This model employs transfer learning with graph neural networks in order to predict micro-state pKa values of small molecules. The model enumerates the molecule's protonation states and predicts its pKa values. It was trained in two phases, first, using a large ChEMBL dataset and then fine-tuning the model for a small training set of molecules with available pKa values. The model in this repository is the pkasolver-light, which does not require an Epik license and is limited to monoprotic molecules.
eos2b6f
pkasolver
Compound
Single
Regression
Experimental value
Float
Single
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