High-throughput screening campaigns are fuelled not only by corporate or “maximally diverse” compound collections, but increasingly accompanied by target- or bioactivity-focused selections of screening compounds. Computerassisted library design methods aid in the compilation of focused molecule libraries. A prerequisite for application of any such computational approach is the definition of a reference set and a molecular similarity metric, based on which compound clustering and iterative virtual screening are performed. In this context the self-organizing map (SOM, Kohonen network) and variations thereof have found widespread application. SOMs cover such diverse fields of drug discovery as screening library design, scaffold-hopping, and repurposing. Here we present the concept of the SOM technique along with recent case studies. Advantages, limitations and potential future applications are critically discussed.
Keywords: Bioisosteric replacement, cheminformatics, chemical space, database, drug design, Kohonen network, leadhopping, molecular similarity, virtual screening
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