Application note 15/14
Determination of pKa: Measurement or Prediction?
The absorption and delivery of drugs are affected by the
ionisation state of the drug molecule at different pH
values, and this ionisation is described by the drug’s pKa
values. It is therefore important to have reliable pKa
values for compound assessment. People often use
predicted values, especially when screening new or virtual
compounds and the latest generation of prediction
models have greatly improved. Sirius has extensive
experience in measuring pKa values of novel drugs for
our Analytical Service customers. Where we know the
compound’s structure, we use computational methods to
predict the number of pKas and the type (acidic or
basic); this information helps us to design optimal
experiments.
Error in precicted pK a
3
2
O
OH
N
Cl
Predicted1: 3.5
Measured: 8.1
Figure 1. Chlorzoxazone predicted and measured pKa values
Common drug compounds
Compounds containing common chemical groups and
functionalities generally yield relatively accurate pKa
predictions. Warfarin, for example, has a measured
acidic pKa of 4.93, which aligns with a predicted value
of 4.51. Some additional examples of successful pKa
predictions are shown in Table 1.
1
0
-1
-2
Acidic pKas
Basic pKas
-3
0
2
4
6
8
Measured pK a
10
12
14
Compound
Propranolol
Imipramine
Diclofenac
Dipyridamole
Predicted pKa1
9.5
9.5
4.2
6.5
Measured pKa
9.49
9.44
4.06
6.20
Table 1. Common drug compounds with accurate pKa predictions
Chlorzoxazone
We analysed data for 64 samples with known
structure (some with multiple pKas) measured for 22
customers in 2013, and compared our results with the
predicted pKas. Most predicted values were within ± 2 of
the measured values. However, these predicted values
may not be considered sufficiently reliable, especially for
decision-making as drugs progress from discovery to
development. We have found that for some chemical
functionalities the agreement between predicted values
and measured values is relatively poor. This application
note highlights some of these cases and demonstrates
that for definitive pKa determination, measurement
is critical.
The pKa prediction for the muscle relaxant chlorzoxazone
is less well handled by computational pKa approaches.
Chlorzoxazone is a small molecule with only one
ionisable group. Although these types of molecule
typically predict very well, in this case the predicted
value of 3.5 is far-removed from the measured value of
8.13, a difference of 4.6 pH units. Using a different
prediction module does give a closer value of 6.72, but
this is still 1.4 pH units away from the actual value.
This is an extreme example of a failed prediction; most
software will reliably predict within ±2 pH units. However,
larger differences have been observed in the compounds
we measure for our Analytical Service customers.
Sirius Analytical e sales@sirius-ai.com w www.sirius-analytical.com t 978 338 5790
Application note 15/14
“...Sirius has extensive experience in measuring pKa values of novel drugs for
our Analytical Service customers...”
Amiloride
N
Amiloride also presents a problem for some prediction
software. The predicted pKa at 7.81 isrelatively close to
the measured value of 8.6, however, the prediction
software ascribes the pKa as acidic. This is probably
because the ionisable centre in question is part of an
amide linking group; these groups are normally weak
acids. Amiloride is, in fact, formulated as a hydrochloride
salt and the pKa is basic. We have confirmed with
Yasuda-Shedlovsky extrapolation by observing the shift
of the aqueous pKa in different concentrations of
methanol. Using a different prediction module does give
the correct pKa assignment, with a more accurate value
(Base at 9.02).
N
N
O
Cl
O
O
H
Cl
N
N
O
H3C
N
N
H3C
N
Predicted1: 2.9, 3.6, 6.5
Measured: 3.9
Figure 3. Itraconazole predicted and measured pKa values.
O
Cl
NH
N
NH
H 2N
N
N H2
N H2
Predicted1: 7.8 Acid
Measured: 8.6 Base
Figure 2. Amiloride predicted and measured pKa values.
Itraconazole
Sometimes it is also possible for prediction software to
appear to predict pKas that do not exist. For example,
Itraconazole is predicted to have three pKas at 2.9, 3.6
and 6.51. However, although we observe a pKa at 3.9, we
have never seen any evidence of pKas at or around 2.9
or 6.5 using either industry-standard UV or pH-metric
methods.
In this case, alternate prediction modules give no
further clues, predicting pKas of 2.3 and 5.52. This may
be because the pKas are actually much lower than
predicted; the predicted pKa at 6.5 could be the one we
observed at 3.9, and the predicted value at 3.6 may be
lower than our typical analytical range (2.0 - 12.0).
Nonetheless, it serves to illustrate how inaccurate
predictions can be misleading.
Conclusion
Although computational methods are capable of
generating comprehensive pKa data that can be used to
infer compound behaviour, they should not be considered
a substitute for measuring the pKa. With any prediction
there will always be an associated error of varying
magnitude which could lead to suboptimal
physicochemical profiling.
References
1
2
ACD/Labs 2012 Percepta © (Classic pKa) Build 2726, May 14
ACD/Labs 2012 Percepta © (GALAS pKa) Build 2726, May 14
Sirius Analytical e sales@sirius-ai.com w www.sirius-analytical.com t 978 338 5790