分子识别器的优化设计：分子识别的贝叶斯信号检测问题
Optimal Design of a Molecular Recognizer: Molecular Recognition as a Bayesian Signal Detection Problem
摘要：
许多生物学功能，如酶催化、免疫应答系统和DNA-蛋白质调控网络，依赖于分子在嘈杂的生化环境中特异性识别大量相似竞争者中的靶分子的能力。利用信号检测理论的基本框架，我们将分子识别过程视为一个信号检测问题，并检查其整体性能。因此，我们评估的最佳性能的分子识别器中存在的竞争和噪声。我们的分析表明，最佳设计经历了“相变”的分子和它们之间的相互作用能的结构特性的变化。在一个阶段中，识别器应该在结构上与其目标互补（如锁和钥匙），而在另一个阶段中，结合时的构象变化通常伴随着分子识别，提高识别质量。使用这个框架，丰富的构象变化可以解释为增加识别器的适应性的结果。此外，这种分析可以用于未来的设计基于生物分子的人工信号处理设备。
英文摘要：
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.
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