Department of Chemistry, Biology and Biotechnology, University of Perugia, Via dell' Elce di Sotto 8, Perugia 06123, Italy.
Kinetic Business Centre, Molecular Discovery Ltd., Elstree, Borehamwood, Hertfordshire WD6 4PJ, United Kingdom.
J Med Chem. 2024 Sep 26;67(18):16355-16380. doi: 10.1021/acs.jmedchem.4c01235. Epub 2024 Sep 13.
Emerging drug candidates more often fall in the beyond-rule-of-five chemical space. Among them, proteolysis targeting chimeras (PROTACs) have gained great attention in the past decade. Although physicochemical properties of small molecules accomplishing Lipinski's rule-of-five can now be easily predicted through models generated by large data collections, for PROTACs the knowledge is still limited and heterogeneous, hampering their prediction. Here, the kinetic solubility and the coefficient of distribution at pH 7.4 (LogD) of 44 PROTACs, designed and synthesized to cover a wide chemical space, were measured. Their generally low solubility and high lipophilicity required an optimization of the experimental methods. Concerning the LogD, several prediction tools were tested, which were quite accurate for classical small molecules but provided dissimilar outcomes for PROTACs. Finally, models for the prediction of PROTACs' kinetic solubility and LogD were proposed by combining in-house generated experimental data with 3D description of PROTACs' structures.
新兴的药物候选物往往属于超出“五规则”的化学空间。在这些候选物中，蛋白水解靶向嵌合体（PROTACs）在过去十年中受到了极大关注。尽管通过大型数据集生成的模型，现在可以轻松预测满足“五规则”的小分子的物理化学性质，但对于 PROTACs，相关知识仍然有限且存在差异，阻碍了其预测。在这里，我们测量了 44 种 PROTACs 的动力学溶解度和在 pH 7.4 时的分配系数（LogD），这些 PROTACs 是为了覆盖广泛的化学空间而设计和合成的。它们通常较低的溶解度和较高的亲脂性需要优化实验方法。关于 LogD，我们测试了几种预测工具，这些工具对于经典小分子非常准确，但对于 PROTACs 提供了不同的结果。最后，我们通过将内部生成的实验数据与 PROTACs 结构的 3D 描述相结合，提出了用于预测 PROTACs 动力学溶解度和 LogD 的模型。
