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- Jarmo Huuskonen
- Journal of Chemical Information and Computer…
- 2000

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… (More)

- J Huuskonen, J Rantanen, D Livingstone
- European journal of medicinal chemistry
- 2000

We describe robust methods for estimating the aqueous solubility of a set of 734 organic compounds from different structural classes based on multiple linear regression (MLR) and artificial neural networks (ANN) model. The structures were represented by atom-type electrotopological state (E-state) indices. The squared correlation coefficient and standard… (More)

- J Huuskonen
- Environmental toxicology and chemistry
- 2001

Based on the atom-type electrotopological state (E-state) indices, a quantitative structure-property relationship model for the prediction of aqueous solubility for a diverse set of 745 organic compounds is presented. The multiple linear regression analysis was used to build the models. A training set of 674 compounds, containing 349 liquids and 325 solids… (More)

- Jarmo Huuskonen
- Chemosphere
- 2003

A quantitative structure-activity relationship model, based on the atom-type electrotopological state (E-state) indices, for the prediction of toxicity to fathead minnow for a diverse set of 140 organic chemicals is presented. Multiple linear regression and artificial neural network techniques were employed in the modeling of experimental toxicity… (More)

- Jarmo Huuskonen
- Journal of Chemical Information and Computer…
- 2003

A correlation study based on simple structural descriptors for predicting the soil sorption coefficient, log K(oc), of a diverse set of 568 organic compounds is presented. Using a training set of 403 compounds, in which the log K(oc) values were in the range 0-6.5, multiple linear regression (MLR) was utilized to build the models. The models were validated… (More)

- Jarmo Huuskonen
- Environmental toxicology and chemistry
- 2003

A group contribution approach based on atom-type electrotopological state indices for predicting the soil sorption coefficient (log KOC) of a diverse set of 201 organic pesticides is presented. Using a training set of 143 compounds, for which the log KOC values were in the range from 0.42 to 5.31, multiple linear regression (MLR) and artificial neural… (More)

- Jarmo Huuskonen, Marja Salo, Jyrki Taskinen
- Journal of Chemical Information and Computer…
- 1998

A method for predicting the aqueous solubility of drug compounds was developed based on topological indices and artificial neural network (ANN) modeling. The aqueous solubility values for 211 drugs and related compounds representing acidic, neutral, and basic drugs of different structural classes were collected from the literature. The data set was divided… (More)

- J Huuskonen, M Salo, J Taskinen
- Journal of pharmaceutical sciences
- 1997

The ability of neural network models to predict aqueous solubility within series of structurally related drugs was evaluated. Three sets of compounds representing different drug classes (28 steroids, 31 barbituric acid derivatives, and 24 heterocyclic reverse transcriptase inhibitors) were studied. Topological descriptors (connectivity indices, kappa… (More)

- Jarmo Huuskonen
- Journal of Chemical Information and Computer…
- 2001

Quantitative structure-activity relationships (QSAR), based on the atom level E-state indices and calculated molecular properties (log P, MR), have been developed for the affinity of a large set of TIBO derivatives against HIV-1 reverse transcriptase (HIV-1 RT) utilizing multiple linear regression techniques. A model with five descriptors, including four… (More)

- J Huuskonen
- Combinatorial chemistry & high throughput…
- 2001

The solubility of drugs in water is of central importance in the process of drug discovery and development from molecular design to pharmaceutical formulation and biopharmacy. The ability to estimate the aqueous solubility and other properties of a promising lead compound affecting its pharmacokinetics is a prerequisite to rational drug design, although it… (More)