The bis(pyridine)silver(I) permanganate promoted hydroxylation of diketopiperazines has served as a pivotal transformation in the synthesis of complex epipolythiodiketopiperazine alkaloids. This late-stage C-H oxidation chemistry is strategically critical to access N-acyl iminium ion intermediates necessary for nucleophilic thiolation of advanced diketopiperazines en route to potent epipolythiodiketopiperazine anticancer compounds. In this study, we develop an informative mathematical model using hydantoin derivatives as a training set of substrates by relating the relative rates of oxidation to various calculated molecular descriptors. The model prioritizes Hammett values and percent buried volume as key contributing factors in the hydantoin series while correctly predicting the experimentally observed oxidation sites in various complex diketopiperazine case studies. Thus, a method is presented by which to use simplified training molecules and resulting correlations to explain and predict reaction behavior for more complex substrates.
The bis(pyridine)silver(I) permanganate promoted hydroxylation of n class="Chemical">diketopiperazines has served as a pivotal transformation in the synthesis of complex epipolythiodiketopiperazine alkaloids. This late-stage C-H oxidation chemistry is strategically critical to access N-acyl iminium ion intermediates necessary for nucleophilic thiolation of advanced diketopiperazines en route to potent epipolythiodiketopiperazine anticancer compounds. In this study, we develop an informative mathematical model using hydantoin derivatives as a training set of substrates by relating the relative rates of oxidation to various calculated molecular descriptors. The model prioritizes Hammett values and percent buried volume as key contributing factors in the hydantoin series while correctly predicting the experimentally observed oxidation sites in various complex diketopiperazine case studies. Thus, a method is presented by which to use simplified training molecules and resulting correlations to explain and predict reaction behavior for more complex substrates.
Authors: Haoxuan Wang; Clinton J Regan; Julian A Codelli; Paola Romanato; Angela L A Puchlopek-Dermenci; Sarah E Reisman Journal: Org Lett Date: 2017-03-28 Impact factor: 6.005
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Authors: Gréta Bettina Kovács; Nóra V May; Petra Alexandra Bombicz; Szilvia Klébert; Péter Németh; Alfréd Menyhárd; Gyula Novodárszki; Vladimir Petrusevski; Fernanda Paiva Franguelli; József Magyari; Kende Béres; Imre Miklós Szilágyi; László Kótai Journal: RSC Adv Date: 2019-09-09 Impact factor: 4.036