Priaxon AG, Gmunder Straße 37-37a, 81379, Munich, Germany.
Mol Divers. 2010 Aug;14(3):513-22. doi: 10.1007/s11030-010-9225-x. Epub 2010 Mar 16.
During the last decades, multicomponent chemistry has gained much attention in pharmaceutical research, especially in the context of lead finding and optimization. Here, in particular, the main advantages of multicomponent reactions (MCRs) like ease of automation and high diversity generation were utilized. In consequence of these beneficial properties, a plethora of new MCRs combined with appropriate classical reaction sequences have been published, the accessible chemical space was extended steadily. In the meantime, the desired high diversity became a challenge itself, because by now the systematic use of this huge and unmanageable space for drug discovery was limited by the lack of suitable computational tools. Therefore, this article provides an insight for the rational use of this enormous chemical space in drug discovery and generic drug synthesis. In this context, a short overview of the applied chemo informatics, necessary for the virtual screening of the biggest available chemical space, is given. Furthermore, some examples for recently developed multicomponent sequences are presented.
在过去的几十年中,多组分化学在药物研究中受到了广泛关注,特别是在寻找和优化先导化合物方面。特别是,多组分反应(MCRs)的主要优点,如易于自动化和高多样性的产生,得到了利用。由于这些有益的特性,大量新的多组分反应与适当的经典反应序列相结合已经被发表,可及的化学空间不断扩展。同时,所需的高多样性本身也成为了一个挑战,因为到目前为止,由于缺乏合适的计算工具,系统地利用这个庞大且难以管理的空间进行药物发现受到了限制。因此,本文提供了一种合理利用这一巨大化学空间进行药物发现和仿制药合成的方法。在这方面,简要概述了应用于虚拟筛选最大可用化学空间所需的化学信息学。此外,还介绍了一些最近开发的多组分序列的例子。