Consequently, many different combinations
of enthalpy and entropy changes can result
in the same change in Gibbs energy and elicit
the same binding affinity. Most drug-design
strategies optimize the binding affinity to
minimize the amount of a drug needed
while maintaining potency. Achievement of
tight binding requires optimization of both
the enthalpic and entropic components that
arise from different interactions between the
drug and protein (Freire 2004).
Let us consider the different possible
interactions that influence the binding of a drug to a targeted protein
(Figure 3.6). Upon binding to the protein, the protein may change either
its conformation or the protonation state of the amino acid residues located
at the binding site. Such protein-related changes are an important aspect
of binding and contribute to the resulting change in enthalpy. However, the
preferred approach for drug design is to target favorable enthalpy changes
that are specific to the drug, such as formation of hydrogen bonds and van
der Waals’ contacts. Desolvation of polar groups upon binding represents
an unfavorable enthalpic contribution that should be compensated for by
the favorable interactions. The entropy will change due to two contribu-
tions. Before binding, the ligand is solvated and the empty binding site
will contain water. Upon binding, water is released resulting in a favorable
entropiccontribution. However, binding may also result in the loss of the
conformations available and so decrease the number of degrees of freedom
and hence an yield an unfavorable entropic change. This unfavorable con-
tribution can be minimized by considerations of the drug’s flexibility.
In optimization studies of drugs, the initial studies usually focus on optim-
ization of the binding affinity. By measuring the temperature dependence
of the binding affinity, the enthalpic and entropic contributions can be
identified individually. Drugs that are selected based upon enthalpic optim-
ization are usually more selective, with a higher binding affinity than that
obtained using entropic optimization. The higher affinity is due to the
less-specific nature of hydrophobic interactions that strongly influence
entropy changes. Therefore, enthalpically driven drugs have in general a
better potential and should be preferred for optimization.
Among the questions concerning drug design is how to design a mole-
cule that recognizes one enzyme from among hundreds, all of which share
a common substrate. Such a challenge confronted biochemists as they
developed inhibitors of protein kinases, which are enzymes that regulate
many cellular processes. Kinases are inviting drug targets as a number
of diseases, including cancer, diabetes, and inflammation, are linked to
cell signaling pathways mediated by protein kinases. The human genome
encodes 518 protein kinases that share a conserved sequence but which
CHAPTER 3 SECOND LAW OF THERMODYNAMICS 57
ΔH reflects strength of interaction
with target relative to solventΔSconf reflects loss of conformational
degrees of freedom upon binding
ΔSsolv reflects the release of water
upon binding
Figure 3.6Binding-
affinity contributions
of enthalpy and
entropy. Modified
from Freire (2004).