Abstract: The potential efficacy of GABAB receptor agonists in the treatment of pain, drug addiction, epilepsy, cognitive dysfunctions, and anxiety disorders is supported by extensive preclinical and clinical evidence. However, the numerous side effects produced by the GABAB receptor agonist, baclofen, considerably limit the therapeutic use of this compound. The identification of positive allosteric modulators (PAMs) of the GABAB receptor (GABAB PAMs) may constitute a novel approach in the pharmacological manipulation of the GABAB receptor leading to fewer side effects. The present study reports the identification of two novel compounds, methyl 2-(1-adamantanecarboxamido)-4-ethyl-5-methylthiophene-3-carboxylate (COR627) and methyl 2-(cyclohexanecarboxamido)-4-ethyl-5-methylthiophene-3-carboxylate (COR628), that act as GABAB PAMs in (a) rat cortical membranes, and (b) in vivo assay. Both compounds potentiated GABA- and baclofen-stimulated guanosine 5'-O-(3-[35S]thio)-triphosphate ([35S]GTPγS) binding to native GABAB receptors, whilst producing no effect when given alone. GABA concentration-response curves in the presence of fixed concentrations of COR627 and COR628 revealed an increase of potency of GABA rather than its maximal efficacy. In radioligand binding experiments (displacement of the GABAB receptor antagonist, [3H]CGP54626), both COR627 and COR628 increased the affinity of high- and low- affinity binding sites for GABA, producing no effect when administered alone up to a concentration of 1 mM. In vivo experiments indicated that pretreatment with per se ineffective doses of COR627 and COR628 potentiated the sedative/hypnotic effect of baclofen. In conclusion, COR627 and COR628 may represent two additional tools for use in investigating the roles and functions of the positive allosteric modulatory binding sites of the GABAB receptor.
Abstract: In our search for new cannabinoid receptor modulators, we describe herein the design and synthesis of three sets of indole-based ligands characterized by an acetamide, oxalylamide, or carboxamide chain, respectively. Most of the compounds showed affinity for CB2 receptors in the nanomolar range, with Ki values spanning 3 orders of magnitude (377–0.37 nM), and moderate to good selectivity over CB1 receptors. Their in vitro functional activity as inverse agonists was confirmed in vivo in the formalin test of acute peripheral and inflammatory pain in mice, in which compounds 10a and 11e proved to be able to reverse the effect of the CB2 selective agonist COR167.
Abstract: Here we report the synthesis and evaluation of antiplasmodial activity of a novel series of bicyclic peroxides inspired by the marine natural compound dihydroplakortin. We developed a synthetic strategy leading to the dihydroplakortin-related peroxides in only few steps. The in vitro antiplasmodial potency of the peroxides was similar or greater than that of the reference natural compound and structure-activity relationship studies revealed several key structural requirements for activity and potency.
Abstract: This paper describes a three-dimensional quantitative structure-selectivity relationships (3D-QSSR) study for selectivity of a series of ligands for cannabinoid CB1 and CB2 receptors. 3D-QSSR exploration was expected to provide design information for drugs with high selectivity toward the CB2 receptor. The proposed 3D computational model was performed by Phase and generated taking into account a number of structurally diverse compounds characterized by a wide range of selectivity index values. The model proved to be predictive, with r2 of 0.95 and Q2 of 0.63. In order to get prospective experimental validation, the selectivity of an external data set of 39 compounds reported in the literature was predicted. The correlation coefficient (r2=0.56) obtained on this unrelated test set provided evidence that the correlation shown by the model was not a chance result. Subsequently, we essayed the ability of our approach to help the design of new CB2-selective ligands. Accordingly, based on our interest in studying the cannabinergic properties of quinolones, the N-(adamantan-1-yl)-4-oxo-8-methyl-1-pentyl-1,4-dihydroquinoline-3-carboxamide (65) was considered as a potential synthetic target. The log(SI) value predicted by using our model was indicative of high CB2 selectivity for such a compound, thus spurring us to synthesize it and to evaluate its CB1 and CB2 receptor affinity. Compound 65 was found to be an extremely selective CB2 ligand as it displayed high CB2 affinity (Ki=4.9 nM), while being devoid of CB1 affinity (Ki>10,000 nM). The identification of a new selective CB2 receptor ligand lends support for the practicability of quantitative ligand-based selectivity models for cannabinoid receptors. These drug discovery tools might represent a valuable complementary approach to docking studies performed on homology models of the receptors.
Abstract: A ligand-based pharmacophore approach for the prediction of antiestrogenic activity to be used as an in silico screening tool for bioactive compounds including natural products was developed using Catalyst HypoGen. The generated pharmacophore hypothesis (HYPO-7) consisted of five features, namely, one hydrophobic (HY1), two hydrophobic aromatic (HY2), one hydrogen-bond acceptor (HBA), and one hydrogen-bond donor (HBD). HYPO-7 successfully predicted the lack of cytotoxicity of a number of new metabolites isolated from the red alga Laurencia glandulifera. Furthermore, a screening of the Asinex Gold Collection database was performed by coupling HYPO-7 with a docking filtration, which resulted in a restricted set of 12 new scaffolds to be investigated as potential SERMs. The inhibitory activity of these compounds was evaluated in vitro using MCF7 human breast adenocarcinoma cell line. Ten out of the twelve compounds exhibited inhibitory activity with IC50 values between 26 and 188 μM. This result shows that application of HYPO-7 could assist in the selection of potentially active compounds, thus expediting the hit discovery process.
Abstract: Five new C15 acetogenin en-ynes (1−5) with a rare tetrahydrofuran moiety and a linear biosynthetic precursor (6) were isolated from an organic extract of Laurencia glandulifera, collected from the island of Crete in the south Aegean Sea. The structures of the new natural products, as well as their relative configuration, were established by means of spectroscopic data analysis. The cytotoxicity of the isolated natural products was evaluated against five human tumor cell lines.
Abstract: In the latest two or three years progressive
applications of pharmacophore modeling continue to
appear in literature. Pharmacophore based parallel
screening, for instance, has been introduced in 2006.
Moreover, in 2008, a survey discussing the prospective
impact of virtual screening techniques in the
discovery of bioactive natural products has been
published. Finally, virtual screening techniques
from the drug discovery field are beginning to
be used for profiling the bioactivity of chemicals
(especially those of potential environmental concern) with the aim of
prioritizing compounds for further testing using more complex systems and
reducing and ultimately replacing the use of animals in regulatory testing.
Pharmacophore modeling might be extremely helpful to allow full
achievement of all the above mentioned goals. In this contribution we report
a couple of case studies where pharmacophore generation and handling
played a pivotal role. In particular, in the first example, the development of a
novel computational pre-screening approach to be used as an in silico
filtering tool for natural products is described, applied to the estrogen
receptor-α subtype. In the second study, differently, the validation of a
preexisting pharmacophore by the prediction of the antifungal activities of
new azole compounds is discussed. In this case, it comes to light the
importance and utility of adding excluded volumes to a pharmacophore, to
increase its predictivity.
Abstract: We have applied a novel approach to generate a ligand-based pharmacophore model. The pharmacophore was built from a set of 42 compounds showing activity against MCF-7 cell line derived from human mammary adenocarcinoma, using the program PHASE, implemented in the Schrödinger suite software package. PHASE is a highly flexible system for common pharmacophore identification and assessment and 3D-database creation and searching. The best pharmacophore hypothesis showed five features: two hydrogen-bond acceptors, one hydrogen-bond donor, and two aromatic rings. The structure–activity relationship (SAR) so acquired was applied within PHASE for molecular alignment in a comparative molecular field analysis 3D-QSAR study. The 3D-QSAR model yielded a test set r2 equal to 0.97 and demonstrated to be highly predictive with respect to an external test set of 18 compounds (r2 =0.93). In summary, in this study we improved a previously developed Catalyst MCF-7 inhibitory pharmacophore, and established a predictive 3D-QSAR model. We have further used this model to detect novel MCF-7 cell line inhibitors through 3D database searching and docking simulation
Abstract: We have applied a novel approach to generate a ligand-based pharmacophore model. The pharmacophore was built from a set of 42 compounds showing activity against MCF-7 cell line derived from human mammary adenocarcinoma, using the program PHASE, implemented in the Schrödinger suite software package. PHASE is a highly flexible system for common pharmacophore identification and assessment and 3D-database creation and searching. The best pharmacophore hypothesis showed five features: two hydrogen-bond acceptors, one hydrogen-bond donor, and two aromatic rings. The structure–activity relationship (SAR) so acquired was applied within PHASE for molecular alignment in a comparative molecular field analysis (CoMFA) 3D-QSAR study. The 3D-QSAR model yielded a test set r2 equal to 0.97 and demonstrated to be highly predictive with respect to an external test set of 18 compounds (r2 =0.93). In summary, in this study we improved a previously developed Catalyst MCF-7 inhibitory pharmacophore, and established a predictive CoMFA 3D-QSAR model. We have further used this model to detect novel MCF-7 cell line inhibitors through 3D database searching.
Abstract: Estrogen receptors (ER-α and ER-β subtypes) are members of a superfamily of ligand-activated transcription factors. Stimulation of estrogen receptors by endogenous estrogens plays an
important role in both male and female physiology. Estrogens are involved in the regulation of cholesterol and lipid levels, the skeletal system, the central nervous system, and reproductive
functions. However, estrogen stimulation is also implicated in the development of breast cancer. Consequently, many estrogen receptor ligands (SERMs: selective estrogen receptor modulators)
are being developed with the aim of preventing estrogen mediated tumor growth. MCF-7 cells are a well-characterized estrogen receptor (ER) positive control cell line and therefore are a useful
in vitro model to study the activity of new metabolites against breast cancer.
Abstract: Un modello farmacoforico tridimensionale per il recettore alfa degli estrogeni (ER-α) è stato
sviluppato usando il software CATALYST®, con la possibilità di individuare nuovi inibitori del
target cellulare attraverso il virtual screening. Molecole con possibile attività antiestrogenica (24
composti), con diverse proprietà strutturali, e con valori di attività , espressi in IC50, compresi tra 0.02 e 267.4 μM per la lina cellulare MCF-7 (adenocarcinoma delle ghiandole mammarie), sono stati selezionati per comporre il Training set. La generazione dell' ipotesi è stata eseguita in HypoRefine utilizzando il Training set selezionato ed inserendo le seguenti features: HBD (Hydrogen Bond Donor), HBA (Hydrogen Bond Acceptor) HYDROPHOBIC, HYDROPHOBIC Aromatic e RING AROMATIC ed un valore di Uncert di 1.5. La migliore ipotesi trovata (Hypo 7) ha mostrato un coefficiente di correlazione (r2) di 0.955 un RMSD pari 2.6 ed un costo totale di 81.2. Hypo 7 è stata validata per mezzo di un Test set formato da 29 composti mostrando correlazione (r2) pari a 0.914 tra attività sperimentale e stimata. L'ipotesi generata è in grado di discriminare in modo corretto tra molecole attive ed inattive. Le features chimiche che rappresentano il modello esprimono perfettamente il binding mode sperimentale dei ligandi all’interno della tasca recettoriale di ER-α. Per questa serie di interessanti caratteristiche scaturite dall'analisi dell'ipotesi numero 7 (Hypo 7) proponiamo la possibilità di usare il modello come primo passo per la possibile identificazione di inibitori più potenti e con livelli di tossicità più bassi per il recettore degli estrogeni (ER-α) nei tumori ormone-dipendenti come quello delle ghiandole mammarie caratterizzato nella linea cellulare MCF-7.
