Dynamic combinatorial libraries (DCLs) display adaptive behavior, enabled by the reversible generation of their molecular constituents from building blocks, in response to external effectors, e.g., protein receptors. So far, chemoinformatics has not yet been used for the design of DCLs─which comprise a radically different set of challenges compared to classical library design. Here, we propose a chemoinformatic model for theoretically assessing the composition of DCLs in the presence and the absence of an effector. An imine-based DCL in interaction with the effector human carbonic anhydrase II (CA II) served as a case study. Support vector regression models for the imine formation constants and imine-CA II binding were derived from, respectively, a set of 276 imines synthesized and experimentally studied in this work and 4350 inhibitors of CA II from ChEMBL. These models predict constants for all DCL constituents, to feed software assessing equilibrium concentrations. They are publicly available on the dedicated website. Models rationally selected two amines and two aldehydes predicted to yield stable imines with high affinity for CA II and provided a virtual illustration on how effector affinity regulates DCL members.

中文翻译：

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迈向动态组合库的计算机建模

动态组合文库 (DCL) 显示出适应性行为，这是通过从构建块中可逆地生成其分子成分来响应外部效应器（例如蛋白质受体）而实现的。到目前为止，化学信息学还没有被用于 DCL 的设计——与经典文库设计相比，它包含了一组截然不同的挑战。在这里，我们提出了一种化学信息学模型，用于在存在和不存在效应器的情况下从理论上评估 DCL 的组成。与效应人碳酸酐酶 II (CA II) 相互作用的基于亚胺的 DCL 作为案例研究。亚胺形成常数和亚胺-CA II 结合的支持向量回归模型分别来自：在这项工作中合成和实验研究了一组 276 种亚胺和来自 ChEMBL 的 4350 种 CA II 抑制剂。这些模型预测所有 DCL 成分的常数，以提供软件评估平衡浓度。它们可在专用网站上公开获得。模型合理地选择了两种胺和两种醛，预计会产生对 CA II 具有高亲和力的稳定亚胺，并提供了关于效应亲和力如何调节 DCL 成员的虚拟说明。