Optimal Design of a Molecular Recognizer: Molecular Recognition as a Bayesian Signal Detection Problem
Abstract
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.
- Publication:
-
IEEE Journal of Selected Topics in Signal Processing
- Pub Date:
- June 2008
- DOI:
- 10.1109/JSTSP.2008.923859
- arXiv:
- arXiv:1007.4527
- Bibcode:
- 2008ISTSP...2..390S
- Keywords:
-
- Quantitative Biology - Molecular Networks;
- Computer Science - Information Theory;
- Physics - Biological Physics
- E-Print:
- Bayesian detection, conformational changes, molecular recognition, specificity. http://www.weizmann.ac.il/complex/tlusty/papers/IEEE2008.pdf