The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
ESOL: Estimating Aqueous Solubility Directly from Molecular Structure
Abstract
This paper describes a simple method for estimating the aqueous solubility (ESOL--Estimated SOLubility) of a compound directly from its structure. The model was derived from a set of 2874 measured solubilities using linear regression against nine molecular properties. The most significant parameter was calculated logP(octanol), followed by molecular weight, proportion of heavy atoms in aromatic systems, and number of rotatable bonds. The model performed consistently well across three validation sets, predicting solubilities within a factor of 5-8 of their measured values, and was competitive with the well-established "General Solubility Equation" for medicinal/agrochemical sized molecules.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
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
Daina, A., Michielin, O., & Zoete, V. (2017) · Scientific Reports · doi:10.1038/srep42717 · Cited by 18,367
MoleculeNet: a benchmark for molecular machine learning
Wu, Z., Ramsundar, B., Feinberg, E. N., Gomes, J., Geniesse, C., Pappu, A. S., Leswing, K., & Pande, V. (2018) · Chemical Science · doi:10.1039/c7sc02664a · Cited by 3,107
Convolutional Networks on Graphs for Learning Molecular Fingerprints
Duvenaud, D., Maclaurin, D., Aguilera-Iparraguirre, J., Gómez-Bombarelli, R., Hirzel, T., Aspuru-Guzik, A., & Adams, R. P. (2015) · arXiv · doi:10.48550/arxiv.1509.09292 · Cited by 2,628
Adaptive Graph Convolutional Neural Networks
Li, R., Wang, S., Zhu, F., & Huang, J. (2018) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v32i1.11691 · Cited by 842
Jiang, D., Wu, Z., Hsieh, C.-Y., Chen, G., Liao, B., Wang, Z., Shen, C., Cao, D., Wu, J., & Hou, T. (2021) · Journal of Cheminformatics · doi:10.1186/s13321-020-00479-8 · Cited by 664
Metadata
- Authors
- Delaney, J. S.
- Venue
- Journal of Chemical Information and Computer Sciences
- Publisher
- American Chemical Society (ACS)
- Published
- 2004-03-13
- Volume
- 44
- Issue
- 3
- Pages
- 1000-1005
- ISSN
- 0095-2338 (ISSN-L)
- OpenAlex
- W2076498053
- Cited by
- 1,091
- References
- 1
- FWCI
- 7.14
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: ESOL: Estimating Aqueous Solubility Directly from Molecular Structure. https://app.cochat.ai/papers/10.1021/ci034243x
- The paper
- Delaney, J. S. (2004). ESOL: Estimating Aqueous Solubility Directly from Molecular Structure. Journal of Chemical Information and Computer Sciences. https://doi.org/10.1021/ci034243x
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
