3-D QSAR studies of triazolinone based balanced AT1/AT2 receptor antagonists

AT1 Receptor Ligands: Virtual-Screening-Based Design with TOPP Descriptors, Synthesis, and Biological Evaluation of Pyrrolidine Derivatives

As a continuing effort to establish the structure-activity relationships (SARs) within the series of the angiotensin II antagonists (sartans), a pharmacophoric model was built by using novel TOPP 3D descriptors. Statistical values were satisfactory (PC4: r(2)=0.96, q(2) ((5) (random) (groups))=0.84; SDEP=0.26) and encouraged the synthesis and consequent biological evaluation of a series of new pyrrolidine derivatives. SAR together with a combined 3D quantitative SAR and high-throughput virtual screening showed that the newly synthesized 1-acyl-N-(biphenyl-4-ylmethyl)pyrrolidine-2-carboxamides may represent an interesting starting point for the design of new antihypertensive agents. In particular, biological tests performed on CHO-hAT(1) cells stably expressing the human AT(1) receptor showed that the length of the acyl chain is crucial for the receptor interaction and that the valeric chain is the optimal one.

Development of CoMFA models of affinity and selectivity to angiotensin II type-1 and type-2 receptors

The renin-angiotensin system (RAS) is of major importance in cardiovascular and renal regulation and has been an attractive target in drug discovery for a long time. The main receptors involved in the RAS are the Angiotensin type-1 (AT(1)) and type-2 (AT(2)) receptors, which are both activated by the endogenous octapeptide angiotensin II (AngII). This study describes the development of 3D-QSAR models for AT(1) and AT(2) receptor affinity and AT(1)/AT(2) receptor selectivity using CoMFA. A data set of 244 compounds, based on the triazolinone and quinazolinone structural classes was compiled from the literature. Before CoMFA could be performed, an alignment rule for the two structural classes was defined using the pharmacophore-searching program DISCOtech. Models were validated using a test set obtained by dividing the data set into a training set and test set using hierarchical clustering, based on the CoMFA fields, AT(1)-, AT(2)-receptor affinities, and AT(1)/AT(2) selectivity values. Predictive models with good statistics could be developed both for AT(1) and AT(2) receptor affinity as well as selectivity towards these receptors.

Synthesis of some substituted pyrazinopyridoindoles and 3D QSAR studies along with related compounds: piperazines, piperidines, pyrazinoisoquinolines, and diphenhydramine, and its semi-rigid analogs as antihistamines (H1)

3D QSAR studies on the title compounds led to the development of a model with three biophoric sites and six secondary sites viz. H-acceptor (ACC), H-donor (DON), heteroatom (presence), hydrophobic (hydrophobicity), steric (refractivity), and a ring (presence) along with total hydrophobicity and total refractivity as global properties. The model predicted the test set of compounds reasonably well. Three of the five newly synthesized 2-substituted octahydropyrazinopyridoindoles have shown potent antihistaminic H(1) activity with less toxicity and sedation potential.

Proposal of a New Binding Orientation for Non-Peptide AT1 Antagonists: Homology Modeling, Docking and Three-Dimensional Quantitative Structure−Activity Relationship Analysis

A three-dimensional model of the AT1 receptor was constructed by means of a homology modeling procedure, using the X-ray structure of bovine rhodopsin as the initial template and taking into account the available site-directed mutagenesis data. The docking of losartan and its active metabolite EXP3174, followed by 1 ns of molecular dynamics (MD) simulation inserted into the phospholipid bilayer, suggested a different binding orientation for these antagonists from those previously proposed. Furthermore, the docking of several non-peptide antagonists was used as an alignment tool for the development of a three-dimensional quantitative structure-activity relationship (3D-QSAR) model, and the good results confirmed our binding hypothesis and the reliability of the model.

Characterization of β3-adrenergic receptor: determination of pharmacophore and 3D QSAR model for β3 adrenergic receptor agonism

The beta3-adrenoreceptor (beta3-AR) has been shown to mediate various pharmacological and physiological effects such as lipolysis, thermogenesis, and intestinal smooth muscle relaxation. It also plays an important role in glucose homeostasis and energy balance. Molecular modeling studies were undertaken to develop predictive pharmacophoric hypothesis and 3D-QSAR model, which may explain variations in beta3-AR agonistic activity in terms of chemical features and physicochemical properties. The two softwares, CATALYST for pharmacophoric alignment and APEX-3D for 3D-QSAR modeling were used to establish the structure activity relationships for beta3-AR agonistic activity. Among the several statistically significant models, the selection of the best pharmacophore and 3D-QSAR model was based on its ability to estimate the activity of external test sets of similar and different structural types along with the reasonable consistency of the model with the limited information of the active site of beta3-AR. The final 3D-QSAR model was derived using the pharmacophoric alignments from the hypothesis which consisted of four chemical features: basic or positive ionizable feature on the nitrogen of the aryloxypropylamino group, two ring aromatic features corresponding to the phenyl ring of the phenoxide and the benzenesulphonamido groups and a hydrogen-bond donor (HBD) in the vicinity of the nitrogen atom of the benzenesulphonamido group with the most active molecule mapping in an energetically favorable extended conformation. This hypothesis was in agreement with the site directed mutagenesis studies on human beta3-AR and correlated well the observed and estimated activity both in, training and both the external test sets. It also mapped reasonably well to six beta3-AR agonists of different structural classes under clinical development and thus this hypothesis may have a universal applicability in providing a powerful template for virtual screening and also for designing new chemical entities (NCEs) as beta3-AR agonists.

CoMFA and Docking Studies on Glycogen Phosphorylase a Inhibitors as Antidiabetic Agents

Glycogen phosphorylase (GP(a)) is a specific target for the design of inhibitors and may prevent glycogenolysis under high glucose conditions in type II diabetes. The carboxamides first reported by Hoover D. J. et al. (J. Med. Chem. 1998, 41, 2934-2938) are one of the major classes of GP(a) inhibitors other than glucose derivatives. The recent, X-ray crystallographic analyses (Oikonomakos et al. Biochim. Biophys. Acta 2003, 1647, 325-332) have revealed a distinct mechanism of action for these inhibitors, which bind at a new allosteric site away from the inhibitory and catalytic sites. To elucidate the essential structural and physicochemical requirements responsible for binding to the GP(a) enzyme and to develop predictive models, CoMFA and docking studies have been carried out on a series of indole-2-carboxamide derivates. The CoMFA model developed using pharmacophoric alignments and hydrogen-bonding fields demonstrated high predictive ability against the training (r2 = 0.98, q2 = 0.68) and the test set (r2pred = 0.85). Further the superimposition of PLS coefficient contour maps from CoMFA with the GP(a) active site (PDB: 1lwo) has shown a high level of compatibility.

Non-peptide angiotensin II receptor antagonists: chemical feature based pharmacophore identification

Chemical feature based pharmacophore models were elaborated for angiotensin II receptor subtype 1 (AT(1)) antagonists using both a quantitative and a qualitative approach (Catalyst HypoGen and HipHop algorithms, respectively). The training sets for quantitative model generation consisted of 25 selective AT(1) antagonists exhibiting IC(50) values ranging from 1.3 nM to 150 microM. Additionally, a qualitative pharmacophore hypothesis was derived from multiconformational structure models of the two highly active AT(1) antagonists 4u (IC(50) = 0.2 nM) and 3k (IC(50) = 0.7 nM). In the case of the quantitative model, the best pharmacophore hypothesis consisted of a five-features model (Hypo1: seven points, one hydrophobic aromatic, one hydrophobic aliphatic, a hydrogen bond acceptor, a negative ionizable function, and an aromatic plane function). The best qualitative model consisted of seven features (Hypo2: 11 points, two aromatic rings, two hydrogen bond acceptors, a negative ionizable function, and two hydrophobic functions). The obtained pharmacophore models were validated on a wide set of test molecules. They were shown to be able to identify a range of highly potent AT(1) antagonists, among those a number of recently launched drugs and some candidates presently undergoing clinical tests and/or development phases. The results of our study provide confidence for the utility of the selected chemical feature based pharmacophore models to retrieve structurally diverse compounds with desired biological activity by virtual screening.

Development of 3D-QSAR models for 5-lipoxygenase antagonists: chalcones

5-Lipoxygenase inhibitors are of current interest for asthma therapy and inflammatory diseases. In order to identify the essential structural and physicochemical requirements in terms of common biophoric sites (pharmacophore) and secondary sites for binding and interacting with 5-lipoxygenase, a series of 51 compounds of chalcones has been used for the development of 3D-QSAR models on APEX-3D expert system. Among several models, the two models have been identified with the statistical criteria R(2)>0.75, Chance <0.001 and Match >0.7. Both the models (nos 1 and 2) with three biophoric sites and four secondary sites, showed very good correlation (r>0.9) between the observed and calculated or predicted activities.