pKa prediction method

The pKa of a chemical compounds strongly infuences its pharmacokinetic and biochemical properties. It reflects the ionization state, which in turn affects lipophilicity, solubility, protein binding, ability to cross the plasma membrane and the blood–brain barrier, absorption, distribution, metabolism, excretion, and toxicity properties and is considered one of the most important parameters in drug discovery.
pKa prediction is challenging because a single chemical can have multiple ionization sites. The method of pKa prediction using a set of decision trees might be a good choice for a wide range of chemical compounds.

No files, tests, or entry points are named in the issue. Start by reviewing the Indigo API and existing prediction-related functionality, then clarify the decision-tree method, supported compounds, expected inputs and outputs, and validation criteria before implementation.

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