COMPUTER-AIDED DRUG DESIGN MINICORE FACILITY PROJECT

该项目由计算机辅助药物设计微型核心机构负责人Marc C.Nicklaus博士领导，其主要目标是使开放式NCI数据库中的信息能够在内部和公开的情况下用于药物开发。使用了来自NCI的发展治疗计划(DTP)的数据和我们用来扩充DTP数据集的附加信息。对数据进行了先进的处理，并实现了强大的搜索和显示功能。NCI化学结构数据库是NCI在过去45年中筛选抗癌(以及最近也是抗艾滋病)活性化合物的过程中以计算机可读形式积累的大约50万个结构的集合。通常，对于这些分子中的60%，样品可用于例如在分析中进行测试。这种样本收集是LMCH的许多计算机辅助药物开发项目中使用的宝贵资源。大约一半的数据库由与样品供应商签订的保密协议覆盖，而另一半(开放的NCI数据库)则可公开访问，计算机结构由DTP作为公共领域数据提供。我们对Open NCI数据库进行了各种分析，以帮助更好地了解其特点，并将其与计算机辅助药物设计和化学信息科学中使用的其他大型数据库进行比较。各种聚类方法正被应用于它，以阐明其多样性，并将结果与其他数据库的结果进行比较。计算了包括Open NCI数据库在内的整个数据库的内部重复率和相互重叠。Open NCI数据库被转换成各种格式，适合进一步处理，包括3D药效团搜索。我们还在为Open NCI数据库实施一个强大的公共搜索工具，该工具具有一个基于化学信息工具包CACTVS的网络界面。只需使用一个网络浏览器，用户将能够搜索600多个标准的大约25万个结构。我们在原始DTP文件中添加了大量额外的数据字段，无论是计算、预测还是超链接信息。这些数据还以可直接下载的格式提供。实现了指向几个用于进一步处理的附加服务的链接。一种简单的3D药效团能力正在实施中。目前和未来的合作意在提供更多的数据和可能的结构集。网址为http://cactus.nci.nih.gov.

The principal objective of this project, headed by Dr. Marc C. Nicklaus, Head, Computer-Aided Drug Design MiniCore Facility, is to make the information in the Open NCI Database available for aiding in drug development, both in-house and publicly. Both the data from NCI's Developmental Therapeutics Program (DTP) and additional information with which we have augmented the DTP datasets are used. Advanced processing is applied to the data, and powerful searching and display capabilities are being implemented. The NCI chemical structural database is a collection about half a million structures, accumulated in computer-readable form during the past 45 years in the course of NCI's screening of compounds for anti-cancer (and recently also anti-AIDS) activity. For typically 60% of these molecules, samples are available for, e.g., testing in assays. This sample collection is a valuable resource used in many of the LMCh's computer-aided drug development projects. Approximately half of the database is covered by confidentiality agreements with the samples' suppliers, whereas the other half (the Open NCI Database) is openly accessible, with the computer structures being made available by DTP as public domain data. We have subjected the Open NCI Database to various analyses that help to better understand its characteristics and put it in perspective of other large databases used in computer-aided drug design and chemical information sciences. Various clustering methods are being applied to it to elucidate its diversity, and the results are compared with those for other databases. Internal duplication rates as well as mutual overlaps are calculated for the entire set of databases including the Open NCI Database. The Open NCI Database is converted into various formats, suitable for further processing including 3D pharmacophore searching. We are also implementing a powerful public search tool for the Open NCI Database with a web interface based on the chemical information toolkit CACTVS. Using just a web browser, the user will be able to search about 250,000 structures for more than 600 criteria. We have greatly augmented the original DTP files with numerous additional data fields, be it calculated, predicted or hyperlinked information. These data are also made available in directly downloadable format. Links to several additional services for further processing are implemented. A simple 3D pharmacophore capability is being implemented. Current and future collaborations are intended to provide additional data and possibly structure sets. The URL is http://cactus.nci.nih.gov.