The pH-dependent charge distribution of proteins affects interactions that span the entire gamut of length scales in chemistry, from the hydration state to gelation . The isoelectric point (pI), where the protein has zero net charge, plays important roles in selective extraction , separation and identification (4, 5) of proteins. Estimating protein pI values from amino acid (AA) sequences can be done by simple optimization schemes that obtain approximate constants used to calculate the protonation state of the seven basic and acidic AAs, as well as the carboxylate and ammonium termini . Such estimates of only nine dissociation constants ignore all environmental effects of the primary, secondary and tertiary protein structures on individual acid dissociation constants. Attempts to improve on such naive calculations have included application of convolutional neural networks and support vector machines .