The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Structure−Activity Landscape Index: Identifying and Quantifying Activity Cliffs
Abstract
A new method for analyzing a structure-activity relationship is proposed. By use of a simple quantitative index, one can readily identify "structure-activity cliffs": pairs of molecules which are most similar but have the largest change in activity. We show how this provides a graphical representation of the entire SAR, in a way that allows the salient features of the SAR to be quickly grasped. In addition, the approach allows us view the SARs in a data set at different levels of detail. The method is tested on two data sets that highlight its ability to easily extract SAR information. Finally, we demonstrate that this method is robust using a variety of computational control experiments and discuss possible applications of this technique to QSAR model evaluation.
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Citations
Cites
On Outliers and Activity CliffsWhy QSAR Often Disappoints
Maggiora, G. M. (2006) · Journal of Chemical Information and Modeling · doi:10.1021/ci060117s · Cited by 728
SAR Index: Quantifying the Nature of Structure−Activity Relationships
Peltason, L., & Bajorath, J. (2007) · Journal of Medicinal Chemistry · doi:10.1021/jm0705713 · Cited by 201
Cited by
QSAR Modeling: Where have you been? Where are you going to?
Cherkasov, A., Muratov, E. N., Fourches, D., Varnek, A., Baskin, I. I., Cronin, M., Dearden, J., Gramatica, P., Martin, Y. C., Todeschini, R., et al. (2014) · Journal of Medicinal Chemistry · doi:10.1021/jm4004285 · Cited by 2,164
Time-Split Cross-Validation as a Method for Estimating the Goodness of Prospective Prediction.
Sheridan, R. P. (2013) · Journal of Chemical Information and Modeling · doi:10.1021/ci400084k · Cited by 376
Exposing the Limitations of Molecular Machine Learning with Activity Cliffs
van Tilborg, D., Alenicheva, A., & Grisoni, F. (2022) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.2c01073 · Cited by 337
Computational Modeling of β-Secretase 1 (BACE-1) Inhibitors Using Ligand Based Approaches
Subramanian, G., Ramsundar, B., Pande, V., & Denny, R. A. (2016) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.6b00290 · Cited by 285
van Westen, G. J. P., Wegner, J. K., IJzerman, A. P., van Vlijmen, H. W. T., & Bender, A. (2011) · MedChemComm · doi:10.1039/c0md00165a · Cited by 176
Metadata
- Authors
- Guha, R., & Van Drie, J. H.
- Venue
- Journal of Chemical Information and Modeling
- Publisher
- American Chemical Society (ACS)
- Published
- 2008-02-28
- Volume
- 48
- Issue
- 3
- Pages
- 646-658
- ISSN
- 1549-9596 (ISSN-L)
- 1549-960X
- OpenAlex
- W2025556769
- Cited by
- 360
- References
- 2
- FWCI
- 33.53
- Type
- journal article
- Language
- en
- Open access
- closed
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