PKIDB: A Curated, Annotated and Updated Database of Protein Kinase Inhibitors in Clinical Trials

• Published in: Molecules (Basel, Switzerland) Vol. 23; no. 4; p. 908
• Main Authors: Carles, Fabrice, Bourg, Stéphane, Meyer, Christophe, Bonnet, Pascal
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 15.04.2018; MDPI
• Subjects: approved drugs; Binding Sites; Chemical Sciences; Cheminformatics; chemometrics analysis; Clinical trials; Clinical Trials as Topic; Cyclin-dependent kinases; Databases as Topic; Drug Approval; Kinases; kinome; Models, Molecular; Pharmaceutical industry; Principal Component Analysis; Principal components analysis; Protease inhibitors; protein kinase inhibitors; Protein Kinase Inhibitors - pharmacology; Proteins; database; chemometrics analysis; clinical trials; approved drugs; kinome; protein kinase inhibitors
• DOI: 10.3390/molecules23040908
• ISSN: 1420-3049

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 http://www.icoa.fr/pkidb and can be easily browsed through a user-friendly spreadsheet-like interface.