Okada Takashi, Yamakawa Masumi, Ohmori Norihito, Mori Sachio, Horikawa Hiroshi, Hayashi Taketo, Fujishima Satoshi
Department of Informatics, School of Science & Technology, Kwansei Gakuin University, Sanda, Hyogo, Japan.
Chem Cent J. 2010 Jan 23;4(1):1. doi: 10.1186/1752-153X-4-1.
Chemical compounds affecting a bioactivity can usually be classified into several groups, each of which shares a characteristic substructure. We call these substructures "basic active structures" or BASs. The extraction of BASs is challenging when the database of compounds contains a variety of skeletons. Data mining technology, associated with the work of chemists, has enabled the systematic elaboration of BASs.
This paper presents a BAS knowledge base, BASiC, which currently covers 46 activities and is available on the Internet. We use the dopamine agonists D1, D2, and Dauto as examples and illustrate the process of BAS extraction. The resulting BASs were reasonably interpreted after proposing a few template structures.
The knowledge base is useful for drug design. Proposed BASs and their supporting structures in the knowledge base will facilitate the development of new template structures for other activities, and will be useful in the design of new lead compounds via reasonable interpretations of active structures.
影响生物活性的化合物通常可分为几组,每组都有一个特征性的亚结构。我们将这些亚结构称为“基本活性结构”或BASs。当化合物数据库包含各种骨架时,BASs的提取具有挑战性。与化学家的工作相关的数据挖掘技术,使得对BASs进行系统阐述成为可能。
本文介绍了一个BAS知识库BASiC,它目前涵盖46种活性,可在互联网上获取。我们以多巴胺激动剂D1、D2和Dauto为例,说明了BAS提取的过程。在提出一些模板结构后,对得到的BASs进行了合理的解释。
该知识库对药物设计有用。知识库中提出的BASs及其支持结构将有助于开发针对其他活性的新模板结构,并将通过对活性结构的合理解释,在新先导化合物的设计中发挥作用。