Design and Synthesis of New Quinazolin-4-one Derivatives with Negative mGlu7 Receptor Modulation Activity and Antipsychotic-Like Properties.

Following the glutamatergic theory of schizophrenia and based on our previous study regarding the antipsychotic-like activity of mGlu7 NAMs, we synthesized a new compound library containing 103 members, which were examined for NAM mGlu7 activity in the T-REx 293 cell line expressing a recombinant human mGlu7 receptor. Out of the twenty-two scaffolds examined, active compounds were found only within the quinazolinone chemotype. 2-(2-Chlorophenyl)-6-(2,3-dimethoxyphenyl)-3-methylquinazolin-4(3H)-one (A9-7, ALX-171, mGlu7 IC50 = 6.14 µM) was selective over other group III mGlu receptors (mGlu4 and mGlu8), exhibited satisfactory drug-like properties in preliminary DMPK profiling, and was further tested in animal models of antipsychotic-like activity, assessing the positive, negative, and cognitive symptoms. ALX-171 reversed DOI-induced head twitches and MK-801-induced disruptions of social interactions or cognition in the novel object recognition test and spatial delayed alternation test. On the other hand, the efficacy of the compound was not observed in the MK-801-induced hyperactivity test or prepulse inhibition. In summary, the observed antipsychotic activity profile of ALX-171 justifies the further development of the group of quinazolin-4-one derivatives in the search for a new drug candidate for schizophrenia treatment.

5-Keto-3-cyano-2,4-diaminothiophenes as selective maternal embryonic leucine zipper kinase inhibitors.

Maternal embryonic leucine zipper kinase (MELK) is involved in several key cellular processes and displays increased levels of expression in numerous cancer classes (colon, breast, brain, ovary, prostate and lung). Although no selective MELK inhibitors have yet been approved, increasing evidence suggest that inhibition of MELK would constitute a promising approach for cancer therapy. A weak high-throughput screening hit (17, IC50 ≈ 5 µM) with lead-like properties was optimized for MELK inhibition. The early identification of a plausible binding mode by molecular modeling offered guidance in the choice of modifications towards compound 52 which displayed a 98 nM IC50. A good selectivity profile was achieved for a representative member of the series (29) in a 486 protein kinase panel. Future elaboration of 52 has the potential to deliver compounds for further development with chemotherapeutic aims.

Discovery of indazole-pyridinone derivatives as a novel class of potent and selective MNK1/2 kinase inhibitors that protecting against endotoxin-induced septic shock.

The mitogen-activated protein kinase (MAPK)-interacting kinases 1 and 2 (MNKs 1/2) and their downstream target eIF4E, play a role in oncogenic transformation, progression and metastasis. These results provided rationale for development of first MNKs inhibitors, currently in clinical trials for cancer treatment. Inhibitors of the MNKs/eIF4E pathway are also proposed as treatment strategy for inflammatory conditions. Here we present results of optimization of indazole-pyridinone derived MNK1/2 inhibitors among which compounds 24 and 26, selective and metabolically stable derivatives. Both compounds decreased levels of eIF4E Ser206 phosphorylation (pSer209-eIF4E) in MOLM16 cell line. When administered in mice compounds 24 and 26 significantly improved survival rates of animals in the endotoxin lethal dose challenge model, with concomitant reduction of proinflammatory cytokine levels - TNFα and IL-6 in serum. Identified MNK1/2 inhibitors represent a novel class of immunomodulatory compounds with a potential for the treatment of inflammatory diseases including sepsis.

How to design potent and selective DYRK1B inhibitors? Molecular modeling study.

DYRK1B protein kinase is an emerging anticancer target due to its overexpression in a variety of cancers and its role in cancer chemoresistance through maintaining cancer cells in the G0 (quiescent) state. Consequently, there is a growing interest in the development of potent and selective DYRK1B inhibitors for anticancer therapy. One of the major off-targets is another protein kinase, GSK3ß, which phosphorylates an important regulator of cell cycle progression on the same residue as DYRK1B and is involved in multiple signaling pathways. In the current work, we performed a detailed comparative structural analysis of DYRK1B and GSK3ß ATP-binding sites and identified key regions responsible for selectivity. As the crystal structure of DYRK1B has never been reported, we built and optimized a homology model by comparative modeling and metadynamics simulations. Calculation of interaction energies between docked ligands in the ATP-binding sites of both kinases allowed us to pinpoint key residues responsible for potency and selectivity. Specifically, the role of the gatekeeper residues in DYRK1B and GSK3ß is discussed in detail, and two other residues are identified as key to selectivity of DYRK1B inhibition versus GSK3ß. The analysis presented in this work was used to support the design of potent and selective azaindole-quinoline-based DYRK1B inhibitors and can facilitate development of more selective inhibitors for DYRK kinases.

"Virtual fragment linking": an approach to identify potent binders from low affinity fragment hits.

In this work we explore the possibilities of using fragment-based screening data to prioritize compounds from a full HTS library, a method we call virtual fragment linking (VFL). The ability of VFL to identify compounds of nanomolar potency based on micromolar fragment binding data was tested on 75 target classes from the WOMBAT database and succeeded in 57 cases. Further, the method was demonstrated for seven drug targets from in-house screening programs that performed both FBS of 8800 fragments and screens of the full library. VFL captured between 28% and 67% of the hits (IC 50 < 10microM) in the top 5% of the ranked library for four of the targets (enrichment between 5-fold and 13-fold). Our findings lead us to conclude that proper coverage of chemical space by the fragment library is crucial for the VFL methodology to be successful in prioritizing HTS libraries from fragment-based screening data.

Mitogen-activated Protein Kinase (MAPK) Interacting Kinases 1 and 2 (MNK1 and MNK2) as Targets for Cancer Therapy: Recent Progress in the Development of MNK Inhibitors.

MAP kinase-interacting kinases (MNK1 and MNK2) are often activated downstream of ERK and p38 MAPK in the MAP kinase family. The role of MNKs in the development and progression of solid tumors and hematological malignancies has been widely discussed, particularly in the context of cap dependent translation, regulated by phosphorylation of eIF4E. MNK/eIF4E axis is involved in the expression of pro angiogenic, antiapoptotic, cell cycle, and motility proteins, such as MCL1, VEGF, MMP3, SNAIL, SMAD2, ß-catenin or cyclin D1, and is essential during Ras and c Myc-induced transformation. MNK1/2 emerged as eligible targets for drug discovery in oncology, based on the antitumor effects observed in genetic knockout and RNA interference experiments and at the same time lack of adverse effects in dual knockout animals. There is a high interest in the development of pharmacological inhibitors of MNK1/2 as not only tools for further basic research studies but also potential drugs in diseases characterized by deregulated translation. Unfortunately, the role of MNK1/2 in cancer still remains elusive due to the absence of potent and selective probes. Moreover, in many instances, hypotheses have been built reliant upon unspecific MNK1/2 inhibitors such as CGP57380 or cercosporamide. Lately, the first two clinical programs targeting MNKs in oncology have been revealed (eFT508 and BAY 1143269), although several other MNK programs are currently running at the preclinical stage. This review aims to provide an overview of recent progress in the development of MNK inhibitors.

Mapping adverse drug reactions in chemical space.

We present a novel method to better investigate adverse drug reactions in chemical space. By integrating data sources about adverse drug reactions of drugs with an established cheminformatics modeling method, we generate a data set that is then visualized with a systems biology tool. Thereby new insights into undesired drug effects are gained. In this work, we present a global analysis linking chemical features to adverse drug reactions.

Gaining insight into off-target mediated effects of drug candidates with a comprehensive systems chemical biology analysis.

We present a workflow that leverages data from chemogenomics based target predictions with Systems Biology databases to better understand off-target related toxicities. By analyzing a set of compounds that share a common toxic phenotype and by comparing the pathways they affect with pathways modulated by nontoxic compounds we are able to establish links between pathways and particular adverse effects. We further link these predictive results with literature data in order to explain why a certain pathway is predicted. Specifically, relevant pathways are elucidated for the side effects rhabdomyolysis and hypotension. Prospectively, our approach is valuable not only to better understand toxicities of novel compounds early on but also for drug repurposing exercises to find novel uses for known drugs.

Common Structural Cliques: a tool for protein structure and function analysis.

Proposed is a method for locating functionally relevant atoms in protein structures and a representation of spatial arrangements of these atoms allowing for a flexible description of active sites in proteins. The search method is based on comparison of local structure features of proteins that share a common biochemical function. The method does not depend on overall similarity of structures and sequences of compared proteins or on previous knowledge about functionally relevant residues. The compared protein structures are condensed to a graph representation, with atoms as nodes and distances as edge labels. Protein graphs are then compared to extract all possible Common Structural Cliques. These cliques are merged to create Structural Templates: graphs that describe structural analogies between compared proteins. Structures of serine endopeptidases were compared in pairs using the presented algorithm with different geometrical parameters. Additionally, a Structural Template was extracted from the structures of aminotransferases, two different proteins that catalyze the same type of chemical reaction. The results presented show that the method works efficiently even in the case of large protein systems and allows for extraction of common structural features from proteins catalyzing a particular chemical reaction, but that evolved from different ancestors by convergent evolution.