Hans Briem

From the Insoluble Dye Indirubin Towards Highly Active, Soluble Cdk2-Inhibitors

The natural product indirubin (1) is part of the class of indigo dyes, employed by mankind since the Bronze Age for textile coloring. These indigo dyes were traditionally obtained by processing of precursor compounds occurring in a number of plants and marine animals and consisted mainly of indigo (5 ; blue) with a small percentage of indirubin (1; purple). In the course of an intensive effort to prepare synthetic indigo as a further program for the rapidly expanding dye industries, the first total synthesis of indirubin (1) was achieved in 1870 by Adolf von Bayer. Shortly thereafter, the total synthesis of indigo was achieved, and synthetic indigo became a major product of the dye industries. Eventually, this dye chemistry laid the foundation for the first synthetic drugs including arsphenamine, acetaminophen, and acetyl salicylic acid. More than 100 years later in 1979, indirubin was reported in a seminal publication to be the active constituent of a traditional Chinese antileukemia remedy. This finding prompted further investigations into the pharmacological properties of the indirubins 5, 6] and resulted in a 1999 report by Eisenbrand, Johnson, Mejier, and co-workers, who showed that indirubin and close analogues are ATP-competitive inhibitors of the enzyme CDK2 (1: IC50 = 2 mm ; see Table 1), a key target in the ongoing search for novel antitumor therapies. 8] This discovery places indirubin in the larger class of ATP-competitive CDK inhibitors of the oxindole family, such as 2, 3, and 4 (Scheme 1). 9] In this publication, the X-ray structure of the related indirubin-5-sulfonic acid (20 ; IC50 =

Classifying "Kinase Inhibitor-Likeness" by Using Machine-Learning Methods

By using an in‐house data set of small‐molecule structures, encoded by Ghose–Crippen parameters, several machine learning techniques were applied to distinguish between kinase inhibitors and other molecules with no reported activity on any protein kinase. All four approaches pursued—support‐vector machines (SVM), artificial neural networks (ANN), k nearest neighbor classification with GA‐optimized feature selection (GA/kNN), and recursive partitioning (RP)—proved capable of providing a reasonable discrimination. Nevertheless, substantial differences in performance among the methods were observed. For all techniques tested, the use of a consensus vote of the 13 different models derived improved the quality of the predictions in terms of accuracy, precision, recall, and F1 value. Support‐vector machines, followed by the GA/kNN combination, outperformed the other techniques when comparing the average of individual models. By using the respective majority votes, the prediction of neural networks yielded the highest F1 value, followed by SVMs.

Macrocyclic Aminopyrimidines as Multitarget CDK and VEGF-R Inhibitors with Potent Antiproliferative Activities

X‐ray structures from CDK2–aminopyrimidine inhibitor complexes led to the idea to stabilize the active conformation of aminopyrimidine inhibitors by incorporating the recognition site into a macrocyclic framework. A modular synthesis approach that relies on a new late‐stage macrocyclization protocol that enables fast and efficient synthesis of macrocyclic aminopyrimidines was developed. A set of structurally diverse derivatives was prepared. Macrocyclic aminopyrimidines were shown to be multitarget inhibitors of CDK1/2 and VEGF‐RTKs. In addition, potent antiproliferative activities toward various human tumor cells and a human tumor xenograft model were demonstrated.