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用于数据驱动药物设计和化学生物组学的共识化合物/生物活性数据集。

A Consensus Compound/Bioactivity Dataset for Data-Driven Drug Design and Chemogenomics.

机构信息

Institute of Pharmaceutical Chemistry, Goethe University Frankfurt, 60438 Frankfurt, Germany.

Structural Genomics Consortium, BMLS, Goethe University Frankfurt, 60438 Frankfurt, Germany.

出版信息

Molecules. 2022 Apr 13;27(8):2513. doi: 10.3390/molecules27082513.

Abstract

Publicly available compound and bioactivity databases provide an essential basis for data-driven applications in life-science research and drug design. By analyzing several bioactivity repositories, we discovered differences in compound and target coverage advocating the combined use of data from multiple sources. Using data from ChEMBL, PubChem, IUPHAR/BPS, BindingDB, and Probes & Drugs, we assembled a consensus dataset focusing on small molecules with bioactivity on human macromolecular targets. This allowed an improved coverage of compound space and targets, and an automated comparison and curation of structural and bioactivity data to reveal potentially erroneous entries and increase confidence. The consensus dataset comprised of more than 1.1 million compounds with over 10.9 million bioactivity data points with annotations on assay type and bioactivity confidence, providing a useful ensemble for computational applications in drug design and chemogenomics.

摘要

公开可用的化合物和生物活性数据库为生命科学研究和药物设计中的数据驱动型应用提供了重要基础。通过分析几个生物活性存储库,我们发现化合物和靶标覆盖率存在差异,因此提倡综合使用来自多个来源的数据。我们使用来自 ChEMBL、PubChem、IUPHAR/BPS、BindingDB 和 Probes & Drugs 的数据,组装了一个关注具有人类大分子靶标生物活性的小分子的共识数据集。这使得化合物空间和靶标覆盖率得到了改善,并通过自动比较和管理结构和生物活性数据来揭示潜在的错误条目并提高置信度。共识数据集包含超过 110 万个化合物,超过 1090 万个生物活性数据点,并对测定类型和生物活性置信度进行了注释,为药物设计和化学生物组学中的计算应用提供了有用的组合。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1560/9028877/2bd78defa902/molecules-27-02513-g001a.jpg

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