| Download | - View accepted manuscript: Predicting PAMPA permeability using the 3D-RISM-KH theory: are we there yet? (PDF, 764 KiB)
- View supplementary information: Predicting PAMPA permeability using the 3D-RISM-KH theory: are we there yet? (XLSX, 223 KiB)
|
|---|
| DOI | Resolve DOI: https://doi.org/10.1007/s10822-020-00364-4 |
|---|
| Author | Search for: Roy, DipankarORCID identifier: https://orcid.org/0000-0002-4703-0130; Search for: Dutta, DevjyotiORCID identifier: https://orcid.org/0000-0002-2516-5624; Search for: Wishart, David S.ORCID identifier: https://orcid.org/0000-0002-3207-2434; Search for: Kovalenko, Andriy1ORCID identifier: https://orcid.org/0000-0001-5033-4314 |
|---|
| Affiliation | - National Research Council of Canada. Nanotechnology
|
|---|
| Format | Text, Article |
|---|
| Subject | PAMPA; 3D-RISM-KH; molecular solvation theory; machine learning; classification |
|---|
| Abstract | The parallel artificial membrane permeability assay (PAMPA), a non-cellular lab-based assay, is extensively used to measure the permeability of pharmaceutical compounds. PAMPA experiments provide a working mimic of a molecule passing through cells and PAMPA values are widely used to estimate drug absorption parameters. There is an increased interest in developing computational methods to predict PAMPA permeability values. We developed an in silico model to predict the permeability of compounds based on the PAMPA assay. We used the three-dimensional reference interaction site model (3D-RISM) theory with the Kovalenko–Hirata (KH) closure to calculate the excess chemical potentials of a large set of compounds and predicted their apparent permeability with good accuracy (mean absolute error or MAE = 0.69 units) when compared to a published experimental data set. Furthermore, our in silico PAMPA protocol performed very well in the binary prediction of 288 compounds as being permeable or impermeable (precision = 94%, accuracy = 93%). This suggests that our in silico protocol can mimic the PAMPA assay and could aid in the rapid discovery or screening of potentially therapeutic drug leads that can be delivered to a desired tissue. |
|---|
| Publication date | 2021-01-04 |
|---|
| Publisher | Springer |
|---|
| In | |
|---|
| Language | English |
|---|
| Peer reviewed | Yes |
|---|
| NRC number | NRC-NANO-108 |
|---|
| Export citation | Export as RIS |
|---|
| Report a correction | Report a correction (opens in a new tab) |
|---|
| Record identifier | 7f9f0814-e0ea-493d-a05f-3cd5d42d4a5c |
|---|
| Record created | 2021-02-24 |
|---|
| Record modified | 2021-02-24 |
|---|
