Isoelectric Point Calculator
Sort the pKa values rather than labelling them — tyrosine is the case where the usual shortcut fails.
The formula
pI = average of the two pKa values flanking the neutral form
Which two pKa values
At the isoelectric point the molecule carries no net charge, and the pI is the average of the two ionisations either side of that neutral form. For an amino acid with an inert side chain those are simply the carboxyl and the amino group, giving glycine a pI of 5.97.
Sort the pKa values, do not label them
The usual shortcut says an acidic side chain pairs with the carboxyl and a basic one with the amino group. It works for aspartate, whose pI is (1.88 + 3.65)/2 = 2.77, and for lysine at (8.95 + 10.53)/2 = 9.74. It fails for tyrosine: its phenol side chain is acidic but its pKa of 10.07 sits ABOVE the amino group's 9.11, so it is the last proton to leave rather than the second. The shortcut gives 6.14 where the real value is 5.66.
Sorting works in every case. Count the groups that carry a positive charge when protonated — the amino group, plus a basic side chain if there is one. That is how many protons must come off to reach neutrality, and the pKa values either side of that step are the pair to average, whatever chemical class they belong to.
Why it is the number that matters
A protein is least soluble at its pI, because with no net charge there is nothing to keep molecules apart and they aggregate. That is the basis of isoelectric precipitation, and it is why casein drops out of milk at pH 4.6. It is also why electrophoresis works: at any other pH the molecule carries charge and moves in a field, in a direction the pI predicts.
Where these models stop
Michaelis-Menten assumes a single substrate and a steady state; Langmuir assumes one layer on identical sites with no interaction between them; Stokes-Einstein assumes a hard sphere much larger than the solvent molecules around it. Each is an idealisation that happens to describe real systems well over a useful range, and each fails predictably outside it. Knowing which assumption a number rests on is usually more valuable than the number.