molBLOCKS: decomposing small molecule sets and uncovering enriched fragments
Author(s) -
Dario Ghersi,
Mona Singh
Publication year - 2014
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btu173
Subject(s) - computer science , source code , set (abstract data type) , cluster analysis , biomolecule , suite , software , small molecule , data mining , computational biology , theoretical computer science , chemistry , programming language , biology , machine learning , biochemistry , archaeology , history
The chemical structures of biomolecules, whether naturally occurring or synthetic, are composed of functionally important building blocks. Given a set of small molecules-for example, those known to bind a particular protein-computationally decomposing them into chemically meaningful fragments can help elucidate their functional properties, and may be useful for designing novel compounds with similar properties. Here we introduce molBLOCKS, a suite of programs for breaking down sets of small molecules into fragments according to a predefined set of chemical rules, clustering the resulting fragments, and uncovering statistically enriched fragments. Among other applications, our software should be a great aid in large-scale chemical analysis of ligands binding specific targets of interest.
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