title: Compilation and physicochemical classification analysis of a diverse hERG inhibition database.
abstract: A large and chemically diverse hERG inhibition data set comprised of 6690 compounds was constructed on the basis of ChEMBL bioactivity database and original publications dealing with experimental determination of hERG activities using patch-clamp and competitive displacement assays. The collected data were converted to binary format at 10 µM activity threshold and subjected to gradient boosting machine classification analysis using a minimal set of physicochemical and topological descriptors. The tested parameters involved lipophilicity (log P), ionization (pKa), polar surface area, aromaticity, molecular size and flexibility. The employed approach allowed classifying the compounds with an overall 75-80 % accuracy, even though it only accounted for non-specific interactions between hERG and ligand molecules. The observed descriptor-response profiles were consistent with common knowledge about hERG ligand binding site, but also revealed several important quantitative trends, as well as slight inter-assay variability in hERG inhibition data. The results suggest that even weakly basic groups (pKa< 6) might substantially contribute to hERG inhibition potential, whereas the role of lipophilicity depends on the compound's ionization state, and the influence of log P decreases in the order of bases > zwitterions > neutrals > acids. Given its robust performance and clear physicochemical interpretation, the proposed model may provide valuable information to direct drug discovery efforts towards compounds with reduced risk of hERG-related cardiotoxicity.
authors: VšĮ "Aukštieji algoritmai", A.Mickevičiaus 29, 08117, Vilnius, Lithuania.|ACD/Labs, Inc., 8 King Street East, Suite 107, Toronto, ON, M5C 1B5, Canada.
authors: Remigijus
authors: R
authors: Didziapetris
authors: VšĮ "Aukštieji algoritmai", A.Mickevičiaus 29, 08117, Vilnius, Lithuania. kiril.lanevskij@acdlabs.com.|ACD/Labs, Inc., 8 King Street East, Suite 107, Toronto, ON, M5C 1B5, Canada. kiril.lanevskij@acdlabs.com.
authors: Kiril
authors: 0000-0001-7419-8169
authors: K
authors: Lanevskij
mesh_terms: D000818:Animals; D016466:CHO Cells; D002627:Chemistry, Physical; D003198:Computer Simulation; D003412:Cricetulus; D062126:Databases, Chemical; D000072237:ERG1 Potassium Channel / Q000037:antagonists & inhibitors* / Q000737:chemistry; D057809:HEK293 Cells; D006801:Humans; D006863:Hydrogen-Ion Concentration; D008956:Models, Chemical; D015394:Molecular Structure; D026902:Potassium Channel Blockers / Q000737:chemistry* / Q000145:classification / Q000494:pharmacology; D021281:Quantitative Structure-Activity Relationship; D012984:Software
chemical_list: D000072237:ERG1 Potassium Channel; D026902:Potassium Channel Blockers
keywords: Classification; QSAR; hERG; log P; pK a