#### Filter Results:

#### Publication Year

1998

2003

#### Publication Type

#### Co-author

#### Publication Venue

Learn More

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)

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)

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)

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)

- ‹
- 1
- ›