Awale Mahendra, Visini Ricardo, Probst Daniel, Arús-Pous Josep, Reymond Jean-Louis
Department of Chemistry and Biochemistry National Center of Competence in Research NCCR TransCure University of Bern Freiestrasse 3, CH-3012 Bern.
Department of Chemistry and Biochemistry National Center of Competence in Research NCCR TransCure University of Bern Freiestrasse 3, CH-3012 Bern;, Email:
Chimia (Aarau). 2017 Oct 25;71(10):661-666. doi: 10.2533/chimia.2017.661.
Chemical space describes all possible molecules as well as multi-dimensional conceptual spaces representing the structural diversity of these molecules. Part of this chemical space is available in public databases ranging from thousands to billions of compounds. Exploiting these databases for drug discovery represents a typical big data problem limited by computational power, data storage and data access capacity. Here we review recent developments of our laboratory, including progress in the chemical universe databases (GDB) and the fragment subset FDB-17, tools for ligand-based virtual screening by nearest neighbor searches, such as our multi-fingerprint browser for the ZINC database to select purchasable screening compounds, and their application to discover potent and selective inhibitors for calcium channel TRPV6 and Aurora A kinase, the polypharmacology browser (PPB) for predicting off-target effects, and finally interactive 3D-chemical space visualization using our online tools WebDrugCS and WebMolCS. All resources described in this paper are available for public use at www.gdb.unibe.ch.
化学空间描述了所有可能的分子以及代表这些分子结构多样性的多维概念空间。化学空间的一部分可在包含数千至数十亿种化合物的公共数据库中获取。利用这些数据库进行药物发现是一个典型的大数据问题,受到计算能力、数据存储和数据访问能力的限制。在此,我们回顾了我们实验室的最新进展,包括化学宇宙数据库(GDB)和片段子集FDB - 17的进展、通过最近邻搜索进行基于配体的虚拟筛选的工具,例如我们用于ZINC数据库以选择可购买筛选化合物的多指纹浏览器,以及它们在发现钙通道TRPV6和极光A激酶的强效和选择性抑制剂方面的应用、用于预测脱靶效应的多药理学浏览器(PPB),最后是使用我们的在线工具WebDrugCS和WebMolCS进行交互式3D化学空间可视化。本文所述的所有资源均可在www.gdb.unibe.ch上供公众使用。