The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
The Importance of Being Earnest: Validation is the Absolute Essential for Successful Application and Interpretation of QSPR Models
Abstract
This paper emphasizes the importance of rigorous validation as a crucial, integral component of Quantitative Structure Property Relationship (QSPR) model development. We consider some examples of published QSPR models, which in spite of their high fitted accuracy for the training sets and apparent mechanistic appeal, fail rigorous validation tests, and, thus, may lack practical utility as reliable screening tools. We present a set of simple guidelines for developing validated and predictive QSPR models. To this end, we discuss several validation strategies including (1) randomization of the modelled property, also called Y‐scrambling, (2) multiple leave‐many‐out cross‐validations, and (3) external validation using rational division of a dataset into training and test sets. We also highlight the need to establish the domain of model applicability in the chemical space to flag molecules for which predictions may be unreliable, and discuss some algorithms that can be used for this purpose. We advocate the broad use of these guidelines in the development of predictive QSPR models.
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Cites
Cramer, R. D., Patterson, D. E., & Bunce, J. D. (1988) · Journal of the American Chemical Society · doi:10.1021/ja00226a005 · Cited by 3,931
Golbraikh, A., & Tropsha, A. (2002) · Journal of Molecular Graphics and Modelling · doi:10.1016/s1093-3263(01)00123-1 · Cited by 3,735
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Cited by
Eriksson, L., Jaworska, J., Worth, A. P., Cronin, M. T. D., McDowell, R. M., & Gramatica, P. (2003) · Environmental Health Perspectives · doi:10.1289/ehp.5758 · Cited by 1,325
Self-citationMuratov, E. N., Bajorath, J., Sheridan, R. P., Tetko, I. V., Filimonov, D., Poroikov, V., Oprea, T. I., Baskin, I. I., Varnek, A., Roitberg, A., et al. (2020) · Chemical Society Reviews · doi:10.1039/d0cs00098a · Cited by 913
Self-citationNetzeva, T. I., Worth, A. P., Aldenberg, T., Benigni, R., Cronin, M. T. D., Gramatica, P., Jaworska, J. S., Kahn, S., Klopman, G., Marchant, C. A., et al. (2005) · Alternatives to Laboratory Animals · doi:10.1177/026119290503300209 · Cited by 836
Self-citationConvolutional embedding of attributed molecular graphs for physical property prediction
Coley, C. W., Barzilay, R., Green, W. H., Jaakkola, T. S., & Jensen, K. F. (2017) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.6b00601 · Cited by 470
How not to develop a quantitative structure–activity or structure–property relationship (QSAR/QSPR)
Dearden, J. C., Cronin, M. T. D., & Kaiser, K. L. E. (2009) · SAR and QSAR in Environmental Research · doi:10.1080/10629360902949567 · Cited by 468
Metadata
- Authors
- Tropsha, A., Gramatica, P., & Gombar, V. K.
- Venue
- QSAR & Combinatorial Science
- Publisher
- Wiley
- Published
- 2003-04
- Volume
- 22
- Issue
- 1
- Pages
- 69-77
- ISSN
- 1611-020X (ISSN-L)
- 1611-0218
- OpenAlex
- W2074681440
- Cited by
- 2,188
- References
- 2
- FWCI
- 33.87
- Type
- journal article
- Language
- en
- Open access
- closed
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- Tropsha, A., Gramatica, P., & Gombar, V. K. (2003). The Importance of Being Earnest: Validation is the Absolute Essential for Successful Application and Interpretation of QSPR Models. QSAR & Combinatorial Science. https://doi.org/10.1002/qsar.200390007
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