Mass-spectrometric studies of new 6-nitroquipazines—serotonin transporter inhibitors

Six synthesized 6-nitroquipazine derivatives were examined by electron ionization (EI) and electrospray ionization (ESI) mass spectrometry in positive and negative ion mode. The compounds exhibit high affinity for the serotonin transporter (SERT) and belong to a new class of SERT inhibitors. The EI mass spectra registered in negative ion mode showed prominent molecular ions for all the compounds studied. All EI mass spectra and all ESI mass spectra showed similar fragmentation pathways of molecular ions, but the pathways differed between EI and ESI. The differences were explained with the aid of theoretical evaluation of the stability of the respective radical ions (EI MS) and protonated ions (ESI MS)

COMBINATIONS OF ISOTHIOCYANATES WITH DRUGS – A CHANCE OR THREAT TO CHEMOPREVENTION AND CANCER TREATMENT?

Isothiocyanates (ITCs) are a group of compounds of natural origin which exhibit anticancer properties. In addition to the cytotoxic impact on cancer cells, confirmed in the multiple cell lines and the in vivo models, ITCs exhibit the cytoprotective effect in normal cells by regulating the activity of enzymes involved in xenobiotic metabolism. These properties of ITCs have led to a continuing increase in the number of studies which have shown that ITCs can sensitize cancer cells to cytostatic drugs used as standard in cancer therapies. On the other hand these compounds may decrease the effectiveness of drugs by deregulating the metabolising system of the cell. This paper discusses the results of preclinical study on ITCs applications in combination therapy as well as their role in drug metabolism

Oncotoxic Properties of Serotonin Transporter Inhibitors and 5-HT1A Receptor Ligands

The cytotoxic activity of several serotonin transporter (SERT) inhibitors and subtype of serotonin receptor 1A (5-HT1A receptor) ligands have been examined in androgen-insensitive human PC-3 prostate and neuroblastoma SH-SY5Y cancer cells. Almost all of the studied compounds (except 5-HT1A receptor agonist (2R)-(+)-8-Hydroxy-2-(di-n-propylamino)tetralin hydrobromide (8-OH-DPAT)) exhibited absolute cytotoxic activity against the examined cancer cells. The compound 4-Fluoro-N-[2-[4-(7-methoxy-1-naphthalenyl)-1-piperazinyl]ethyl]benzamide hydrochloride (S14506) that showed highest activity against neuroblastoma tumors was the 5-HT1A receptor agonist (although not alike other 5-HT1A receptor agonists). On the other hand, the compound 6-nitro-2-(4-undecylpiperazin-1-yl)quinoline hydrochloride (AZ07) that had the highest activity against PC-3 prostate cancer cells was a compound exhibiting antagonistic activity against the 5-HT1A receptor. Thus, compounds of oncotoxic properties S14506 and AZ07 should be evaluated further for their potential use in the prevention and treatment of cancer. Most of the 15 compounds tested exhibited either agonistic or antagonistic activity for both the cyclic adenosine monophosphate (cAMP) and extracellular signal-regulated kinase 1 and 2 (ERK1/2) pathways in human embryonic kidney 293 (HEK293) cells that overexpress the 5HT1AR gene. However, compounds paroxetine, N-Ac-paroxetine and 2-[4-(cyclobutylmethyl)piperazin-1-yl]-6-nitroquinoline hydrochloride (AB22) simultaneously exhibited antagonistic activity on the cAMP pathway and agonistic activity on the ERK1/2 pathway. Fluoxetine relative to compound AZ07 had almost three times lower cytotoxic activity against PC-3 prostate cancer cells. However, the proapoptotic activity of fluoxetine compared to compound AZ07 is almost two times higher which would suggest that the cytotoxic activity of both compounds may be dependent on different cell death mechanisms. Compound S14506 was found to be an antagonist of the serine-threonine protein kinase B (Akt) pathway. Prosurvival Akt activity may be reversed by Akt antagonists. Therefore, the antagonistic activity of S14506 on the Akt pathway may evoke caspase-3 expression and cytotoxicity. It appears that one should not expect a straightforward relationship between the activation of particular serotonergic pathways by selective serotonin reuptake inhibitors (SSRIs) and 5-HT1A receptor ligands and their cytotoxic or cytoprotective activity. Additionally, nuclear transcription factor κB (NF-κB), which may be involved in 5-HT-dependent biochemical pathways by coordinating different subunits in the formation of a dimer, may regulate the transcription of different transduction pathways. Therefore, it can be suggested that the mechanism of the cytotoxic activity of certain compounds (serotonergic against nonserotonergic) may depend on the compound and cancer type being examined. Docking studies showed that S14506, buspirone and spiperone bind in similar ways in the 5-HT1A receptor model and interacted with similar 5-HT1A receptor residues. S14506 and spiperone were found to be located closer to both phenylalanines in TM6 than buspirone, thus exhibiting more antagonist binding modes

The best linear combination of pharmacophore models obtained for manual clustering and MCC optimization.

<p>The best linear combination of pharmacophore models obtained for manual clustering and MCC optimization (manual/random/hit-once; see also <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0084510#pone-0084510-g004" target="_blank">Figures 4</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0084510#pone-0084510-g006" target="_blank">6</a>). For each hypothesis the best fitting compound is presented, along with a matrix of distances (in angstroms) between features and a name of cluster it was developed on. The feature abbreviations used are: hydrogen bond acceptor – <b>A</b>, hydrogen bond donor – <b>D</b>, hydrophobic group – <b>H</b>, positively charged group – <b>P</b>, aromatic ring – <b>R</b>.</p

From Homology Models to a Set of Predictive Binding Pocketsa 5HT1A Receptor Case Study

Despite its remarkable importance in the arena of drug design, serotonin 1A receptor (5-HT(1A)) has been elusive to the x-ray crystallography community. This lack of direct structural information not only hampers our knowledge regarding the binding modes of many popular ligands (including endogenous neurotransmitter – serotonin), but also limits the search for more potent compounds. In this paper we shed new light on the 3D pharmacological properties of the 5-HT(1A) receptor by using a ligand-guided approach (ALiBERO) grounded in the Internal Coordinate Mechanics (ICM) docking platform. Starting from a homology template and set of known actives, the method introduces receptor flexibility via Normal Mode Analysis and Monte Carlo sampling, to generate a subset of pockets that display enriched discrimination of actives from inactives in retrospective docking. Here, we thoroughly investigated the repercussions of using different protein templates and the effect of compound selection on screening performance. Finally, the best resulting protein models were applied prospectively in a large virtual screening campaign, in which two new active compounds were identified that were chemically distinct from those described in the literature

The development of an optimal combination of pharmacophore models.

<p>The development of an optimal combination of pharmacophore models. Transparent boxes show the logical steps of the workflow; cylinders represent data sources; colored boxes reflect the compound character: gray – inactives, orange – actives or the active’s selection method (blue, red or green), which is consequently used in subsequent figures. The population of the compound set is given in brackets. Thick arrows indicate the use of data sets.</p

Exemplary pharmacophore hypothesis selected for arylpiperazines with classical amide fragment.

<p>Exemplary pharmacophore hypothesis selected for arylpiperazines with classical amide fragment mapping 6 out of 10 cluster representatives. The model fit 462 of the 533 compounds (87%) in the cluster. The feature abbreviations are: hydrogen-bond donor – <b>D</b>, positively charged group – <b>P</b>, aromatic ring – <b>R</b>.</p

A dendrogram obtained using the manual clustering procedure.

<p>A dendrogram obtained using the manual clustering procedure. The number of compounds comprising each cluster is given in brackets. The last column presents a feature composition of the pharmacophore model created for a given cluster. The feature abbreviations used are: hydrogen bond acceptor – <b>A</b>, hydrogen bond donor – <b>D</b>, hydrophobic group – <b>H</b>, positively charged group – <b>P</b>, aromatic ring – <b>R</b>.</p

An optimization curve for the investigated parameters of a top-ranked linear combination of MCC.

<p>An optimization curve for the investigated parameters of a top-ranked linear combination of MCC (M2D/random/hit-once); arrows indicate the maximum value: MCC reached a rate of 0.686 for 10 hypotheses (also see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0084510#pone-0084510-g006" target="_blank">Figure 6</a>); the optimization of accuracy and recall had the highest values for a combination of 8 and 9 hypotheses, respectively (also see Figures S1 and S2).</p