Illuminating the druggable genome through patent bioactivity data.
Illuminating the druggable genome through patent bioactivity data.
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作者：
Magariños MP;Gaulton A;Félix E;Kiziloren T;Arcila R;Oprea TI;Leach AR
专利文献是生物活性数据的潜在有价值的来源。在这篇文章中，我们描述了一个过程，优先考虑从SureChEMBL数据库获得的370万个生命科学相关专利（），根据它们在较少研究的目标上包含有效小分子生物活性数据的可能性，基于Illuminating the Druggable Genome（IDG）项目开发的分类。总体目标是选择少量可以手动管理并纳入ChEMBL数据库的专利。使用相对简单的注释和过滤管道，我们已经能够识别大量的专利，其中包含先前在同行评议的药物化学文献中未报道的未充分研究的靶点的定量生物活性数据。我们量化这些方法的附加值的数量，这样确定的目标，并提供了一些具体的说明性例子。我们的工作强调了除了更传统的同行评议文献之外，搜索专利语料库的潜在价值。在这些专利中发现的小分子，以及它们对靶点的测量活性，现在可以通过ChEMBL数据库访问。
The patent literature is a potentially valuable source of bioactivity data. In this article we describe a process to prioritise 3.7 million life science relevant patents obtained from the SureChEMBL database (), according to how likely they were to contain bioactivity data for potent small molecules on less-studied targets, based on the classification developed by the Illuminating the Druggable Genome (IDG) project. The overall goal was to select a smaller number of patents that could be manually curated and incorporated into the ChEMBL database. Using relatively simple annotation and filtering pipelines, we have been able to identify a substantial number of patents containing quantitative bioactivity data for understudied targets that had not previously been reported in the peer-reviewed medicinal chemistry literature. We quantify the added value of such methods in terms of the numbers of targets that are so identified, and provide some specific illustrative examples. Our work underlines the potential value in searching the patent corpus in addition to the more traditional peer-reviewed literature. The small molecules found in these patents, together with their measured activity against the targets, are now accessible via the ChEMBL database.
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蛋白质甲基转移酶和去甲基酶抑制剂。
影响因子：
62.1
作者：
Kaniskan HÜ;Martini ML;Jin J
通讯作者：
Jin J
影响因子：
9.8
作者：
Gaulton, Anna;Kale, Namrata;van Westen, Gerard J. P.;Bellis, Louisa J.;Bento, A. Patricia;Davies, Mark;Hersey, Anne;Papadatos, George;Forster, Mark;Wege, Philip;Overington, John P.
通讯作者：
Overington, John P.
影响因子：
14.9
作者：
Avram S;Bologa CG;Holmes J;Bocci G;Wilson TB;Nguyen DT;Curpan R;Halip L;Bora A;Yang JJ;Knockel J;Sirimulla S;Ursu O;Oprea TI
通讯作者：
Oprea TI
DOI：
10.1093/bioinformatics/btac716
发表时间：
2023-01-01
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
通讯作者：
--
影响因子：
8.6
作者：
Garbaccio, Robert M.;Parmee, Emma R.
通讯作者：
Parmee, Emma R.