Understanding pH-Dependent Protein Behavior Using Advanced Continuum Theory

描述（由申请人提供）：许多医疗条件，包括心脏病，可能导致某些组织的血流损失，这可能会损害细胞维持内部氢离子（质子）适当浓度的能力。这种微观故障可能导致心力衰竭，中风和死亡，因此了解质子浓度（以pH值测量的量）如何影响细胞中不同蛋白质的行为至关重要。pH值在人类生活中的重要性的一个很好的例子可以在蛋白质血红蛋白中找到，它通过血液携带氧气。肌肉运动的化学副产品（例如，在运动期间）是肌肉附近的pH值降低，这导致血红蛋白在需要的地方释放更多的氧气。我们有一个新的理论，预测蛋白质功能如何依赖于pH，初步结果表明，新理论可能是蛋白质pH依赖性的准确模型。相比之下，许多现有的模型表现出无法解释的弱点，尽管进行了大量的研究，但这些弱点仍未得到解决。在这个项目中，我们将测试新理论对蛋白质的实验研究非常详细，并比较新理论的预测与现有模型。这种新方法被称为非定域静电学，它是多尺度模型的一个例子，因为它捕捉了在非常小的长度尺度（例如，水分子的大小）以及在更大的长度尺度（大蛋白质的大小）上重要的物理学。尽管物理学家们知道这个多尺度理论已经有将近40年的时间了，但在生物学意义的问题上测试这个理论的困难使它直到几年前才得到应用。即使在那时，计算机速度和内存限制也阻止了对大分子的研究;研究人员最近开发了一种快速计算机模拟器，这使得所提出的蛋白质模拟首次可行。调查员已经进行了初步研究 这表明新理论有望解释蛋白质物理学中几个重要而尚未解决的问题，包括pH依赖性;在这里，我们将研究实际的蛋白质，放弃前期工作中的简化。我们的第一个目标是回答几个基本问题的新的非局部静电模型，以及它的关系，众所周知的理论。非定域理论是否对所有分子都更准确，或者是否存在某些特殊类型的分子形状，而非定域理论并不更准确？为了解决这些问题，我们必须进行系统的计算，使用我们在早期工作中开发的新的比较策略。除了教我们关于新的非局部理论，这些计算也将提供新的见解流行的现有的。这项工作的第二个目的是计算实际的pH值依赖性的真实的蛋白质，专注于那些最实验数据是可用的。为了确保科学的可重复性并推进pH模拟领域的发展，我们的计算机软件将作为开源软件发布，数据文件将通过互联网免费共享。 公共卫生相关性：许多疾病损害我们的细胞维持内部氢离子正确浓度的能力。由于这种微观失效可能导致心力衰竭或中风，因此了解这种氢浓度（称为pH值）如何影响蛋白质行为至关重要。在这个项目中，我们将测试一个新的pH依赖性蛋白质功能的理论，这似乎是显着优于现有的理论。

DESCRIPTION (provided by applicant): Many medical conditions, including heart disease, can lead to a loss of blood flow to certain tissues, which can impair the cells' ability to maintai an appropriate concentration of hydrogen ions (protons) inside. This microscopic failure can cascade towards heart failure, stroke, and death, making it crucial to understand how proton concentration (a quantity measured in pH) affects the behavior of different proteins in the cell. An excellent example of pH's importance in human life may be found in the protein hemoglobin, which carries oxygen through the blood. The chemical byproduct of muscle exertion (for example, during exercise) is a lowered pH near the muscle, which causes hemoglobin to release more of its oxygen just where it is needed. We have a new theory that predicts how protein function depends on pH, and initial results suggest that the new theory may be an accurate model of pH dependence of proteins. In contrast, many existing models exhibit unexplained weaknesses that have not been resolved despite intense research. In this project, we will test the new theory on proteins that have been experimentally studied in great detail, and compare the new theory's predictions to those from existing models. The new approach, called nonlocal electrostatics, is an example of a multiscale model because it captures physics that are important at very small length scales (say, the size of a water molecule) as well as those that are important at much larger length scales (the size of a large protein). Although this multiscale theory has been known by physicists for almost forty years, the difficulties of testing the theory on biologically meaningful problems kept it from being applied until just a few years ago. Even then, computer speed and memory limitations prevented the study of large molecules; the investigator has recently developed a fast computer simulator, which makes the proposed protein simulations feasible for the first time. The investigator has conducted a preliminary study that suggested the new theory holds the promise of explaining several important and unresolved questions in protein physics, including pH dependence; here, we will study actual proteins, abandoning the simplifications in the preliminary work. Our first aim is to answer several fundamental questions about the new nonlocal electrostatic model, and its relationship to well known theories. Is nonlocal theory more accurate for all molecules, or are there special types of molecular shapes where it is not better? To address these questions, we must conduct systematic calculations, using a new strategy for comparison that we have developed in earlier work. In addition to teaching us about the new nonlocal theory, these calculations will also provide new insights into the popular existing ones. The second aim of this work is to compute actual pH-dependent properties of real proteins, focusing on those for which the most experimental data is available. To ensure scientific reproducibility and advance the field of pH simulations, our computer software will be released as open-source software and data files will be shared freely via the internet. PUBLIC HEALTH RELEVANCE: Many diseases impair our cells' ability to maintain the right concentration of hydrogen ions inside. Because this microscopic failure can cascade towards heart failure or stroke, it is crucial to understand how this hydrogen concentration, a quantity known as pH, can affect protein behavior. In this project, we will test a new theory of pH-dependent protein function, which seems to be significantly better than existing theories.