Concepts in receptor optimization: Targeting the RGD peptide
Concepts in receptor optimization: Targeting the RGD peptide
复制标题
DOI：
10.1021/ja056600l
复制
发表时间：
2006-04-12
影响因子：
15
通讯作者：
Gilson, MK
中科院分区：
文献类型：
--
作者：
Chen, W;Chang, CE;Gilson, MK
合成受体具有广泛的潜在应用，但设计低分子受体来结合具有高亲和力的配体一直是一件困难的事情。这项研究使用新的计算方法来理解为什么很难设计高亲和力的受体，并以生物活性多肽RGD作为模型配体来探索亲和力的极限。对于已知的RGD受体，M2建模方法与实验结果吻合很好，然后用从头设计算法分析了在Silico中产生的一系列受体。由于解溶和熵，驱动结合的力被成比例的排斥力系统地对立。特别是，库仑吸引与静电解溶罚、结合平均能量变化与构型熵代价之间存在着很强的相关性。这些相关性有助于解释为什么很难达到高亲和力。结合时表面积的变化被发现与本系列中的亲和力相关性较差。受体效率的测量方法总结了受体如何有效地利用表面积、总能量和库仑能量来实现亲和力。对计算效率的分析表明，低分子受体可以实现蛋白样亲和力。研究还发现，受体的大环化可以意外地增加结合的熵成本，因为大环结构进一步限制了配体的运动。
Synthetic receptors have a wide range of potential applications, but it has been difficult to design low molecular weight receptors that bind ligands with high, "proteinlike" affinities. This study uses novel computational methods to understand why it is hard to design a high-affinity receptor and to explore the limits of affinity, with the bioactive peptide RGD as a model ligand. The M2 modeling method is found to yield excellent agreement with experiment for a known RGD receptor and then is used to analyze a series of receptors generated in silico with a de novo design algorithm. Forces driving binding are found to be systematically opposed by proportionate repulsions due to desolvation and entropy. In particular, strong correlations are found between Coulombic attractions and the electrostatic desolvation penalty and between the mean energy change on binding and the cost in configurational entropy. These correlations help explain why it is hard to achieve high affinity. The change in surface area upon binding is found to correlate poorly with affinity within this series. Measures of receptor efficiency are formulated that summarize how effectively a receptor uses surface area, total energy, and Coulombic energy to achieve affinity. Analysis of the computed efficiencies suggests that a low molecular weight receptor can achieve proteinlike affinity. It is also found that macrocyclization of a receptor can, unexpectedly, increase the entropy cost of binding because the macrocyclic structure further restricts ligand motion.