Ravasco Joao M J M, Coelho Jaime A S
Research Institute for Medicines (iMed.ULisboa), Faculty of Pharmacy, Universidade de Lisboa, Avenida Prof. Gama Pinto, 1649-003 Lisboa, Portugal.
J Am Chem Soc. 2020 Mar 4;142(9):4235-4241. doi: 10.1021/jacs.9b11948. Epub 2020 Feb 24.
Inverse-electron demand Diels-Alder cycloadditions have emerged as important bioorthogonal reactions in chemical biology. Understanding and predicting reaction rates for bioconjugation reactions is fundamental for evaluating their efficacy in biological systems. Here, we present multivariate models to predict the second order rate constants of bioorthogonal inverse-electron demand Diels-Alder reactions involving 1,2,4,5-tetrazines derivatives. A data-driven approach was used to model these reactions by parametrizing both the dienophiles and the dienes partners. The models are statistically robust and were used to predict/extrapolate the outcome of several reactions as well as to identify mechanistic differences among similar reactants.
逆电子需求狄尔斯-阿尔德环加成反应已成为化学生物学中重要的生物正交反应。理解和预测生物共轭反应的反应速率是评估其在生物系统中功效的基础。在此，我们提出多变量模型来预测涉及1,2,4,5-四嗪衍生物的生物正交逆电子需求狄尔斯-阿尔德反应的二级速率常数。采用数据驱动方法，通过对亲双烯体和亲双烯体伙伴进行参数化来对这些反应进行建模。这些模型具有统计学稳健性，用于预测/推断几种反应的结果，并识别相似反应物之间的机理差异。
