A systems biology analysis of eukaryotic G protein-mediated signalling

细胞不能孤立地生活；它们需要来自环境的信号，或者需要邻居来控制它们行为的各个方面。这些信号告诉细胞是否应该生长、繁殖(分裂)或甚至死亡。细胞接收许多不同类型的信号，需要解释(理解)这些信号并做出正确的反应。对于哺乳动物细胞来说，这些反应可能会影响心脏、肺和肾脏等重要器官的许多关键过程。这些信号的错误或误解导致了癌症、自身免疫、心脏缺陷、精神分裂症和糖尿病等疾病。因此，如果我们能够对这些信号网络进行科学研究，我们可能能够理解并控制这些疾病的基础。为了实现这些目标，需要对激活和终止这些信号的细胞成分有一个隐含的了解。最近，利用基因技术的基础科学研究为我们的理解提供了许多重要的进步，然而，很明显，为了进一步了解我们的知识，我们需要了解信号通路的大型网络结构。多年来，物理学家们一直很欣赏使用复杂的数学技术来揭示迄今未知粒子在宇宙的产生和持续存在中所做的贡献。最近，生物学家开始利用数学家来帮助他们理解信号网络的组成。这项研究方案中描述的工作旨在将生物学研究与数学模拟相结合，探索酵母(其基因组已完全测序，并可在实验室中轻松操作的生物体)中与人类细胞中发现的高度相似的信号网络。研究中的信号网络是由一个分子与细胞表面发现的G蛋白偶联受体(GPCR)结合而开始的。GPCRs是人类细胞中最大的蛋白质家族之一，这些受体和相关信号网络中的缺陷导致了一系列疾病。到目前为止，在西方世界销售的所有药物中，约有50%针对GPCRs。G蛋白信号转导调节蛋白(RGS)家族控制着流经GPCR信号网络的信号量。人们一直认为RGS蛋白通过减少信号级联中活性蛋白的浓度来“关闭”信号传递。这是通过化学反应从被称为GTP的分子中去除一个磷酸基团来实现的。然而，最近的数据表明，在高刺激条件下，这种反应可能是细胞达到最大反应所必需的。因此，RGS蛋白可能扮演着一个二元开关的角色，从而根据刺激水平的不同，GPCR信号要么关闭，要么开启。这一假设的核心是我们认为G蛋白存在一种状态，尽管它具有作为活性分子的特征，但实际上是不活性的。这项研究的目的是在分子水平上深入了解RGS蛋白是如何发挥这些双重作用的。我们将使用生物学调查来提供准确数量的细胞成分，从而能够产生一个计算模型，该模型将产生对酵母中GPCR信号网络的详细评价。通过使用数学技术，我们的目标是提供一个适用于所有生物体的G蛋白信号传递的一般机制。

Cells cannot live in isolation; they require signals from their environment, or neighbours to control all aspects of their behaviour. These signals inform the cell if it should grow, reproduce (divide) or even die. Cells receive many differing types of signal and are required to interpret (understand) these and to respond correctly. For mammalian cells, these responses may influence many critical processes within essential organs e.g. heart, lungs and kidneys. Errors or misinterpretation of these signals are responsible for diseases such as cancer, autoimmunity, cardiac defects, schizophrenia and diabetes. It therefore follows that, if we can perform scientific research on these signalling networks, we may be able to understand, and thereby control, the basis of these diseases. To achieve such aims requires an implicit understanding of the cellular components that contribute to activating, and terminating these signals. In recent times, basic scientific investigations utilising genetic techniques has provided many important advances in our understanding, however it is becoming apparent that to further our knowledge we are required to appreciate the large network architecture of the signalling pathways. For many years physicists have had an appreciation of the use of complex mathematical techniques to inform the contribution that hither-to unknown particles perform in the production and continued existence of the Universe. In recent times, biologists have begun to utilise mathematicians to aid in their understanding of signalling network composition. The work described in this research proposal aims to combine biological investigation with mathematical simulation, to probe a signalling network within yeast (an organism whose genome has been fully sequenced, and is easily manipulated in the laboratory) that has high similarity to that found in human cells. The signalling network under investigation is initiated by the binding of a molecule to a G protein-coupled receptor (GPCR) found on the surface of cells. GPCRs are one of the largest families of proteins in human cells and defects within these receptors and associated-signalling networks, are responsible for a range of diseases. To date approximately 50% of all drugs sold in the Western world target GPCRs. The family of regulator of G protein signalling (RGS) proteins control the amount of signalling that flows through a GPCR signal network. It has always been understood that RGS proteins 'switch-off' signalling, by reducing the concentration of active proteins in the signalling cascade. This occurs by a chemical reaction that removes a phosphate group from a molecule called GTP. However, recent data suggests that this reaction may, under conditions of high stimulation, be required for cells to achieve their maximal response. Thus the RGS protein may be acting as a binary switch such that GPCR signalling is either off or on, depending upon the level of stimulation. Central to this hypothesis is our suggestion that a state for the G protein exists that although it has the characteristics of being an active molecule is, in fact, inactive. The research in this proposal is intended at providing an in depth understanding, at the molecular level, of how RGS proteins perform these dual roles. We will use biological investigation to provide exact amounts of cellular components so enabling the production of a computational model which will generate a detailed appreciation of GPCR signalling networks in yeast. By using mathematical techniques we aim to provide a general mechanism of G protein signalling applicable to all organisms.