Identification of descriptors capturing compound class-specific features by mutual information analysis

Journal of Chemical Information and Modeling

Volumn 50, Issue 11, 2010, Pages 1935-1940

  Wassermann, Anne Mai ^a   Nisius, Britta ^a   Vogt, Martin ^a   Bajorath, Jürgen ^a  

^a UNIVERSITY OF BONN   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

INFORMATION ANALYSIS;

CHEMOINFORMATICS; CLASS SPECIFIC FEATURES; CORRELATION ANALYSIS; INFORMATION CONTENTS; LARGE DATABASE; MOLECULAR DESCRIPTORS; SHANNON ENTROPY; SPECIFIC INFORMATION;

INFORMATION THEORY;

ALGORITHM; ARTICLE; CHEMISTRY; FACTUAL DATABASE; INFORMATION SCIENCE; METHODOLOGY;

ALGORITHMS; CHEMISTRY; DATABASES, FACTUAL; INFORMATICS;

EID: 78649493849     PISSN: 15499596     EISSN: 1549960X     Source Type: Journal    
DOI: 10.1021/ci100319n     Document Type: Article

References (14)

1. Todeschini, R.; Consonni, V. Handbook of molecular descriptors; Wiley: Weinheim, Germany, 2000.
2. Bajorath, J. Integration of virtual and high-throughput screening Nat. Rev. Drug Discovery 2002, 1, 882-894
3. Liu, Y. A comparative study on feature selection methods for drug discovery J. Chem. Inf. Comput. Sci. 2004, 44, 1823-1828
4. Shannon, C. E. A mathematical theory of communication Bell. Syst. Tech. J. 1948, 27, 379-423
5. Godden, J. W.; Stahura, F. L.; Bajorath, J. Variability of molecular descriptors in compound databases revealed by Shannon entropy calculations J. Chem. Inf. Comput. Sci. 2000, 40, 796-800
6. Stahura, F. L.; Godden, J. W.; Bajorath, J. Distinguishing between natural products and synthetic molecules by descriptor Shannon entropy analysis and binary QSAR calculations J. Chem. Inf. Comput. Sci. 2000, 40, 1245-1252
7. Godden, J. W.; Bajorath, J. Differential Shannon entropy as a sensitive measure of differences in database variability of molecular descriptors J. Chem. Inf. Comput. Sci. 2001, 41, 1060-1066
8. Stahura, F. L.; Godden, J. W.; Bajorath, J. Differential Shannon entropy analysis identifies molecular property descriptors that predict aqueous solubility of synthetic compounds with high accuracy in binary QSAR calculations J. Chem. Inf. Comput. Sci. 2002, 42, 550-558
9. Irwin, J. J.; Shoichet, B. K. ZINC-a free database of commercially available compounds for virtual screening J. Chem. Inf. Model. 2005, 45, 177-182
10. Cover, T. M.; Thomas, J. A. Elements of information theory; Wiley: New York, 1991.
11. Lin, J. Divergence measures based on Shannon entropy IEEE Trans. Inf. Theory 1991, 37, 145-151
12. ChemblDB; European Bioinformatics Institute (EBI): Cambridge, U.K.; http://www.ebi.ac.uk/chembl/. Accessed August 15, 2010.
13. Molecular Operating Environment (MOE); Chemical Computing Group, Inc.: Montreal, Quebec, Canada, 2007.
14. Nisius, B.; Vogt, M.; Bajorath, J. Development of a fingerprint reduction approach for Bayesian similarity searching based on Kullback-Leibler divergence analysis J. Chem. Inf. Model. 2009, 49, 1347-1358