Lessons learnt from assembling screening libraries for drug discovery for neglected disease
ABSTRACT To enable the establishment of a drug discovery operation for neglected diseases, out of 2.3 million commercially available compounds 222 552 compounds were selected for an in silico library, 57 438 for a diverse general screening library, and 1 697 compounds for a focused kinase set. Compiling these libraries required a robust strategy for compound selection. Rules for unwanted groups were defined and selection criteria to enrich for lead-like compounds which facilitate straightforward structure–activity relationship exploration were established. Further, a literature and patent review was undertaken to extract key recognition elements of kinase inhibitors (“core fragments”) to assemble a focused library for hit discovery for kinases. Computational and experimental characterisation of the general screening library revealed that the selected compounds 1) span a broad range of lead-like space, 2) show a high degree of structural integrity and purity, and 3) demonstrate appropriate solubility for the purposes of biochemical screening. The implications of this study for compound selection, especially in an academic environment with limited resources, are considered.
- SourceAvailable from: ru.nl[show abstract] [hide abstract]
ABSTRACT: In contrast to high-throughput screening, in virtual ligand screening (VS), compounds are selected using computer programs to predict their binding to a target receptor. A key prerequisite is knowledge about the spatial and energetic criteria responsible for protein-ligand binding. The concepts and prerequisites to perform VS are summarized here, and explanations are sought for the enduring limitations of the technology. Target selection, analysis and preparation are discussed, as well as considerations about the compilation of candidate ligand libraries. The tools and strategies of a VS campaign, and the accuracy of scoring and ranking of the results, are also considered.Drug Discovery Today 08/2006; 11(13-14):580-94. · 6.55 Impact Factor
- [show abstract] [hide abstract]
ABSTRACT: Using a simple model of ligand-receptor interactions, the interactions between ligands and receptors of varying complexities are studied and the probabilities of binding calculated. It is observed that as the systems become more complex the chance of observing a useful interaction for a randomly chosen ligand falls dramatically. The implications of this for the design of combinatorial libraries is explored. A large set of drug leads and optimized compounds is profiled using several different properties relevant to molecular recognition. The changes observed for these properties during the drug optimization phase support the hypothesis that less complex molecules are more common starting points for the discovery of drugs. An extreme example of the use of simple molecules for directed screening against thrombin is provided.Journal of Chemical Information and Computer Sciences 01/2001; 41(3):856-64.
Article: On sampling of fragment space.[show abstract] [hide abstract]
ABSTRACT: Fragment-based lead discovery has over the years matured into an attractive alternative to high-throughput screening (HTS) for lead generation. Several techniques for screening libraries of typically 10(3)-10(4) fragments have been reported. In this work, the practical success rates that can be expected from the screening of fragment-like libraries was investigated via interrogating medicinal chemistry databases for several programs with virtual libraries created from commercially available reagents or with libraries of commercially available fragments. The results suggest that hits more potent than typically discovered in today's fragment-based screens can consistently be identified from realistically accessible compound sets under screening conditions similar to commonly used HTS protocols.Journal of Medicinal Chemistry 08/2007; 50(14):3214-21. · 5.61 Impact Factor