The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Solubility Challenge: Can You Predict Solubilities of 32 Molecules Using a Database of 100 Reliable Measurements?
Abstract
Solubility is a key physicochemical property of molecules. Serious deficiencies exist in the consistency and reliability of solubility data in the literature. The accurate prediction of solubility would be very useful. However, systematic errors and lack of metadata associated with measurements greatly reduce the confidence in current models. To address this, we are accurately measuring intrinsic solubility values, and here we report results for a diverse set of 100 druglike molecules at 25 degrees C and an ionic strength of 0.15 M using the CheqSol approach. This is a highly reproducible potentiometric technique that ensures the thermodynamic equilibrium is reached rapidly. Results with a coefficient of variation higher than 4% were rejected. In addition, the Potentiometric Cycling for Polymorph Creation method, [PC] (2), was used to obtain multiple polymorph forms from aqueous solution. We now challenge researchers to predict the intrinsic solubility of 32 other druglike molecules that have been measured but are yet to be published.
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Cites
Lipinski, C. A., Lombardo, F., Dominy, B. W., & Feeney, P. J. (2001) · Advanced Drug Delivery Reviews · doi:10.1016/s0169-409x(00)00129-0 · Cited by 18,139
Cited by
Fourches, D., Muratov, E., & Tropsha, A. (2010) · Journal of Chemical Information and Modeling · doi:10.1021/ci100176x · Cited by 832
Lusci, A., Pollastri, G., & Baldi, P. (2013) · Journal of Chemical Information and Modeling · doi:10.1021/ci400187y · Cited by 555
In silico ADME/T modelling for rational drug design
Wang, Y., Xing, J., Xu, Y., Zhou, N., Peng, J., Xiong, Z., Liu, X., Luo, X., Luo, C., Chen, K., et al. (2015) · Quarterly Reviews of Biophysics · doi:10.1017/s0033583515000190 · Cited by 367
Metadata
- Authors
- Llinàs, A., Glen, R. C., & Goodman, J. M.
- Venue
- Journal of Chemical Information and Modeling
- Publisher
- American Chemical Society (ACS)
- Published
- 2008-07-01
- Volume
- 48
- Issue
- 7
- Pages
- 1289-1303
- ISSN
- 1549-9596 (ISSN-L)
- 1549-960X
- OpenAlex
- W2061481072
- Cited by
- 204
- References
- 1
- FWCI
- 7.41
- Type
- journal article
- Language
- en
- Open access
- closed
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- Llinàs, A., Glen, R. C., & Goodman, J. M. (2008). Solubility Challenge: Can You Predict Solubilities of 32 Molecules Using a Database of 100 Reliable Measurements? Journal of Chemical Information and Modeling. https://doi.org/10.1021/ci800058v
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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
