Array Design for Lead Optimisation in Pharmaceutical Research

先导化合物优化是药物发现项目的一部分，其中合成和测试分子以确保它们不仅具有某些所需的药理活性，例如，降低血压或缩小肿瘤，而且还表现出一系列额外的所需性质，例如，易溶、易于合成且无毒。寻求发现新药的药物化学家传统上在迭代的设计-合成-测试循环中一次合成一个潜在的药物分子。然而，最近引入的组合化学技术使他们能够同时合成包含数百甚至数千种化合物的阵列。虽然这是一种非常有效的合成新分子的方法，因此提供了一种探索可能化合物范围的有效方法，但化学家仍然面临着困难的设计决策，特别是在寻求找到几种性质的最佳组合时。该项目将开发计算机工具，帮助药物化学家设计新的化合物阵列，以加快新药的发现。该项目将利用葛兰素史克过去在铅优化计划中生成的大量阵列档案。一个关键的阶段将涉及分析档案，以确定过去使用阵列来探索分子结构与其性质之间关系的方式，特别是在成功优化过程中这些性质得到改善的方式。然后，这个知识提取阶段将为项目的第二阶段提供输入，该阶段将涉及决策支持系统的构建，这是一个计算机系统，将为化学家提供关于在优化项目的每个阶段下一步制作什么阵列或阵列的指南。开发一个对化学家友好的阵列设计系统对实验化学家来说应该是巨大的好处，不仅在制药和农业化学领域，而且在其他开始使用阵列方法的工业领域，如材料科学和催化剂设计。

Lead optimisation is the name given to that part of a drug discovery project in which molecules are synthesised and tested to ensure that they not only have some required pharmacological activity, e.g., reducing blood pressure or shrinking a tumour, but also exhibit a range of additional desirable properties, e.g., being readily soluble, easy to synthesise and not being toxic. Medicinal chemists seeking to discover new drugs have traditionally synthesised potential drug molecules one at a time in an iterative design-synthesise-test cycle. However, the recent introduction of combinatorial chemistry technologies enables them to synthesis arrays containing hundreds or even thousands of compounds simultaneously. While, this is a very efficient way of synthesising new molecules and thus provides an effective way of exploring the range of possible compounds, the chemist is still faced with difficult design decisions especially when seeking to find the optimum combination of several properties. This project will develop computer tools that will assist a medicinal chemist in designing new arrays of compounds, with the aim of expediting the discovery of new drugs. The project will draw on a large archive of arrays that have been generated in the past in lead optimisation programmes at GlaxoSmithKline. A key phase will involve analysing the archive to determine the ways in which arrays have been used in the past to explore relationships between the structures of molecules and their properties, and in particular the ways in which these properties have been improved over the course of a successful optimisation. This knowledge extraction phase will then provide the input to the second phase of the project, which will involve the construction of a decision support system, a computer system that will provide the chemist with guidelines on what array or arrays to make next at each stage of an optimisation project. The development of a chemist-friendly system for array design should be of enormous benefit to experimental chemists, not just in the pharmaceutical and agrochemical sectors, but also in other industrial sectors where array methods are starting to be used, such as materials science and catalyst design.