Drug- and Lead-likeness, Target Class, and Molecular Diversity Analysis of 7.9 Million Commercially Available Organic Compounds Provided by 29 Suppliers

被引:73
作者
Chuprina, Alexander [1 ]
Lukin, Oleg [1 ]
Demoiseaux, Robert [2 ]
Buzko, Alexander [3 ]
Shivanyuk, Alexander [4 ]
机构
[1] Natl Taras Shevchenko Univ, ChemBioCtr, UA-01033 Kiev 33, Ukraine
[2] Univ Calif Los Angeles, Jonsson Comprehens Canc Ctr, Los Angeles, CA 90095 USA
[3] Abraxis Biosci Inc, Los Angeles, CA 90025 USA
[4] Natl Taras Shevchenko Univ, Inst High Technol, UA-01033 Kiev 33, Ukraine
关键词
AQUEOUS SOLUBILITY; PREDICTION; COMBINATORIAL; LEADLIKENESS; DISCOVERY; LIBRARIES; SELECTION;
D O I
10.1021/ci900464s
中图分类号
R914 [药物化学];
学科分类号
100701 ;
摘要
A database of 7.9 million compounds commercially available from 29 suppliers in 2008-2009 was assembled and analyzed. 5.2 million structures of this database were identified to be unique and were subjected to an assessment of physical and biological properties and estimation of molecular diversity. The rules of Lipinski and Veber were applied to the molecular weight, the calculated water/n-octanol partition coefficients (Clog P), the calculated aqueous solubility (log S), the numbers of hydrogen-bond donors and acceptors, and the calculated Caco-2 membrane permeability to identify the drug-like compounds, whereas the toxicity/reactivity filters were used to remove the structures with biologically undesired functional groups. This filtering resulted in 2.0 million (39%) structures perfectly suitable for high-throughput screening of biological activity. Modified filters applied to identify lead-like structures revealed that 16% of the unique compounds could be potential leads. Assessment of the biological activities, the analysis of diversity, and the sizes of exclusive sets of compounds are presented.
引用
收藏
页码:470 / 479
页数:10
相关论文
共 26 条
[1]   Drug-like annotation and duplicate analysis of a 23-supplier chemical database totalling 2.7 million compounds [J].
Baurin, N ;
Baker, R ;
Richardson, C ;
Chen, I ;
Foloppe, N ;
Potter, A ;
Jordan, A ;
Roughley, S ;
Parratt, M ;
Greaney, P ;
Morley, D ;
Hubbard, RE .
JOURNAL OF CHEMICAL INFORMATION AND COMPUTER SCIENCES, 2004, 44 (02) :643-651
[2]  
Butina D, 2003, J CHEM INF COMP SCI, V43, P837, DOI 10.1021/6020279y
[3]  
*CHEMAXON KFT, 2008, JCHEM VERS 5 1 4
[4]   Property distributions: Differences between drugs, natural products, and molecules from combinatorial chemistry [J].
Feher, M ;
Schmidt, JM .
JOURNAL OF CHEMICAL INFORMATION AND COMPUTER SCIENCES, 2003, 43 (01) :218-227
[5]   Chemical similarity assessment through multilevel neighborhoods of atoms: definition and comparison with the other descriptors [J].
Filimonov, D ;
Poroikov, V ;
Borodina, Y ;
Gloriozova, T .
JOURNAL OF CHEMICAL INFORMATION AND COMPUTER SCIENCES, 1999, 39 (04) :666-670
[6]   A knowledge-based approach in designing combinatorial or medicinal chemistry libraries for drug discovery. 1. A qualitative and quantitative characterization of known drug databases [J].
Ghose, AK ;
Viswanadhan, VN ;
Wendoloski, JJ .
JOURNAL OF COMBINATORIAL CHEMISTRY, 1999, 1 (01) :55-68
[7]   Pursuing the leadlikeness concept in pharmaceutical research [J].
Hann, MM ;
Oprea, TI .
CURRENT OPINION IN CHEMICAL BIOLOGY, 2004, 8 (03) :255-263
[8]   Parameter based methods for compound selection from chemical databases [J].
Hudson, BD ;
Hyde, RM ;
Rahr, E ;
Wood, J .
QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIPS, 1996, 15 (04) :285-289
[9]  
Huser J., 2006, High-throughput Screening for Targeted Lead Discovery, High-Throughput Screening in Drug Discovery, P15
[10]   Estimation of aqueous solubility for a diverse set of organic compounds based on molecular topology [J].
Huuskonen, J .
JOURNAL OF CHEMICAL INFORMATION AND COMPUTER SCIENCES, 2000, 40 (03) :773-777