universally accepted that protein–ligand interactions are rarely rigid
[5]. Proteins are inherently flexible molecules that adopt an ensemble of conformations in solution, which exist in a state of dynamic
equilibrium. This realization led to the formation of the “induced
fit” and, subsequently, the “conformational selection” models of
protein–ligand and enzyme–substrate interactions [1–17]. These
models account for conformational changes in ligand binding [9].
The induced fit and conformational selection models account
for the dynamic state of a protein, but differ in when in the binding
process the conformational change occurs [9]. In the induced fit
model, the ligand binds to the predominant, free conformation in
solution followed by a conformational change to the preferred
ligand-bound conformation (Fig. 1). The conformational selection
model proposes that a given protein exists in a state of dynamic
equilibrium between several conformations, termed the conformational ensemble and the “ligand-bound” conformation already
exists as part of the conformational ensemble in solution in a low
population state. The population state of a conformation refers to
the amount of protein in a particular conformation. Therefore, the
ligand recognizes and selectively binds to the conformer in the
favored state, shifting the conformational equilibrium to make it
the predominant conformation in the ensemble [10]. Conformational selection may appear similar to the “lock-and-key” model
because selection occurs via a match in the “shape” in both models.
However, in conformational selection, the selection is of a
conformer out of many different conformers of a single protein
rather than selection of a protein out of many different proteins, as
in the lock-and-key model (Fig. 1). In the conformational selection
model, ligand binding induces a change in the equilibrium of the
states, which forces the system to re-equilibrate, shifting the population of the conformational ensemble toward the preferred
conformer. The population shift described in the conformational
selection model cannot be present in the lock-and-key model
because the ensemble is composed of different proteins rather
than different conformers [4]. Thus, the key difference between
these two models is the presence of a dynamic equilibrium which
allows for a population shift to occur upon ligand binding [16].
Conformational motions in enzymes are inherently linked to
their function and have a direct impact on binding of substrate or
cofactor, product release, and allosteric regulation [12, 15, 18,
19]. Enzymes are common therapeutic targets but the movement
between different conformational states is often ignored during
drug discovery and design [12]. When the flexibility of a protein
is acknowledged during drug design, it is often assumed to follow
the induced fit model. The possibility that small molecule or drug
binding may occur through the conformational selection mechanism is usually ignored, which may hinder drug discovery and
development efforts [20]. Understanding the mechanism by
Distal Regions Regulate Dihydrofolate Reductase-Ligand Interactions
187
[5]. Proteins are inherently flexible molecules that adopt an ensemble of conformations in solution, which exist in a state of dynamic
equilibrium. This realization led to the formation of the “induced
fit” and, subsequently, the “conformational selection” models of
protein–ligand and enzyme–substrate interactions [1–17]. These
models account for conformational changes in ligand binding [9].
The induced fit and conformational selection models account
for the dynamic state of a protein, but differ in when in the binding
process the conformational change occurs [9]. In the induced fit
model, the ligand binds to the predominant, free conformation in
solution followed by a conformational change to the preferred
ligand-bound conformation (Fig. 1). The conformational selection
model proposes that a given protein exists in a state of dynamic
equilibrium between several conformations, termed the conformational ensemble and the “ligand-bound” conformation already
exists as part of the conformational ensemble in solution in a low
population state. The population state of a conformation refers to
the amount of protein in a particular conformation. Therefore, the
ligand recognizes and selectively binds to the conformer in the
favored state, shifting the conformational equilibrium to make it
the predominant conformation in the ensemble [10]. Conformational selection may appear similar to the “lock-and-key” model
because selection occurs via a match in the “shape” in both models.
However, in conformational selection, the selection is of a
conformer out of many different conformers of a single protein
rather than selection of a protein out of many different proteins, as
in the lock-and-key model (Fig. 1). In the conformational selection
model, ligand binding induces a change in the equilibrium of the
states, which forces the system to re-equilibrate, shifting the population of the conformational ensemble toward the preferred
conformer. The population shift described in the conformational
selection model cannot be present in the lock-and-key model
because the ensemble is composed of different proteins rather
than different conformers [4]. Thus, the key difference between
these two models is the presence of a dynamic equilibrium which
allows for a population shift to occur upon ligand binding [16].
Conformational motions in enzymes are inherently linked to
their function and have a direct impact on binding of substrate or
cofactor, product release, and allosteric regulation [12, 15, 18,
19]. Enzymes are common therapeutic targets but the movement
between different conformational states is often ignored during
drug discovery and design [12]. When the flexibility of a protein
is acknowledged during drug design, it is often assumed to follow
the induced fit model. The possibility that small molecule or drug
binding may occur through the conformational selection mechanism is usually ignored, which may hinder drug discovery and
development efforts [20]. Understanding the mechanism by
Distal Regions Regulate Dihydrofolate Reductase-Ligand Interactions
187