Investigating Ionotropic Glutamate Receptor Interfaces as Novel Drug Targets.

现代医学的一个关键目标是开发更好的治疗方法来治疗与大脑相关的疾病和状况。这是医学上最具挑战性的目标之一，部分受制于大脑本身的复杂性。另一个主要绊脚石是开发没有严重副作用的新药的问题，这个问题经常被认为是患者停止服用处方的原因之一。神经信号在身体和大脑中的传递依赖于被称为受体的蛋白质。这种控制记忆和学习的神经传递大部分是由离子型谷氨酸受体控制的，所谓的谷氨酸受体，是因为当谷氨酸(神经递质)结合时，它们会打开一个孔，穿过神经元膜，允许带正电荷的离子(钠和钾)通过它。这是大脑中神经信号的基础。因此，从癫痫到阿尔茨海默病，谷氨酸受体与中枢神经系统(CNS)的许多神经系统疾病有关，这或许并不令人惊讶。谷氨酸受体有许多不同的亚型，似乎这些受体的某些亚型在不同的神经条件下受到不同程度的影响。因此，为了避免不必要的副作用，作用于这些受体的药物应该尽可能具体。问题是，它们都与相同的神经递质谷氨酸结合，因此这实际上是相当困难的。亚型之间的差异在远离谷氨酸结合部位的地方表现出来，并在受体展示的一些属性方面明显。例如，它们打开的速度有多快，关闭的时间有多长，可以由远离结合部位的受体区域控制。这些区域有时被称为变构位点，因为它们没有受到与主要(正构)结合位点相同的进化压力，因此提供了一条获得更高特异性的潜在途径。换句话说，我们从这些位点的化合物中获得更高特异性的机会应该比在谷氨酸结合位点的机会大得多。在我们之前的工作中，我们能够展示，对于一个称为海人酸受体的特定受体家族，远离谷氨酸结合位点的区域如何控制受体的动态特性。特别是，这个区域包含不同的钠离子和氯离子结合部位。在这项提案中，我们不仅想进一步探索这一方面，而且还想调查副作用较少的新药是否有可能针对该地区。通过以这种方式进行靶向治疗，我们希望能够开发出治疗癫痫和神经病理性疼痛的新的改进疗法。我们的建议利用分子模拟的能力来提供原子水平的细节，说明是什么控制了这个结合位点的行为方式。如果我们想要有任何机会开发出以可预测的方式发挥作用的化合物，就有必要充分了解这一点。我们将产生的结果将由我们在加拿大麦吉尔大学的合作者进行验证和测试。

A key goal of modern medicine is to develop better therapeutic approaches for the treatment of diseases and conditions associated with the brain. This is one of the most challenging goals of medicinal science, hampered in part by the complexity of the brain itself. Another major stumbling block is the problem of developing new drugs that do not have severe side-effects, an issue often cited as one of the reasons why patients stop taking their prescriptions. The transmission of nerve signals in the body and brain is dependent on proteins called receptors. Most of this neurotransmission that governs memory and learning is controlled by ionotropic glutamate receptors, so-called, because upon binding of glutamate (the neurotransmitter) they open a pore that passes through the membrane of the neuron and allows positively charged ions (sodium and potassium) to pass through it. This is the basis of nerve signals in the brain. It is therefore perhaps unsurprising that glutamate receptors have been implicated in many neurological conditions of the central nervous system (CNS) ranging from epilepsy to Alzheimer's disease. There are many different subtypes of glutamate receptors and it appears that certain subtypes of these receptors are implicated to different extents in different neurological conditions. Therefore, to avoid unwanted side-effects, drugs that act at these receptors should be as specific as possible. The problem is that they all bind the same neurotransmitter, glutamate, and therefore this is actually quite difficult. The differences between the subtypes manifest themselves away from the glutamate-binding site, and is apparent in terms of some of the properties the receptors exhibit. For example, how quickly they open or how long it takes for them to close, can be controlled by regions of the receptor away from the binding site. These regions are sometime referred to as allosteric sites and because they have not been subjected to the same evolutionary pressure as the main (orthosteric) binding site offer a potential route to greater specificity. In other words, our chances of obtaining greater specificity with compounds at these sites should be much greater than at the glutamate-binding site.In our previous work, we were able to show how, for one particular sub-family of receptors called kainate receptors, a region away from the glutamate-binding site could control the dynamic properties of the receptor. In particular, this region contains separate binding sites for sodium and chloride ions. In this proposal we'd like to not only explore this aspect further, but also to investigate the possibility that new drugs with fewer side-effects can be targeted to this region. By targeting in this way, we are hopeful that we can develop new improved therapies for the treatment of epilepsy and neuropathic pain. Our proposal utilizes the power of molecular simulations to provide atomic-level detail of what controls the way this binding site behaves. A full understanding of this is necessary if we are to have any chance of developing compounds that act in a predictable way. The results we will generate will be verified and tested by our collaborators in McGill University in Canada.