Open AccessChemical Space: Big Data Challenge for Molecular Diversity
Author(s) -
Mahendra Awale,
Ricardo Visini,
Daniel Probst,
Josep ArúsPous,
JeanLouis Reymond
Publication year - 2017
Publication title -
chimia
Language(s) - English
Resource type - Journals
eISSN - 2673-2424
pISSN - 0009-4293
DOI - 10.2533/chimia.2017.661
Subject(s) - chemical space , virtual screening , computer science , big data , drug discovery , chemical database , space (punctuation) , database , visualization , fingerprint (computing) , data mining , data science , information retrieval , bioinformatics , biology , artificial intelligence , operating system
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.