Over the years a massive amount of high-throughput screening (HTS) data has been collected, however, the data are mainly utilized for providing lead generation programs with chemical entry points. The comparison of molecular structures and HTS data across many projects allows to identify and validate structural patterns of frequent hitters, i.e. compounds which generate multiple hits in various target families. The identification of frequent hitters is an important component in maintaining a high-quality screening deck and supports project teams in the triaging of HTS hit lists. In addition, frequent hitters will be contrasted with privileged motifs which are believed to show activities in specific target classes only. The talk will also address the question what causes compounds to be frequent hitters, and in-silico prediction methods will be discussed.
. 2011 Apr 19;3(Suppl 1):O2. doi: 10.1186/1758-2946-3-S1-O2
Cross-project HTS-datamining
Wolfgang Guba
1,✉, Daniel Stoffler
1
Wolfgang Guba
1F. Hoffmann-La Roche Ltd., Basel, CH-4070, Switzerland
Find articles by Wolfgang Guba
Daniel Stoffler
1F. Hoffmann-La Roche Ltd., Basel, CH-4070, Switzerland
Find articles by Daniel Stoffler
1F. Hoffmann-La Roche Ltd., Basel, CH-4070, Switzerland
✉
Corresponding author.
Supplement
6th German Conference on Chemoinformatics, GCC 2010
Frank Oellien, Uli Fechner and Thomas Engel
Conference
7-9 November 2010
6th German Conference on Chemoinformatics, GCC 2010
Goslar, Germany
Collection date 2011.
Copyright ©2011 Guba and Stoffler; licensee BioMed Central Ltd.
This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
PMCID: PMC3083550
