SAR exploration of the non-imidazole histamine H3 receptor ligand ZEL-H16 reveals potent inverse agonism.

Histamine H3 receptor (H3 R) agonists without an imidazole moiety remain very scarce. Of these, ZEL-H16 (1) has been reported previously as a high-affinity non-imidazole H3 R (partial) agonist. Our structure-activity relationship analysis using derivatives of 1 identified both basic moieties as key interaction motifs and the distance of these from the central core as a determinant for H3 R affinity. However, in spite of the reported H3 R (partial) agonism, in our hands, 1 acts as an inverse agonist for Gαi signaling in a CRE-luciferase reporter gene assay and using an H3 R conformational sensor. Inverse agonism was also observed for all of the synthesized derivatives of 1. Docking studies and molecular dynamics simulations suggest ionic interactions/hydrogen bonds to H3 R residues D1143.32 and E2065.46 as essential interaction points.

Covalent Inhibition of the Histamine H3 Receptor.

Covalent binding of G protein-coupled receptors by small molecules is a useful approach for better understanding of the structure and function of these proteins. We designed, synthesized and characterized a series of 6 potential covalent ligands for the histamine H3 receptor (H3R). Starting from a 2-amino-pyrimidine scaffold, optimization of anchor moiety and warhead followed by fine-tuning of the required reactivity via scaffold hopping resulted in the isothiocyanate H3R ligand 44. It shows high reactivity toward glutathione combined with appropriate stability in water and reacts selectively with the cysteine sidechain in a model nonapeptide equipped with nucleophilic residues. The covalent interaction of 44 with H3R was validated with washout experiments and leads to inverse agonism on H3R. Irreversible binder 44 (VUF15662) may serve as a useful tool compound to stabilize the inactive H3R conformation and to study the consequences of prolonged inhibition of the H3R.

Docking pose selection by interaction pattern graph similarity: application to the D3R grand challenge 2015.

High affinity ligands for a given target tend to share key molecular interactions with important anchoring amino acids and therefore often present quite conserved interaction patterns. This simple concept was formalized in a topological knowledge-based scoring function (GRIM) for selecting the most appropriate docking poses from previously X-rayed interaction patterns. GRIM first converts protein-ligand atomic coordinates (docking poses) into a simple 3D graph describing the corresponding interaction pattern. In a second step, proposed graphs are compared to that found from template structures in the Protein Data Bank. Last, all docking poses are rescored according to an empirical score (GRIMscore) accounting for overlap of maximum common subgraphs. Taking the opportunity of the public D3R Grand Challenge 2015, GRIM was used to rescore docking poses for 36 ligands (6 HSP90α inhibitors, 30 MAP4K4 inhibitors) prior to the release of the corresponding protein-ligand X-ray structures. When applied to the HSP90α dataset, for which many protein-ligand X-ray structures are already available, GRIM provided very high quality solutions (mean rmsd = 1.06 Å, n = 6) as top-ranked poses, and significantly outperformed a state-of-the-art scoring function. In the case of MAP4K4 inhibitors, for which preexisting 3D knowledge is scarce and chemical diversity is much larger, the accuracy of GRIM poses decays (mean rmsd = 3.18 Å, n = 30) although GRIM still outperforms an energy-based scoring function. GRIM rescoring appears to be quite robust with comparison to the other approaches competing for the same challenge (42 submissions for the HSP90 dataset, 27 for the MAP4K4 dataset) as it ranked 3rd and 2nd respectively, for the two investigated datasets. The rescoring method is quite simple to implement, independent on a docking engine, and applicable to any target for which at least one holo X-ray structure is available.

Discovery of 4-anilino α-carbolines as novel Brk inhibitors.

Dysregulation of cell signalling processes caused by an enhanced activity of protein kinases mainly contributes to cancer progression. Protein kinase inhibitors have been established as promising drugs that inhibit such overactive protein kinases in cancer cells. The formation of metastases, which makes a therapy difficult, remains a great challenge for cancer treatment. Recently, breast tumor kinase (Brk) was discovered as novel and interesting target for a cancer therapy because Brk participates in both cell dysregulation and metastasis. We discovered 4-anilino substituted α-carboline compounds as a novel class of highly active Brk inhibitors. In the current work, structure-activity relationships are discussed including docking results obtained for 4-anilino α-carbolines. A first profiling of selective kinase inhibition and a proof of concept for the antiproliferative effects is demonstrated. These results qualify the compounds as a promising class of novel antitumor agents.

Virtual screening of PRK1 inhibitors: ensemble docking, rescoring using binding free energy calculation and QSAR model development.

Protein kinase C Related Kinase 1 (PRK1) has been shown to be involved in the regulation of androgen receptor signaling and has been identified as a novel potential drug target for prostate cancer therapy. Since there is no PRK1 crystal structure available to date, multiple PRK1 homology models were generated in order to address the protein flexibility. An in-house library of compounds tested on PRK1 was docked into the ATP binding site of the generated models. In most cases a correct pose of the inhibitors could be identified by ensemble docking, while there is still a challenge of finding a reasonable scoring function that is able to rank compounds according to their biological activity. We estimated the binding free energy for our data set of structurally diverse PRK1 inhibitors using the MM-PB(GB)SA and QM/MM-GBSA methods. The obtained results demonstrate that a correlation between calculated binding free energies and experimental IC50 values was found to be usually higher than using docking scores. Furthermore, the developed approach was tested on a set of diverse PRK1 inhibitors taken from literature, which resulted in a significant correlation. The developed method is computationally inexpensive and can be applied as a postdocking filter in virtual screening as well as for optimization of PRK1 inhibitors in order to prioritize compounds for further biological characterization.

Application of docking and QM/MM-GBSA rescoring to screen for novel Myt1 kinase inhibitors.

Identification of compounds that can bind to a target protein with high affinity is a nontrivial task in structure-based drug design. Several approaches ranging from simple scoring methods to more computationally demanding methods are usually applied for this purpose. In the current work, we used ligand docking in combination with QM/MM-GBSA, MM-GBSA, and MM-PBSA rescoring to discriminate between active and inactive Myt1 kinase inhibitors. Results show that QM/MM-GBSA rescoring performs better than normal docking scores or MM-GBSA rescoring in classifying active and inactive inhibitors. We also applied QM/MM-GBSA rescoring to estimate the binding affinities of compounds from different virtual screening runs. To prove our approach and to confirm its predictive power, a few compounds which were predicted to be active were purchased and experimentally tested. Among the five selected compounds, three showed significant inhibition of recombinant Myt1. PD-173952, which yielded a favorable QM/MM-GBSA binding free energy, showed a K(i) value of 8.1 nM. In addition, two compounds, PD-180970 and saracatinib, showed inhibition at the low micromolar level. Thus, the developed protocol might be useful for further virtual screening experiments to better discriminate between active and inactive compounds and to further optimize the identified hits.

Vanishing white matter: Eukaryotic initiation factor 2B model and the impact of missense mutations.

BACKGROUND: Vanishing white matter (VWM) is a leukodystrophy, caused by recessive mutations in eukaryotic initiation factor 2B (eIF2B)-subunit genes (EIF2B1-EIF2B5); 80% are missense mutations. Clinical severity is highly variable, with a strong, unexplained genotype-phenotype correlation. MATERIALS AND METHODS: With information from a recent natural history study, we severity-graded 97 missense mutations. Using in silico modeling, we created a new human eIF2B model structure, onto which we mapped the missense mutations. Mutated residues were assessed for location in subunits, eIF2B complex, and functional domains, and for information on biochemical activity. RESULTS: Over 50% of mutations have (ultra-)severe phenotypic effects. About 60% affect the ε-subunit, containing the catalytic domain, mostly with (ultra-)severe effects. About 55% affect subunit cores, with variable clinical severity. About 36% affect subunit interfaces, mostly with severe effects. Very few mutations occur on the external eIf2B surface, perhaps because they have minor functional effects and are tolerated. One external surface mutation affects eIF2B-substrate interaction and is associated with ultra-severe phenotype. CONCLUSION: Mutations that lead to (ultra-)severe disease mostly affect amino acids with pivotal roles in complex formation and function of eIF2B. Therapies for VWM are emerging and reliable mutation-based phenotype prediction is required for propensity score matching for trials and in the future for individualized therapy decisions.

Drug Development of Small-Molecule Inhibitors of AD-Relevant Kinases as Novel Perspective Multitargeted Approach.

So far monotargeted therapies in Alzheimers disease (AD) led to insufficient results. Slight improvements in the AD symptomatics have been limited to patients in the early stage of the disease. So multitargeting approaches have been started addressing amyloid plaques as preferred primary target structures beside acetylcholine esterase inhibition. Various protein kinases have been discussed to make a contribution to the progression of AD. So protein kinases are promising target structures for a perspective multitargeting. We identified substituted smallmolecule protein kinase inhibitors of the tricyclic benzofuropyridine type which showed partly nanomolar affinities to AD-relevant glycogen synthase kinase (gsk) 3ß, extracellular-signal regulated kinase (ERK) 2 and C-Jun-N-terminal kinase (JNK) 3. Substituent-dependent effects on the respective kinase inhibitions are discussed and inhibitor binding modes to those kinases are presented based on enzyme docking studies. Inhibitor effects on the tau protein target structure are shown for first compounds in cellular studies to prove the enzyme conditioned effects.

Identification of Highly Potent Protein Kinase†C-Related Kinase†1 Inhibitors by Virtual Screening, Binding Free Energy Rescoring, and in†vitro Testing.

Despite the considerable interest in protein kinase C-related kinase 1 (PRK1) as a target in cancer research, there is still a lack of PRK1 inhibitors with suitable selectivity profiles and physicochemical properties. To identify new PRK1 inhibitors we applied a virtual screening approach, which combines ensemble docking, minimization of the protein-ligand complex, binding free energy calculations, and application of quantitative structure-activity relationship (QSAR) models for predicting in vitro activity. The developed approach was then applied in a prospective manner to screen available libraries of kinase inhibitors from Selleck and GlaxoSmithKline (GSK). Compounds that showed favorable prediction were then tested in vitro for PRK1 inhibition. Some of the hits were found to inhibit PRK1 in the low-nanomolar range. Three in vitro hits were additionally tested in a mass-spectrometry-based cellular kinase profiling assay to examine selectivity. Our findings show that nanomolar and drug-like inhibitors can be identified by the virtual screening approach presented herein. The identified inhibitors are valuable tools for gaining a better understanding of PRK1 inhibition, and the identified hits can serve as starting points for further chemical optimization.

Tofacitinib and analogs as inhibitors of the histone kinase PRK1 (PKN1).

AIM: The histone kinase PRK1 has been identified as a potential target to combat prostate cancer but selective PRK1 inhibitors are lacking. The US FDA -approved JAK1-3 inhibitor tofacitinib also potently inhibits PRK1 in vitro. RESULTS: We show that tofacitinib also inhibits PRK1 in a cellular setting. Using tofacitinib as a starting point for structure-activity relationship studies, we identified a more potent and another more selective PRK1 inhibitor compared with tofacitinib. Furthermore, we found two potential PRK1/JAK3-selectivity hotspots. CONCLUSION: The identified inhibitors and the selectivity hotspots lay the basis for the development of selective PRK1 inhibitors. The identification of PRK1, but also of other cellular tofacitinib targets, has implications on its clinical use and on future development of tofacitinib-like JAK inhibitors. [Formula: see text].

Lestaurtinib inhibits histone phosphorylation and androgen-dependent gene expression in prostate cancer cells.

BACKGROUND: Epigenetics is defined as heritable changes in gene expression that are not based on changes in the DNA sequence. Posttranslational modification of histone proteins is a major mechanism of epigenetic regulation. The kinase PRK1 (protein kinase C related kinase 1, also known as PKN1) phosphorylates histone H3 at threonine 11 and is involved in the regulation of androgen receptor signalling. Thus, it has been identified as a novel drug target but little is known about PRK1 inhibitors and consequences of its inhibition. METHODOLOGY/PRINCIPAL FINDING: Using a focused library screening approach, we identified the clinical candidate lestaurtinib (also known as CEP-701) as a new inhibitor of PRK1. Based on a generated 3D model of the PRK1 kinase using the homolog PKC-theta (protein kinase c theta) protein as a template, the key interaction of lestaurtinib with PRK1 was analyzed by means of molecular docking studies. Furthermore, the effects on histone H3 threonine phosphorylation and androgen-dependent gene expression was evaluated in prostate cancer cells. CONCLUSIONS/SIGNIFICANCE: Lestaurtinib inhibits PRK1 very potently in vitro and in vivo. Applied to cell culture it inhibits histone H3 threonine phosphorylation and androgen-dependent gene expression, a feature that has not been known yet. Thus our findings have implication both for understanding of the clinical activity of lestaurtinib as well as for future PRK1 inhibitors.