Balakin Konstantin V, Kozintsev Alexander V, Kiselyov Alex S, Savchuk Nikolay P
ChemDiv, Inc., 11558 Sorrento Valley Rd., Ste. 5, San Diego, CA 92121, USA.
Curr Drug Discov Technol. 2006 Mar;3(1):49-65. doi: 10.2174/157016306776637564.
Sequencing of the human genome along with developments in combinatorial synthesis and high-throughput biological screening provide unparallel opportunities to drug discovery. It has been noted that the increased number of synthesized and annotated compounds did not yield the expected increase in number of viable drug candidates. To address this problem, several novel computation technologies have emerged for making combinatorial library design cost-effective. Of particular interest for the modern drug discovery are the structure-based or target-based methods that use structural information about target proteins and their small molecule ligands. In this work, we provide an overview of selected advances in computational algorithms for the rational selection of molecule libraries for the synthesis, with emphasis on structure-based approaches. These include a fusion of scaffold-linking method and combinatorial library design, pharmacophore matching and informative library design, and search by 3-D tree topological descriptors.
人类基因组测序以及组合合成和高通量生物筛选技术的发展为药物发现提供了无与伦比的机会。人们已经注意到，合成和注释化合物数量的增加并没有带来可行药物候选物数量的预期增长。为了解决这个问题，出现了几种新颖的计算技术，以使组合文库设计具有成本效益。对于现代药物发现特别感兴趣的是基于结构或基于靶点的方法，这些方法使用关于靶蛋白及其小分子配体的结构信息。在这项工作中，我们概述了用于合理选择用于合成的分子文库的计算算法的选定进展，重点是基于结构的方法。这些方法包括支架连接方法与组合文库设计的融合、药效团匹配和信息丰富的文库设计，以及通过三维树拓扑描述符进行搜索。
