Lounkine, Eugen, Kutchukian, Peter, Petrone, Paula, Davies, John and Glick, Meir (2012) Chemotography for multi-target SAR analysis in the context of biological pathways. Bioorganic and Medicinal Chemistry. ISSN 0968-0896

Abstract

The increasing amount of chemogenomics data, i.e. activity measurements of many compounds across a variety of biological targets, allows for better understanding of pharmacology in a broad biological context. Rather than aiming at individual biological targets, today understanding of compound interaction with complex biological systems and molecular pathways is often sought in phenotypic screens. This perspective poses novel challenges to structure-activity relationship (SAR) assessment. Today, the bottleneck of drug discovery lies in the understanding of SAR of rich datasets in the context biological pathways, potential off-targets, and complex selectivity profiles. Contrary to this change of philosophy, SAR analysis in medicinal chemistry is still largely done on a single target-basis, and current computational tools cannot take into account a rich biological context beyond one target. Here, we introduce Chemotography (chemotype chromatography), which encodes chemical space using a color spectrum by combining clustering and multidimensional scaling. Rich biological data in our approach is visualized using spatial dimensions traditionally reserved for chemical space. This allowed to integrate SAR with target hierarchies and phylogenetic trees, two-target activity scatter plots, and biological pathways. Chemotography allowed us to extract pathway-relevant SAR from the ChEMBL database in combination with the Kyoto Encyclopedia of Genes and Genomes (KEGG). We identified chemotypes showing polypharmacology and selectivity-conferring scaffolds, even in cases where individual compounds have not been tested against all relevant targets. In addition, we analyzed SAR in ChEMBL across the entire Kinome, going beyond individual compounds. Chemotography is a new paradigm for chemogenomic data visualization and its versatile applications presented here may allow for improved assessment of SAR in biological context, such as phenotypic assay hit lists. It combines the strengths of chemical space visualization for SAR analysis and graphical representation of complex biological data.

Item Type:	Article
Related URLs:	http://www.ncbi.nlm.nih.gov/pubmed?term=...
Keywords:	Chemical Space, Color Visualization, Molecular Fingerprints, Chemogenomics, Systems Phamracology
Related URLs:	http://www.ncbi.nlm.nih.gov/pubmed?term=...
Date Deposited:	13 Oct 2015 13:14
Last Modified:	13 Oct 2015 13:14
URI:	https://oak.novartis.com/id/eprint/6578