  Numerous biological functions-such as enzymatic catalysis, the immune
response system, and the DNA-protein regulatory network-rely on the ability of
molecules to specifically recognize target molecules within a large pool of
similar competitors in a noisy biochemical environment. Using the basic
framework of signal detection theory, we treat the molecular recognition
process as a signal detection problem and examine its overall performance.
Thus, we evaluate the optimal properties of a molecular recognizer in the
presence of competition and noise. Our analysis reveals that the optimal design
undergoes a "phase transition" as the structural properties of the molecules
and interaction energies between them vary. In one phase, the recognizer should
be complementary in structure to its target (like a lock and a key), while in
the other, conformational changes upon binding, which often accompany molecular
recognition, enhance recognition quality. Using this framework, the abundance
of conformational changes may be explained as a result of increasing the
fitness of the recognizer. Furthermore, this analysis may be used in future
design of artificial signal processing devices based on biomolecules.
