  Allosteric (long-range) interactions can be surprisingly strong in proteins
of biomedical interest. Here we use bioinformatic scaling to connect prior
results on nonsteroidal anti-inflammatory drugs to promising new drugs that
inhibit cancer cell metabolism. Many parallel features are apparent, which
explain how even one amino acid mutation, remote from active sites, can alter
medical results. The enzyme twins involved are cyclooxygenase (aspirin) and
isocitrate dehydrogenase (IDH). The IDH results are accurate to 1% and are
overdetermined by adjusting a single bioinformatic scaling parameter. It
appears that the final stage in optimizing protein functionality may involve
leveling of the hydrophobic cutoffs of the arms of conformational hydrophilic
hinges.
