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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(More)
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(More)
The HYDE scoring function consistently describes hydrogen bonding, the hydrophobic effect and desolvation. It relies on HYdration and DEsolvation terms which are calibrated using octanol/water partition coefficients of small molecules. We do not use affinity data for calibration, therefore HYDE is generally applicable to all protein targets. HYDE reflects(More)
A crystallographic fragment screen was carried out to identify starting points for the development of inhibitors of protein kinase Pim-1, a potential target for tumour therapy. All fragment hits identified via soaking in this study turned out to bind to the unusually hydrophobic pocket at the hinge region. The most potent fragments, two cinnamic acid(More)
Lead optimization of a high-throughput screening hit led to the rapid identification of aminopyrimidine ZK 304709, a multitargeted CDK and VEGF-R inhibitor that displayed a promising preclinical profile. Nevertheless, ZK 304709 failed in phase I studies due to dose-limited absorption and high inter-patient variability, which was attributed to limited(More)
An alternative method for defining molecular similarity is presented. By using the docking program DOCK and a reference panel of protein binding sites, fingerprints for a set of molecules have been generated, based on calculated interaction energies. These binding patterns allowed us to calculate matrices of similarity coefficients which subsequently were(More)
Using a 4D-QSAR approach (software Quasar) allowing for multiple-conformation, orientation, and protonation-state ligand representation as well as for the simulation of local induced-fit phenomena, we have validated a family of receptor surrogates for the neurokinin-1 (NK-1) receptor system. The evolution was based on a population of 500 receptor models and(More)
Kohonen neural networks generate projections of large data sets defined in high-dimensional space. The resulting self-organizing maps can be used in many applications in the drug discovery process, such as to analyze combinatorial libraries for their similarity or diversity and to select descriptors for structure-activity relationships. The ability to(More)
Computational target prediction for bioactive compounds is a promising field in assessing off-target effects. Structure-based methods not only predict off-targets, but, simultaneously, binding modes, which are essential for understanding the mode of action and rationally designing selective compounds. Here, we highlight the current open challenges of(More)