Permeability and Efflux Prediction
Predict Caco-2 and MDCK permeability and efflux from small-molecule structures.
Overview
Predict epithelial permeability and efflux for small molecules with the published four-task GNN-MTL model. The model estimates Caco-2 efflux ratio and apparent permeability, MDCK efflux ratio, and NIH-MDCK efflux ratio from molecular structure.
Run Permeability and Efflux Prediction on Neurosnap
The Permeability and Efflux Prediction online webserver allows anybody with a Neurosnap account to run and access Permeability and Efflux Prediction, no downloads required. Information submitted through this webserver is kept confidential and never sold to third parties as detailed by our strong Terms of Use and Privacy Policy.
Features
- Predicts Caco-2 efflux ratio and apparent permeability alongside MDCK and NIH-MDCK efflux ratios.
- Accepts batches of SMILES, SDF, or CCD molecules through the standard molecule input.
- Returns a single sortable CSV table with all four assay endpoints and their units.
Statistics
Neurosnap periodically calculates runtime statistics based on job execution data. These estimates provide a general guideline for how long your job may take, but actual runtimes can vary significantly depending on factors like input size or settings used.
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API Request
Access Permeability and Efflux Prediction using the Neurosnap API by sending a request using any programming language with HTTP support. To safely generate an API key, visit the API tab of your overview page.
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Citations
Please cite the original work when using Permeability and Efflux Prediction in publications or research outputs.
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Ivers Ohlsson P, Ghiandoni GM, Winiwarter S, Mercado R, Subramanian V. Prediction of Permeability and Efflux Using Multitask Learning. ACS Omega. 2025;10(45):54148-54159. https://doi.org/10.1021/acsomega.5c04861 |
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Ivers Ohlsson P, et al. GNN-MTL permeability model. Zenodo. 2025. https://doi.org/10.5281/zenodo.16948542 |
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Neurosnap Inc. (2022). Neurosnap: An online platform for computational biology and chemistry. Available at: https://neurosnap.ai/ |