Quantitative structure-property relationship modeling: a valuable support in high-throughput screening quality control.
Evaluation of important pharmacokinetic properties such as hydrophobicity by high-throughput screening (HTS) methods is a major issue in drug discovery. In this paper, we present measurements of the chromatographic hydrophobicity index (CHI) on a subset of the French chemical library Chimiothèque Nationale (CN). The data were used in quantitative structure-property relationship (QSPR) modeling in order to annotate the CN. An algorithm is proposed to detect problematic molecules with large prediction errors, called outliers. In order to find an explanation for these large discrepancies between predicted and experimental values, these compounds were reanalyzed experimentally. As the first selected outliers indeed had experimental problems, including hydrolysis or sheer absence of expected structure, we herewith propose the use of QSPR as a support tool for quality control of screening data and encourage cooperation between experimental and theoretical teams to improve results. The corrected data were used to produce a model, which is freely available on our web server at http://infochim.u-strasbg.fr/webserv/VSEngine.html .
Laboratoire de Chémoinformatique, UMR 7140 CNRS, Université de Strasbourg , 1 rue Blaise Pascal, 67000 Strasbourg, France.
Fiorella
F
Ruggiu
Patrick
P
Gizzi
Jean-Luc
JL
Galzi
Marcel
M
Hibert
Jacques
J
Haiech
Igor
I
Baskin
Dragos
D
Horvath
Gilles
G
Marcou
Alexandre
A
Varnek
D057166:High-Throughput Screening Assays; D057927:Hydrophobic and Hydrophilic Interactions; D011786:Quality Control; D021281:Quantitative Structure-Activity Relationship