A chemoinformatics analysis of hit lists obtained from high-throughput affinity-selection screening

被引:23
作者
Brown, N [1 ]
Zehender, H [1 ]
Azzaoui, K [1 ]
Schuffenhauer, A [1 ]
Mayr, LM [1 ]
Jacoby, E [1 ]
机构
[1] Novartis Inst Biomed Res, CH-4002 Basel, Switzerland
关键词
affinity-based high-throughput screening; SpeedScreen; chemoinformatics; scaffolds; genetic algorithms; subset selection; diversity;
D O I
10.1177/1087057105283579
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
The high-throughput affinity-selection screening platform SpeedScreen was recently reported by the Novartis Institutes for BioMedical Research as a homogeneous, label-free screening technology with mass-spectrometry readout. SpeedScreen relies on the screening of compound mixtures with various target proteins and uses fast size-exclusion chromatography to separate target-bound from unbound substances. After disintegration of the target-binder complex, the binder molecules are identified by their molecular masses using liquid chromatography/mass spectrometry. The authors report an analysis of the molecular properties of hits obtained with SpeedScreen on 26 targets screened within the past few years at Novartis using this technology. Affinity-based SpeedScreen is a robust high-throughput screening technology that does not accumulate frequent hitters or potential covalent binders. The hits are representative of the most commonly identified scaffold classes observed for known drugs. Validated SpeedScreen hits tend to be enriched on more lipophilic and larger-molecular-weight compounds compared to the whole library. The potential for a reduced SpeedScreen screening set to be used in case only limited protein quantities are available is evaluated. Such a reduced compound set should also maximize the coverage of the high-performing regions of the chemical property and class spaces; chemoinformatics methods including genetic algorithms and divisive K-means clustering are used for this aim.
引用
收藏
页码:123 / 130
页数:8
相关论文
共 32 条
[1]   The properties of known drugs .1. Molecular frameworks [J].
Bemis, GW ;
Murcko, MA .
JOURNAL OF MEDICINAL CHEMISTRY, 1996, 39 (15) :2887-2893
[2]   Target-related affinity profiling: Telik's lead discovery technology [J].
Beroza, P ;
Damodaran, K ;
Lum, RT .
CURRENT TOPICS IN MEDICINAL CHEMISTRY, 2005, 5 (04) :371-381
[3]   Use of structure Activity data to compare structure-based clustering methods and descriptors for use in compound selection [J].
Brown, RD ;
Martin, YC .
JOURNAL OF CHEMICAL INFORMATION AND COMPUTER SCIENCES, 1996, 36 (03) :572-584
[4]  
CLARK DE, 2000, EVOLUTIONARY ALGORIT
[5]   Components of successful lead generation [J].
Davis, AM ;
Keeling, DJ ;
Steele, J ;
Tomkinson, NP ;
Tinker, AC .
CURRENT TOPICS IN MEDICINAL CHEMISTRY, 2005, 5 (04) :421-439
[6]   Onion design and its application to a pharmaceutical QSAR problem [J].
Eriksson, L ;
Arnhold, T ;
Beck, B ;
Fox, T ;
Johansson, E ;
Kriegl, JM .
JOURNAL OF CHEMOMETRICS, 2004, 18 (3-4) :188-202
[7]  
Gasteiger J., 2003, CHEMOINFORMATICS TXB
[8]  
Goodnow RA, 2003, COMB CHEM HIGH T SCR, V6, P649
[9]   Pursuing the leadlikeness concept in pharmaceutical research [J].
Hann, MM ;
Oprea, TI .
CURRENT OPINION IN CHEMICAL BIOLOGY, 2004, 8 (03) :255-263
[10]   ALARM NMR: A rapid and robust experimental method to detect reactive false positives in biochemical screens [J].
Huth, JR ;
Mendoza, R ;
Olejniczak, ET ;
Johnson, RW ;
Cothron, DA ;
Liu, YY ;
Lerner, CG ;
Chen, J ;
Hajduk, PJ .
JOURNAL OF THE AMERICAN CHEMICAL SOCIETY, 2005, 127 (01) :217-224