Analysis of data fusion methods in virtual screening: Similarity and group fusion

Journal of Chemical Information and Modeling

Volumn 46, Issue 6, 2006, Pages 2206-2219

  Whittle, Martin ^a   Gillet, Valerie J ^a   Willett, Peter ^a   Loesel, Jens ^b  

^a UNIVERSITY OF SHEFFIELD   (United Kingdom)

^b PFIZER GLOBAL RESEARCH AND DEVELOPMENT   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

DATABASE SYSTEMS; INFORMATION ANALYSIS; INFORMATION RETRIEVAL SYSTEMS; MATHEMATICAL MODELS;

MULTIPLE INTEGRAL FORMALISM; REAL DATA; SIMILARITY DISTRIBUTIONS; VIRTUAL SCREENING;

DATA REDUCTION;

DRUG;

ARTICLE; COMBINATORIAL CHEMISTRY; COMPUTER ANALYSIS; COMPUTER SIMULATION; DRUG DESIGN; DRUG INDUSTRY; DRUG SCREENING; FACTUAL DATABASE; INSTRUMENTATION; METHODOLOGY; PHARMACEUTICS; STATISTICAL ANALYSIS; STATISTICAL MODEL;

COMBINATORIAL CHEMISTRY TECHNIQUES; COMPUTER SIMULATION; COMPUTING METHODOLOGIES; DATA INTERPRETATION, STATISTICAL; DATABASES, FACTUAL; DRUG DESIGN; DRUG EVALUATION, PRECLINICAL; DRUG INDUSTRY; MODELS, STATISTICAL; PHARMACEUTICAL PREPARATIONS; TECHNOLOGY, PHARMACEUTICAL;

EID: 33845782959     PISSN: 15499596     EISSN: 1549960X     Source Type: Journal    
DOI: 10.1021/ci0496144     Document Type: Article

References (20)

1. Charifson, P. S.; Corkery, J. J.; Murcko, M. A.; Walters, W. P. Consensus Scoring: a Method for Obtaining Improved Hit Rates from Docking Databases of Three-Dimensional Structures into Proteins. J. Med. Chem. 1999, 42, 5100-5109.
2. Ginn, C. M. R.; Willett, P.; Bradshaw, J. Combination of Molecular Similarity Measures Using Data Fusion. Perspect. Drug Discovery Des. 2000, 20, 1-16.
3. Willett, P.; Barnard, J. M.; Downs, G. M. Chemical Similarity Searching. J. Chem. Inf. Comput. Sci. 1998, 38, 983-996.
4. Sheridan, R. P.; Kearsley, S. K. Why Do We Need So Many Chemical Similarity Search Methods? Drug Discovery Today 2002, 7, 903-911.
5. Edgar, S. J.; Holliday, J. D.; Willett, P. Effectiveness of Retrieval in Similarity Searches of Chemical Databases: A Review of Performance Measures. J. Mol. Graphics Modell. 2000, 18, 343-357.
6. Whittle, M.; Willett, P.; Klaffke, W.; van Noort, P. Evaluation of Similarity Measures for Searching the Dictionary of Natural Products Database. J. Chem. Inf. Comput. Sci. 2003, 43, 449-457.
7. Hen, J.; Willett, P.; Wilton, D. J.; Acklin, P.; Azzaoui, K.; Jacoby, E.; Schuffenhauer, A. Comparison of Fingerprint-Based Methods for Vvirtual Screening Using Multiple Bioactive Reference Structures. J. Chem. Inf. Comput. Sci. 2004, 44, 1177-1185.
8. Whittle, M.; Gillet, V. J.; Willet, P.; Loesel, J.; Alexander, A. Enhancing the Effectiveness of Virtual Screening by Fusing Nearest-Neighbour Lists: A Comparison of Similarity Coefficients. J. Chem. Inf. Comput. Sci. 2004, 44, 1840-1848.
9. Whittle, M.; Gillet, V. J.; Willett, P.; Loesel, J. Analysis of Data Fusion Methods in Virtual Screening: Theoretical Model. J. Chem. Inf. Model. 2006, 46, 2193-2205.
10. The MDL Drug Data Report database is available from MDL Information Systems at URL http://www.mdl.com/.
11. The BCI software is available from Digital Chemistry Ltd. at URL http://www.digitalchemistry.co.uk.
12. The Pipeline Pilot software is available from Scitegic Inc. at URL http://www.scitegic.com.
13. Fligner, M. A.; Verducci, J. S.; Blower, P. E. A Modification of the Jaccard-Tanimoto Similarity Index for Diverse Selection of Chemical Compounds Using Binary Strings. Technometrics 2002, 44, 110-119.
14. Holliday, J. D.; Salim, N.; Whittle, M.; Willett, P. Analysis and Display of the Size Dependence of Chemical Similarity Coefficients. J. Chem. Inf. Comput. Sci. 2003, 43, 819-828.
15. Salim, N.; Holliday, J.; Willett, P. Combination of Fingerprint-Based Similarity Coefficients Using Data Fusion. J. Chem. Inf. Comput. Sci. 2003, 43, 435-440.
16. Beitzel, S. M.; Jensen, E. C.; Chowdhury, A.; Grossman, D.; Goharian, N.; Frieder, O. Fusion of Effective Retrieval Strategies in the Same Information Retrieval System. J. Am. Soc. Inf. Sci. Tech. 2004, 55, 859-868.
17. Ng, K. B.; Kantor, P. B. Predicting the Effectiveness of Naïve Data Fusion on the Basis of System Characteristics. J. Am. Soc. Inf. Sci. 2000, 51, 1177-1189.
18. Wilton, D.; Willett, P.; Lawson, K.; Mullier, G. Comparison of Ranking Methods for Virtual Screening in Lead-Discovery Programs. J. Chem. Inf. Comput. Sci. 2003, 43, 469-474.
19. Glick, M.; Klon, A. E.; Acklin, P.; Davies, J. W. Enrichment of Extremely Noisy High-Throughput Screening Data Using a Naive Bayes Classifier. J. Biomol. Screening 2004, 9, 32-36.
20. Saeh, J. C.; Lyne, P. D.; Takasaki, B. K.; Cosgrove, D. A. Lead Hopping Using SVM and 3D Pharmacophore Fingerprints, J. Chem. Inf. Model. 2005, 45, 1122-1133.