MolGpKa
Site-level molecular pKa prediction.
Overview
Predict site-level acidic and basic pKa values with the pretrained MolGpKa graph-convolutional models. The service standardizes neutralizable molecules and reports the ionizable heavy atom using explicit atom-map numbers. Basic-site predictions require benchmark review before release; local upstream inference produced implausible results for some simple amines. Predictions do not include pH-dependent populations or macroscopic titration curves.
Run MolGpKa on Neurosnap
The MolGpKa online webserver allows anybody with a Neurosnap account to run and access MolGpKa, 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
- Acidic and basic site predictions using the upstream checkpoints.
- Mapped SMILES identify the heavy atom associated with each predicted pKa.
- Explicit reporting of molecules without recognized ionization sites.
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 MolGpKa 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 MolGpKa in publications or research outputs.
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https://doi.org/10.1021/acs.jcim.1c00075 |
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Neurosnap Inc. (2022). Neurosnap: An online platform for computational biology and chemistry. Available at: https://neurosnap.ai/ |