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动态分子网络:从合成受体到自我复制体。

Dynamic molecular networks: from synthetic receptors to self-replicators.

机构信息

Centre for Systems Chemistry, Stratingh Institute, University of Groningen, Nijenborgh 4, 9747 AG Groningen, The Netherlands.

出版信息

Acc Chem Res. 2012 Dec 18;45(12):2200-10. doi: 10.1021/ar200246j. Epub 2012 Jan 20.

DOI:10.1021/ar200246j
PMID:22264201
Abstract

Dynamic combinatorial libraries (DCLs) are molecular networks in which the network members exchange building blocks. The resulting product distribution is initially under thermodynamic control. Addition of a guest or template molecule tends to shift the equilibrium towards compounds that are receptors for the guest. This Account gives an overview of our work in this area. We have demonstrated the template-induced amplification of synthetic receptors, which has given rise to several high-affinity binders for cationic and anionic guests in highly competitive aqueous solution. The dynamic combinatorial approach allows for the identification of new receptors unlikely to be obtained through rational design. Receptor discovery is possible and more efficient in larger libraries. The dynamic combinatorial approach has the attractive characteristic of revealing interesting structures, such as catenanes, even when they are not specifically targeted. Using a transition-state analogue as a guest we can identify receptors with catalytic activity. Although DCLs were initially used with the reductionistic view of identifying new synthetic receptors or catalysts, it is becoming increasingly apparent that DCLs are also of interest in their own right. We performed detailed computational studies of the effect of templates on the product distributions of DCLs using DCLSim software. Template effects can be rationalized by considering the entire network: the system tends to maximize global host-guest binding energy. A data-fitting analysis of the response of the global position of the DCLs to the addition of the template using DCLFit software allowed us to disentangle individual host-guest binding constants. This powerful procedure eliminates the need for isolation and purification of the various individual receptors. Furthermore, local network binding events tend to propagate through the entire network and may be harnessed for transmitting and processing of information. We demonstrated this possibility in silico through a simple dynamic molecular network that can perform AND logic with input and output in the form of molecules. Not only are dynamic molecular networks responsive to externally added templates, but they also adjust to internal template effects, giving rise to self-replication. Recently we have started to explore scenarios where library members recognize copies of themselves, resulting in a self-assembly process that drives the synthesis of the very molecules that self-assemble. We have developed a system that shows unprecedented mechanosensitive self-replication behavior: depending on whether the solution is shaken, stirred or not agitated, we have obtained a hexameric replicator, a heptameric replicator or no replication, respectively. We rationalize this behavior through a mechanism in which replication is promoted by mechanically-induced fragmentation of self-assembled replicator fibers. These results represent a new mode of self-replication in which mechanical energy liberates replicators from a self-inhibited state. These systems may also be viewed as self-synthesizing, self-assembling materials. These materials can be captured photochemically, converting a free-flowing fiber solution into a hydrogel through photo-induced homolytic disulfide exchange.

摘要

动态组合化学库(DCL)是一种分子网络,其中网络成员交换构建块。最初,所得产物分布受热力学控制。添加客体或模板分子往往会使平衡向对客体具有受体作用的化合物转移。本报告概述了我们在这一领域的工作。我们已经证明了合成受体的模板诱导扩增,这导致了在高度竞争的水溶液中对阳离子和阴离子客体具有高亲和力的几种结合物。动态组合化学方法允许识别不太可能通过合理设计获得的新受体。在更大的文库中,受体的发现是可能的,并且更有效。动态组合化学方法具有揭示有趣结构的诱人特性,例如即使它们不是专门针对它们,也可以揭示轮烷等结构。使用过渡态类似物作为客体,我们可以识别具有催化活性的受体。尽管 DCL 最初是从识别新的合成受体或催化剂的简化观点出发使用的,但越来越明显的是,DCL 本身也具有重要意义。我们使用 DCLSim 软件对模板对 DCL 产物分布的影响进行了详细的计算研究。通过考虑整个网络,可以合理地解释模板效应:系统倾向于最大化全局主客体结合能。使用 DCLFit 软件对 DCL 对模板添加的整体位置的响应进行数据拟合分析,使我们能够分离出各个主客体结合常数。这种强大的程序消除了分离和纯化各种单个受体的需要。此外,局部网络结合事件往往会在整个网络中传播,并可用于信息的传输和处理。我们通过一个简单的动态分子网络在计算机上证明了这一点,该网络可以以分子的形式进行 AND 逻辑输入和输出。动态分子网络不仅对外部添加的模板有反应,而且还对内部模板效应做出反应,从而导致自我复制。最近,我们开始探索库成员识别自身副本的情况,从而导致驱动自身组装分子合成的自组装过程。我们开发了一种系统,该系统显示出前所未有的机械敏感自复制行为:根据溶液是摇晃,搅拌还是不搅拌,我们分别获得了六聚体复制子,七聚体复制子或没有复制。我们通过一种机制来解释这种行为,该机制通过机械诱导的自组装复制纤维的断裂来促进复制。这些结果代表了一种新的自我复制模式,其中机械能将复制子从自我抑制状态中释放出来。这些系统也可以被视为自合成,自组装材料。这些材料可以通过光化学捕获,将自由流动的纤维溶液通过光诱导的均裂二硫键交换转化为水凝胶。

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