PLK4 is a key regulator of centriole duplication. Here, we show that PLK4 is active beyond the initiation of centriole duplication with the abundance of active kinase increasing to a peak in mitosis. Importantly, we show that differences in PLK4 abundance exist between mother and daughter centrioles and that active PLK4 is restricted to the centrosome.

The number of protein kinase inhibitors (PKIs) approved worldwide continues to grow steadily, with 39 drugs approved in the period between 2001 and January 2018. PKIs on the market have been the subject of many reviews, and structure-property relationships specific to this class of drugs have been inferred. However, the large number of PKIs under development is often overlooked. In this paper, we present PKIDB (Protein Kinase Inhibitor Database), a monthly-updated database gathering approved PKIs as well as PKIs currently in clinical trials. The database compiles currently 180 inhibitors ranging from phase 0 to 4 clinical trials along with annotations extracted from seven public resources. The distribution and property ranges of standard physicochemical properties are presented. They can be used as filters to better prioritize compound selection for future screening campaigns. Interestingly, more than one-third of the kinase inhibitors violate at least one Lipinski’s rule. A Principal Component Analysis (PCA) reveals that Type-II inhibitors are mapped to a distinct chemical space as compared to orally administrated drugs as well as to other types of kinase inhibitors. Using a Principal Moment of Inertia (PMI) analysis, we show that PKIs under development tend to explore new shape territories as compared to approved PKIs. In order to facilitate the analysis of the protein space, the kinome tree has been annotated with all protein kinases being targeted by PKIs. Finally, we analyzed the pipeline of the pharmaceutical companies having PKIs on the market or still under development. We hope that this work will assist researchers in the kinase field in identifying and designing the next generation of kinase inhibitors for still untargeted kinases. The PKIDB database is freely accessible from a website at and can be easily browsed through a user-friendly spreadsheet-like interface.

As computational drug design becomes increasingly reliant on virtual screening and on high-throughput 3D modeling, the need for fast, robust, and reliable methods for sampling molecular conformations has become greater than ever. Furthermore, chemical novelty is at a premium, forcing medicinal chemists to explore more complex structural motifs and unusual topologies. This necessitates the use of conformational sampling techniques that work well in all cases. Here, we compare the performance of several popular conformational search algorithms on three broad classes of macrocyclic molecules. These methods include Catalyst, CAESAR, MacroModel, MOE, Omega, Rubicon and two newer self-organizing algorithms known as stochastic proximity embedding (SPE) and self-organizing superimposition (SOS) that have been developed at Johnson & Johnson. Our results show a compelling advantage for the three distance geometry methods (SOS, SPE, and Rubicon) followed to a lesser extent by MacroModel. The remaining techniques, particularly those based on systematic search, often failed to identify any of the lowest energy conformations and are unsuitable for this class of structures. Taken together with our previous study on drug-like molecules (Agrafiotis, D. K.; Gibbs, A.; Zhu, F.; Izrailev, S.; Martin, E. Conformational Sampling of Bioactive Molecules: A Comparative Study. J. Chem. Inf. Model., 2007, 47, 1067-1086), these results suggest that SPE and SOS are two of the most robust and universally applicable conformational search methods, with the latter being preferred because of its superior speed.