Designing and synthesising new classes of phosphatase inhibitor using novel computational methods

磷酸酶负责去除磷酸基团，并与激酶（起相反作用）一起控制细胞中的许多信号网络。这种信号及其控制的生化过程的故障与一系列疾病有关，包括糖尿病、某些癌症和感染。尽管有这种重要的活性，新疗法的前景诱人，但磷酸酶通常被认为是不可药物的——也就是说，人们认为不可能获得既能阻断磷酸酶又具有药物所需的物理性质的分子。在这个项目中，您将应用新颖的计算技术来探索它们是否可以为能够实现这种平衡的新分子类型提供路线图。该项目将允许最令人兴奋的计算设计被合成，然后测试，这要感谢监督团队的丰富经验。该项目将首先探索一些具有治疗意义的磷酸酶的已知结构-活性关系。这将包括公共领域的数据，但也包括曼彻斯特的数据。同样的特性使得磷酸酶对药物发现者具有挑战性（调整为将带有长键的带多重电荷的阴离子基团与磷结合），使得计算研究具有挑战性，因此学生将花费一些时间探索可用的理论水平（使用量子力学计算）并考虑蛋白质的灵活性（使用分子动力学计算），以便推导出令人满意的模型。该模型及其推导过程中提供的见解将用于设计采用非共价和共价作用模式的新潜在抑制剂。然后用最好的建模方法进行计算。候选人不需要使用任何这些计算类型的经验，但了解他们的背景将是有益的。随后，学生将能够选择合成和测试一些最好的分子，或者通过计算探索更广泛的磷酸酶，以探索这类酶是否适用于一些最新的机器学习方法，从而推广量子力学/动力学计算。

Phosphatases are responsible for removing the phosphate groups and play a role in conjunction with kinases (that do the opposite) in controlling many signalling networks in cells. Malfunctioning of this signalling and the biochemical processes they control is associated with a range of diseases including diabetes, some cancers and infections. Despite this important activity, with tantalising prospects for new treatments, phosphatases are often viewed as undruggable - that is that it is thought impossible to obtain molecules that can block the phosphatase but also have the sort of physical properties that are required in a drug. In this project, you will apply novel computational techniques to probe whether they can provide a route map towards new molecule types that are able to achieve this balance. The project will allow the most exciting computational designs to be synthesised and then tested thanks to the breadth of experience of the supervisory team. The project will first explore the known structure-activity relationships for a number of phosphatases of therapeutic interest. This will include data in the public domain but also those measured in Manchester. The same features that make phosphatases challenging for drug discoverers (tuned to bind multiply-charged anionic groups with long bonds to phosphorous) make them challenging to study computationally and the student will therefore spend some time exploring the levels of theory available (using quantum mechanical calculations) and considering protein flexibility (using molecular dynamics calculations) in order to derive a satisfactory model. This model and the insights provided during its derivation will be used to design new potential inhibitors that employ non-covalent and covalent modes of action. These will then be subjected to calculations with the best modelling approaches. Candidates would not need experience in using any of these calculation types although some understanding of their background would be beneficial.Subsequently, the student will be able to choose to either synthesise and test some of the best molecules or else to explore a wider range of phosphatases computationally in order to explore whether this class of enzymes might be amenable to some of the latest in machine learning approaches in order to generalise the quantum mechanical/dynamical calculations.