Introduction of r m 2 (rank) metric incorporating rank-order predictions as an additional tool for validation of QSAR/QSPR models

Chemometrics and Intelligent Laboratory Systems

Volumn 118, Issue , 2012, Pages 200-210

  Roy, Kunal ^a   Mitra, Indrani ^a   Ojha, Probir Kumar ^a   Kar, Supratik ^a   Das, Rudra Narayan ^a   Kabir, Humayun ^a  

^a JADAVPUR UNIVERSITY   (India)

Author keywords

Pearson's correlation coefficient; QSAR; QSPR; QSTR; Spearman's rank correlation coefficient; Validation

Indexed keywords

CHEMICAL COMPOUND;

ALGORITHM; ARTICLE; CALCULATION; COMPUTER MODEL; CONTROLLED STUDY; CORRELATION ANALYSIS; CORRELATION COEFFICIENT; MEASUREMENT; PREDICTION; PRIORITY JOURNAL; QUANTITATIVE ANALYSIS; QUANTITATIVE STRUCTURE ACTIVITY RELATION; QUANTITATIVE STRUCTURE PROPERTY RELATION; RANK ORDER PREDICTION; REGRESSION ANALYSIS; RM2(RANK) METRIC; STATISTICAL ANALYSIS; TOXICITY; VALIDATION PROCESS;

EID: 84868210651     PISSN: 01697439     EISSN: 18733239     Source Type: Journal    
DOI: 10.1016/j.chemolab.2012.06.004     Document Type: Article

References (31)

1. Buchwald P., Bodor N. Computer-aided drug design: the role of quantitative structure-property, structure-activity and structure-metabolism relationships. Drugs Future 2002, 27:577-588.
2. Huang H.J., Yu H.W., Chen C.Y., Hsu C.H., Chen H.Y., Lee K.J., Tsai F.J., Chen C.Y.C. Current developments of computer-aided drug design. Journal of Taiwan Institute of Chemistry Engineering 2010, 41:623-635.
3. Sprous D.G., Palmer R.K., Swanson J.T., Lawless M. QSAR in the pharmaceutical research setting: QSAR models for broad, large problems. Current Topics in Medicinal Chemistry 2010, 10:619-637.
4. Tropsha A., Gramatica P., Gombar V.K. The importance of being earnest: validation is the absolute essential for successful application and interpretation of QSPR models. QSAR and Combinatorial Science 2003, 22:69-77.
5. Hu J., Zhang X., Wang Z. A review on progress in QSPR studies for surfactants. International Journal of Molecular Sciences 2010, 11:1020-1047.
6. Duchowicz P.R., Castro E.A. QSPR studies on aqueous solubilities of drug-like compounds. International Journal of Molecular Sciences 2009, 10:2558-2577.
7. Kar S., Roy K. Predictive toxicology using QSAR: a perspective. Journal of the Indian Chemical Society 2010, 87:1455-1515.
8. Dearden J.C., Cronin M.T.D., Kaiser K.L.E. How not to develop a quantitative structure-activity or structure-property relationship (QSAR/QSPR). SAR and QSAR in Environmental Research 2009, 20:241-266.
9. Tropsha A. Best practices for QSAR model development, validation, and exploitation. Mol. Inf. 2010, 29:476-488.
10. Scior T., Medina-Franco J.L., Do Q.T., Martínez-Mayorga K., Rojas J.A.Y., Bernard P. How to recognize and workaround pitfalls in QSAR studies: a critical review. Current Medicinal Chemistry 2009, 16:4297-4313.
11. Roy P.P., Leonard J.T., Roy K. Exploring the impact of the size of training sets for the development of predictive QSAR models. Chemometrics and Intelligent Laboratory Systems 2008, 90:31-42.
12. Roy K. On some aspects of validation of predictive quantitative structure-activity relationship models. Expert Opinion on Drug Discovery 2007, 2:1567-1577.
13. Snedecor G.W., Cochran W.G. Statistical Methods 1989, Iowa State University Press, Ames. 8th ed.
14. Consonni V., Ballabio D., Todeschini R. Evaluation of model predictive ability by external validation techniques. Journal of Chemometrics 2010, 24:194-201.
15. Schuurmann G., Ebert R.U., Chen J., Wang B., Kuhne R. External validation and prediction employing the predictive squared correlation coefficient: Test set activity mean vs training set activity mean. Journal of Chemical Information and Modeling 2008, 48:2140-2145.
16. McLellan M.R., Ryan M.D., Breneman C.M. Rank order entropy: why one metric is not enough. Journal of Chemical Information and Modeling 2011, 51:2302-2319.
17. Caruso J.C., Cliff N. Empirical size, coverage, and power of confidence intervals for spearman's rho, ed. and psy. Measurement 1997, 57:637-654.
18. Devlin S.J., Gnanadesikan R., Kettenring J.R. Robust estimation and outlier detection with correlation coefficients. Biometrika 1975, 62(3):531-545.
19. 2 metrics for validation of QSPR models dataset. Chemometrics and Intelligent Laboratory Systems 2011, 107:194-205.
20. Roy K., Mitra I., Kar S., Ojha P.K., Das R.N., Kabir H. Comparative studies on some metrics for external validation of QSPR models. Journal of Chemical Information and Modeling 2012, 52:396-408.
21. Toropov A.A., Toropova A.P., Benfenati E. QSPR modeling bioconcentration factor (BCF) by balance of correlations. European Journal of Medicinal Chemistry 2009, 44:2544-2551.
22. Zeng H., Zhang H. Combined 3D-QSAR modeling and molecular docking study on 1,4-dihydroindeno[1,2-c]pyrazoles as VEGFR-2 kinase inhibitors. Journal of Molecular Graphics Model 2010, 29:54-71.
23. Lu P., Wei X., Zhang R. CoMFA and CoMSIA 3D-QSAR studies on quionolone carboxylic acid derivatives inhibitors of HIV-1 integrase. European Journal of Medicinal Chemistry 2010, 45:3413-3419.
24. Deeb O., Khadikar P.V., Goodarzi M. QSPR modeling of bioconcentration factors of nonionic organic compounds. Environmental Health Insights 2010, 4:33-47.
25. Roy K., Paul S. Exploring 2D and 3D QSARs of 2,4-diphenyl-1,3-oxazolines for ovicidal activity against Tetranychus urticae. QSAR and Combinatorial Science 2009, 28:406-425.
26. Rogers D., Hopfinger A.J. Application of genetic function approximation to quantitative structure-activity relationships and quantitative structure-property relationships. Journal of Chemical Information and Computer Sciences 1994, 34:854-866.
27. Cerius2 Version 4.10 2005, Accelrys Inc, San Diego, CA, USA.
28. Everitt B.S., Landau S., Leese M. Cluster Analysis 2001, Edward Arnold, London.
29. SPSS is a statistical software of SPSS Inc., IL, USA, 1998.
30. Héberger K. Sum of ranking differences compares methods or models fairly. TrAC Trends in Analytical Chemistry 2010, 29:101-109.
31. Héberger K., Kollár-Hunek K. Sum of ranking differences for method discrimination and its validation: comparison of ranks with random numbers. Journal of Chemometrics 2010, 25:151-158.