A Systematic Review of Recently Reported Marine Derived Natural Product Kinase Inhibitors

Protein kinases are validated drug targets for a number of therapeutic areas, as kinase deregulation is known to play an essential role in many disease states. Many investigated protein kinase inhibitors are natural product small molecules or their derivatives. Many marine-derived natural products from various marine sources, such as bacteria and cyanobacteria, fungi, animals, algae, soft corals, sponges, etc. have been found to have potent kinase inhibitory activity, or desirable pharmacophores for further development. This review covers the new compounds reported from the beginning of 2014 through the middle of 2019 as having been isolated from marine organisms and having potential therapeutic applications due to kinase inhibitory and associated bioactivities. Moreover, some existing clinical drugs based on marine-derived natural product scaffolds are also discussed.

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

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.

VSPrep: A General KNIME Workflow for the Preparation of Molecules for Virtual Screening

Over the past decades, virtual screening has proved itself to be a valuable asset to identify new bioactive compounds. The vast majority of commonly used techniques can be described in three steps: pre-processing the dataset i. e. small (ligands) and eventually larger (receptors) molecules, execute the method and finally analyse the results. Hence, the preparation of ligands is a critical step for success of commonly used virtual screening approaches such as protein-ligand docking, similarity or pharmacophore search. We present here a new workflow, VSPrep, for the pre-processing of small molecules; it is based on freely accessible tools for academics and is integrated within the KNIME platform. It can be used to perform several chemoinformatics tasks such as molecular database cleaning, tautomer and stereoisomer enumeration, focused library design and conformer generation. Additionally, graphical reports of the results are provided to the user as a convenient analysis tool.

Prediction of Protein Kinase-Ligand Interactions through 2.5D Kinochemometrics

So far, 518 protein kinases have been identified in the human genome. They share a common mechanism of protein phosphorylation and are involved in many critical biological processes of eukaryotic cells. Deregulation of the kinase phosphorylation function induces severe illnesses such as cancer, diabetes, or inflammatory diseases. Many actors in the pharmaceutical domain have made significant efforts to design potent and selective protein kinase inhibitors as new potential drugs. Because the ATP binding site is highly conserved in the protein kinase family, the design of selective inhibitors remains a challenge and has negatively impacted the progression of drug candidates to late-stage clinical development. The work presented here adopts a 2.5D kinochemometrics (KCM) approach, derived from proteochemometrics (PCM), in which protein kinases are depicted by a novel 3D descriptor and the ligands by 2D fingerprints. We demonstrate in two examples that the protein descriptor successfully classified protein kinases based on their group membership and their Asp-Phe-Gly (DFG) conformation. We also compared the performance of our models with those obtained from a full 2D KCM model and QSAR models. In both cases, the internal validation of the models demonstrated good capabilities to distinguish "active" from "inactive" protein kinase-ligand pairs. However, the external validation performed on two independent data sets showed that the two statistical models tended to overestimate the number of "inactive" pairs.

A Proteometric Analysis of Human Kinome: Insight into Discriminant Conformation-dependent Residues

Because of the success of imatinib, the first type-II kinase inhibitor approved by the FDA in 2001, sustained efforts have been made by the pharmaceutical industry to discover novel compounds stabilizing the inactive conformation of protein kinases. On the seven type-II inhibitors having reached the market, four were released in 2012, suggesting an acceleration of the research of such a class of compounds. Still, they represent less than a third of the protein kinase inhibitors available to patients today. The identification of key residues involved in the binding of this type of ligands in the kinase active site might ease the design of potent and selective type-II inhibitors. In order to identify those discriminant residues, we have developed a proteometric approach combining residue descriptors of protein kinase sequences and biological activities of various type-II kinase inhibitors. We applied Partial Least Squares (PLS) regression to identify 29 key residues that influence the binding of four type-II inhibitors to most proteins of the kinome. The gatekeeper residue was found to be the most relevant, confirming an essential role in ligand binding as well as in protein kinase conformational changes. Using the newly developed proteometric model, we predicted the propensity of each protein kinase to be inhibited by type-II ligands. The model was further validated using an external data set of protein/ligand activity pairs. Other residues present in the kinase domain, and more specifically in the binding site, have been highlighted by this approach, but their role in biological mechanisms is still unknown.

Approaches to discover non-ATP site kinase inhibitors

This review will highlight the most commonly used methods to discover small molecule Type III/IV kinase inhibitors.