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Research Article

Estimation of Aqueous Solubility for a Diverse Set of Organic Compounds Based on Molecular Topology

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Jarmo Huuskonen^†

Division of Pharmaceutical Chemistry, Department of Pharmacy, POB 56, FIN-00014, University of Helsinki, Finland

J. Chem. Inf. Comput. Sci., 2000, 40 (3), pp 773–777

DOI: 10.1021/ci9901338

Publication Date (Web): February 19, 2000

†

Tel: 358 9 19159170. FAX: 358 9 19159556. E-mail: jarmo.huuskonen@helsinki.fi.

Abstract

An accurate and generally applicable method for estimating aqueous solubilities for a diverse set of 1297 organic compounds based on multilinear regression and artificial neural network modeling was developed. Molecular connectivity, shape, and atom-type electrotopological state (E-state) indices were used as structural parameters. The data set was divided into a training set of 884 compounds and a randomly chosen test set of 413 compounds. The structural parameters in a 30−12−1 artificial neural network included 24 atom-type E-state indices and six other topological indices, and for the test set, a predictive r² = 0.92 and s = 0.60 were achieved. With the same parameters the statistics in the multilinear regression were r² = 0.88 and s = 0.71, respectively.

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History

Published In Issue May 22, 2000
Received October 21, 1999

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Research Article

Estimation of Aqueous Solubility for a Diverse Set of Organic Compounds Based on Molecular Topology

Abstract

Tools

SciFinder Links

History

Recommend & Share

Related Content

ESOL: Estimating Aqueous Solubility Directly from Molecular Structure

Estimation of Aqueous Solubility of Chemical Compounds Using E-State Indices

ADME Evaluation in Drug Discovery. 4. Prediction of Aqueous Solubility Based on Atom Contribution Approach

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