Regression model (regression)
Open in:QDB ExplorerQDB Predictor
Name | Type | n |
R2 |
σ |
---|---|---|---|---|
Training set | training | 44 | 0.825 | 0.451 |
Validation set | external validation | 14 | 0.620 | 0.615 |
External validation set | external validation | 15 | 0.663 | 0.555 |
When using this QDB archive, please cite (see details) it together with the original article:
Oja, M.; Maran, U. Data for: The permeability of artificial membrane for the wide range of pH in human gastrointestinal tract: experimental measurements and quantitative structure-activity relationship. QsarDB repository, QDB.137. 2015. https://doi.org/10.15152/QDB.137
Oja, M.; Maran, U. The permeability of artificial membrane for the wide range of pH in human gastrointestinal tract: experimental measurements and quantitative structure-activity relationship. Mol. Inform. 2015, 34, 493–506. https://doi.org/10.1002/minf.201400147
Title: | Oja, M.; Maran, U. The permeability of artificial membrane for the wide range of pH in human gastrointestinal tract: experimental measurements and quantitative structure-activity relationship. Mol. Inf. 2015, 34, 493–506. |
Abstract: | In silico models for membrane permeability have been based on values measured for single pH. Depending on the diet (fasted/fed state) and part of human intestinal the range of pH varies approximately from 2.4 to 8.0. This motivated to study and model membrane permeability of chemicals considering range of pH in the human intestinal. For this effective membrane permeability values were measured for 65 drugs and drug-like compounds using parallel artificial membrane permeability assay (PAMPA) at four pH-s (3, 5, 7.4 and 9) over 48 hours, introducing technological innovations for the time-dependence measurement. The highest permeability value of compound from four pH-s was used to derive quantitative structure-activity relationship (QSAR) analyzing large pool of molecular descriptors and introducing one new descriptor. Using stepwise forward selection approach significant QSAR model was derived that included only two mechanistically relevant descriptors, the logarithmic octanol-water partition coefficient and hydrogen bonding surface area. Prediction confidence of the model was blind tested (first predicted and then measured) with true external validation set of 15 compounds. Resulting QSAR model shows potential to combine permeability values from various pH-s to one descriptive and predictive model for estimating maximum permeability in human intestinal. QSAR model and underlined data in the manuscript is available on-line through QsarDB repository. |
URI: | http://hdl.handle.net/10967/137
http://dx.doi.org/10.15152/QDB.137 |
Date: | 2015-02-26 |
Funding: | Estonian Ministry for Education and Research (Grants SF0140031Bs09, IUT34-14) and Estonian Research Council (Grant 7709) |
Name | Description | Format | Size | View |
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2015MI.qdb.zip | QSAR model for membrane permeability | application/zip | 84.85Kb | View/ |