膜混合物中纳米级膜结构和脂质结构域之间蛋白质分配的平均实验测量进行验证的。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Professor John E. Straub at Boston University is supported by an award from the Chemical Theory, Models and Computational Methods (CTMC) Program in the Chemistry Division to perform theoretical and computational research on predictions of the structure of the lipid membrane. The lipid membrane plays a key role in the organization and function of the cell. The systematic investigation of lipid membranes is essential to our understanding of fundamental aspects of cellular function, including cellular transport and signaling. At the present time, state-of-the-art computational models fail to capture key aspects of membrane structure and function. The Straub group is developing novel theoretical models of membrane and membrane proteins that aspire to a new level of realism in the computational modeling of the cell. As such, the successful development of the methods and their applications may be transformative to the field. This project includes the training and mentoring of undergraduate and graduate research students as well as the development of simulation methods, codes, and datasets. A complete textbook on the topic "Mathematical Methods for Chemists" is being developed that will be made freely available to instructors and students.The program of analyzing multi-component protein mixtures partitioning with lipid domains in heterogeneous membrane surface structure is extremely challenging. For direct comparison with experiment, it is necessary to perform all-atom simulations, so the free energy calculations use Umbrella Sampling and Energy Representation methods for speed and accuracy and Simulated Tempering in dihedral space and free volume space for enhanced conformational sampling. The multi-component mixtures are complex, containing cholesterol, sphingolipids, glycolipids and other agents important in determining lipid phase domains. The goal of this research is to enable the first de novo studies of membrane domain formation and membrane protein partitioning using atomistic models. The models are validated against average experimental measurements of nanoscopic membrane structures in membrane mixtures and protein partitioning between lipid domains.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.