PyPermM Membrane Permeability
Estimate passive membrane permeability and insertion energy from 3D molecular structure.
Overview
Estimate passive membrane permeability from three-dimensional small-molecule structure using PyPermM, a Python implementation of the physics-based PerMM method. The service reports insertion energy and intrinsic permeability estimates for black lipid, plasma, blood-brain barrier, Caco-2, and PAMPA membranes.
Run PyPermM Membrane Permeability on Neurosnap
The PyPermM Membrane Permeability online webserver allows anybody with a Neurosnap account to run and access PyPermM Membrane Permeability, 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 intrinsic passive permeability for five membrane systems and reports membrane binding energy.
- Preserves supplied 3D SDF coordinates or generates a reproducible conformer from SMILES or CCD input.
- Exports an insertion-energy profile through the membrane for each molecule.
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 PyPermM Membrane Permeability 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 PyPermM Membrane Permeability in publications or research outputs.
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Lomize AL, Hage JM, Schnitzer K, et al. PerMM: A Web Tool and Database for Analysis of Passive Membrane Permeability and Translocation Pathways of Bioactive Molecules. Journal of Chemical Information and Modeling. 2019;59(7):3094-3099. https://doi.org/10.1021/acs.jcim.9b00225 |
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Wagen C. PyPermM: permeability modeling made easy. https://github.com/rowansci/pypermm |
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Neurosnap Inc. (2022). Neurosnap: An online platform for computational biology and chemistry. Available at: https://neurosnap.ai/ |