Modeling of alphak/gamma2 (k=1, 2, 3 and 5) interface of GABA A receptor and docking studies with zolpidem: implications for selectivity

The three-dimensional models of the alphak/gamma2 (k=1, 2, 3 and 5) interface of GABA(A) receptors, which included the agonist-binding site, were constructed and validated by molecular modeling technology. To investigate the mechanism of alpha subunit selectivity of zolpidem, docking calculations were used to illustrate the potential binding modes of zolpidem with different alpha subtypes. The results revealed that there were three reasons resulting in the distinct binding affinity of zolpidem to different alpha subtype. Firstly, the number of hydrogen bonds of agonist-receptor complex would determine the magnitude of binding affinity. Secondly, the His residue in loop A of alpha subunit was indicated as a key role of benzodiazepine binding. Thirdly, the side chain of Glu in loop C reduced the affinity of zolpidem to those receptors containing alpha2, alpha3 or alpha5 subunits.     

Structural determinants of the alpha2 adrenoceptor subtype selectivity

Alpha2-adrenergic receptor (α2-AR) subtypes, acting mainly on the central nervous and cardiovascular systems, represent important targets for drug design, confirmed by the high number of studies published so far. Presently, only a few α2-AR subtype selective compounds are known. Using homology modeling and ligand docking, the present study analyzes the similarities and differences between binding sites, and between extracellular loops of the three subtypes of α2-ARs. Several α2-AR subtype selective ligands were docked into the active sites of the three α2-AR subtypes, key interactions between ligands and receptors were mapped, and the predicted results were compared with the available experimental data. Binding site analysis reveals a strong identity between important amino acid residues in each receptor, the very few differences being the key toward modulating selectivity of α2-AR ligands. The observed differences between binding site residues provide an excellent starting point for virtual screening of chemical databases, in order to identify potentially selective ligands for α2-ARs.     

An investigation of structurally diverse carbamates for acetylcholinesterase (AChE) inhibition using 3D-QSAR analysis

In order to identify the essential structural features and physicochemical properties for acetylcholinesterase (AChE) inhibitory activity in some carbamate derivatives, the systematic QSAR (Quantitative Structure Activity Relationship) studies (CoMFA, advance CoMFA and CoMSIA) have been carried out on a series of (total 78 molecules) taking 52 and 26 molecules in training and test set, respectively. Statistically significant 3D-QSAR (three-dimensional Quantitative Structure Activity Relationship) models were developed on training set molecules using CoMFA and CoMSIA and validated against test set compounds. The highly predictive models (CoMFA q(2)=0.733, r(2)=0.967, predictive r(2)=0.732, CoMSIA q(2)=0.641, r(2)=0.936, predictive r(2)=0.812) well explained the variance in binding affinities both for the training and the test set compounds. The generated models suggest that steric, electrostatic and hydrophobic interactions play an important role in describing the variation in binding affinity. In particular the carbamoyl nitrogen should be more electropositive; substitutions on this nitrogen should have high steric bulk and hydrophobicity while the amino nitrogen should be electronegative in order to have better activity. These studies may provide important insights into structural variations leading to the development of novel AChE inhibitors which may be useful in the development of novel molecules for the treatment of Alzheimer's disease.     

Homology modeling of the estrogen receptor subtype beta (ER-beta) and calculation of ligand binding affinities.

Estrogen is a steroid hormone playing critical roles in physiological processes such as sexual differentiation and development, female and male reproductive processes, and bone health. Numerous natural and synthetic environmental compounds have been shown capable of estrogenic effects. This area has been the focus of significant fundamental and applied research due both to the potential detrimental effects of these compounds upon normal physiological processes and to the potential beneficial effects of tissue-selective estrogen agonists/antagonists for the prevention and treatment of numerous diseases. Genomic effects of the active form of estrogen, 17beta-estradiol, are mediated through at least two members of the steroid hormone receptor superfamily, estrogen receptor subtype alpha (ER-alpha) and estrogen receptor subtype beta (ER-beta). At the time of this work, the X-ray crystal structure of the ER-alpha had been elucidated, however, coordinates of the ER-beta were not publicly available. Based upon the significant structural conservation across members of the steroid hormone receptor family, and the high sequence homology between ER-alpha and ER-beta (>60%), we have developed a homology model of the ER-beta structure. Using the crystal structure of ER-alpha and the homology model of ER-beta, we demonstrate a strong correlation between computed values of the binding-energy and published values of the observed relative binding affinity (RBA) for a variety of compounds for both receptors, as well as the ability to identify receptor subtype selective compounds. Furthermore, using the recently available crystal structure of ER-beta for comparison purposes, we show that not only is the predicted homology model structurally accurate, but that it can be used to assess ligand binding affinities.     

Selective pharmacophore design for alpha1-adrenoceptor subtypes

Alpha1-adrenoceptors are G-protein coupled receptors found in a variety of vascular tissues and responsible for vasoconstriction. Selectivity for each of the three subtypes is an important consideration in drug design in order to minimise the possibility of side effects. Using Catalyst we developed ligand-based pharmacophores from alpha(1a,b,d)-selective antagonists available in the literature using three separate training sets. Four-feature pharmacophores were developed for the alpha(1a) and alpha(1b) subtype-selective antagonists and a five-feature pharmacophore was developed for the alpha(1d) subtype-selective antagonists. The alpha(1a) pharmacophore represents both class I and II compounds with good predictivity for other compounds outside the training set as well. The alpha(1b) pharmacophore best predicts the activity of prazosin analogues as these make up the majority of alpha(1b)-selective antagonists. Unexpectedly, no positive ionisable feature was incorporated in the alpha(1b) pharmacophore. The alpha(1d) pharmacophore was based primarily on one structural class of compounds, but has good predictivity for a heterogeneous test set. Preliminary docking studies using AutoDock and optimised alpha1-adrenoceptor homology models, conducted with the antagonists prazosin (32) and 66, showed good agreement with the findings from the pharmacophores.     

Selectivity-based QSAR approach for screening and evaluation of TRH analogs for TRH-R1 and TRH-R2 receptors subtypes

Design and development of therapeutically useful CNS selective thyrotropin-releasing hormone (TRH) analogs acting on TRH-R2 receptor subtype, exerting weak or no TRH-R1-mediated TSH-releasing side effects has gained imagination of researchers in the recent past. The present study reports the development and implementation of a selectivity-based QSAR approach for screening selective agonists of TRH-R2 receptor subtype. The statistically significant predictive models were thoroughly validated using an external validation set whose activity was previously unknown. The model was able to predict preference for either of the receptor subtypes successfully.     

Gas sensitivity of Zn doped α-Fe2O3(SO4, Sn, Zn) to carbon monoxide

It is shown that the doping of Zn and Sn can improve the gas sensitivity of α-Fe₂O₃-based sensing material to CO. X-ray photo-electron spectroscopy analysis suggests that this is mainly due to the fact that the simultaneous doping of Zn and Sn can increase the S and hence SO₄²⁻ contents in the α-Fe₂O₃(SO₄²⁻, Sn, Zn) sensing material. The results also suggest that under a given condition, the gas sensitivity of α-Fe₂O₃(SO₄²⁻, Sn, Zn) to CO can be optimised by properly adjusting the doped Zn content.     

Hydration of T-antigen Gal beta(1-3)GalNAc and the isomer Gal beta(1-3)GlcNAc by molecular dynamics simulations

We present a 250 ps molecular dynamics simulation of the T-antigen Gal beta(1-3)GalNAc and its isomer Gal beta(1-3)GlcNAc in the classic Gibbs Ensemble, Number of particles, Pressure and Temperature (NPT) with explicit representation of 432 water molecules. We computed the radial distribution function, equilibrium conformation, intramolecular and intermolecular hydrogen bonds, and water residence time to characterize the hydration pattern of these sugars, which are not very different and exhibit hydrophilic behavior. Based on hydration dynamics, it was concluded that these sugars should be classified as negative hydrated. Formation of an intramolecular hydrogen bond between the ring oxygen atom O5 of the first unit and the OH4' group of glycoside of the second unit might influence interaction with the antigenic receptor and could explain the main difference of affinities between them.     

Molecular simulation study of the unbinding of α-conotoxin [ϒ4E]GID at the α7 and α4β2 neuronal nicotinic acetylcholine receptors

The α7 and α4β2 neuronal nicotinic receptors belonging to the family of ligand-gated ion channels are most prevalent in the brain, and are implicated in various neurodegenerative disorders. α-conotoxin GID (and its analogue [ϒ4E]GID) specifically inhibits these subtypes, with more affinity towards the human α7 (hα7) subtype, and is valuable in understanding the physiological roles of these receptors. In this study, we use umbrella-sampling molecular dynamics simulations to understand the mechanism of interaction between [ϒ4E]GID and the agonist binding pockets of the α4β2 and the hα7 receptors, and to estimate their relative binding affinities (ΔG_bind). The obtained ΔG_bind values indicate stronger interaction with the hα7 receptor, in agreement with previous experimental studies. Simulations also revealed different unbinding pathways between the two receptor subtypes, enabling identification of a number of interactions at locations far from the orthosteric binding site which may explain the difference in [ϒ4E]GID potency. The pathways identified will help in the design of novel conotoxins with increased potency at α4β2, for which there is currently no known highly potent conotoxin inhibitor. Computational mutational free energy analyses also revealed a number of possible single-site mutations to GID which might enhance its selective binding to α4β2 over α7.     

Exploring putative inhibitors of Death Associated Protein Kinase 1 (DAPK1) via targeting Gly-Glu-Leu (GEL) and Pro-Glu-Asn (PEN) substrate recognition motifs

Recently, a new signaling complex Death Associated Protein Kinase 1 (DAPK1) ̶ N-methyl-D-aspartate receptor subtype 2B (NMDAR2B or NR2B) engaged in the neuronal death cascade was identified and it was found that after stroke injury, N-methyl-D-aspartate glutamate (NMDA) receptors interact with DAPK1 through NR2B subunit and lead to excitotoxicity via over-activation of NMDA receptors. An acute brain injury, such as stroke, is a serious life-threatening medical condition which occurs due to poor blood supply to the brain and further leads to neuronal cell death. During a stroke, activated DAPK1 migrates towards the extra-synaptic site and binds to NR2B subunit of NMDA receptor. It is this DAPK1-NR2B interaction that arbitrates the pathological processes like apoptosis, necrosis, and autophagy of neuronal cells observed in stroke injury, hence we aimed to inhibit this vital interaction to prevent neuronal damage. In the present study, using PubChem database, we applied an integrative approach of virtual screening and molecular dynamic simulations and identified a potential lead compound 11 that interrupts DAPK1-NR2B interaction by competing with both ATP and substrate for their binding sites on DAPK1. This inhibitor was found potent and considerably selective to DAPK1 as it made direct contact with the ATP binding sites as well as substrate recognition motifs: Gly-Glu-Leu (GEL) and Pro-Glu-Asn (PEN). Further in vitro and in vivo experiments are demanded to validate the efficacy of compound 11 nevertheless, it can be considered as suitable starting point for designing DAPK1 inhibitors.     

CoMFA methodology in structure-activity analysis of hexahydro- and octahydropyrido[1,2-c]pyrimidine derivatives based on affinity towards 5-HT1A, 5-HT2A and alpha1-adrenergic receptors

Structural features of the pyrido[1,2-c]pyrimidine derivatives with arylpiperazine moiety and their affinities towards 5-HT1A, 5-HT2A and alpha1-adrenergic receptors were analyzed using the CoMFA procedure. On the basis of 3D-QSAR models for the 5-HT2A and alpha1-adrenergic receptors, four compounds with expected better affinity/selectivity were proposed and synthesized. The affinities obtained confirm experimentally the usefulness of CoMFA models. Our results suggest that active conformations adopted by the studied molecules when interacting with the receptors are neutral instead of the protonated ones.     

Structural basis for ligand recognition at the benzodiazepine binding site of GABAA alpha 3 receptor, and pharmacophore-based virtual screening approach

Given the heterogeneity of GABA(A) receptor, the pharmacological significance of identifying subtype selective modulators is increasingly being recognized. Thus, drugs selective for GABA(A) alpha(3) receptors are expected to display fewer side effects than the drugs presently in clinical use. Hence we carried out 3D QSAR (three-dimensional quantitative structure-activity relationship) studies on a series of novel GABA(A) alpha(3) subtype selective modulators to gain more insight into subtype affinity. To identify the 3D functional attributes required for subtype selectivity, a chemical feature-based pharmacophore, primarily based on selective ligands representing diverse structural classes was generated. The obtained pseudo receptor model of the benzodiazepine binding site revealed a binding mode akin to "Message-Address" concept. Scaffold hopping was carried out across multi-conformational May Bridge database for the identification of novel chemotypes. Further a focused data reduction approach was employed to choose a subset of enriched compounds based on "Drug likeness" and "Similarity-based" methods. These results taken together could provide impetus for rational design and optimization of more selective and high affinity leads with a potential to have decreased adverse effects.     

Controlled synthesis and gas-sensing properties of hollow sea urchin-like α-Fe2O3 nanostructures and α-Fe2O3 nanocubes

Hollow sea urchin-like α-Fe₂O₃ nanostructures were successfully synthesized by a hydrothermal approach using FeCl₃ and Na₂SO₄ as raw materials, and subsequent annealing in air at 600 °C for 2 h. The hollow sea urchin-like α-Fe₂O₃ nanostructures with the diameters of 2–4.5 μm consist of well-aligned α-Fe₂O₃ nanorods with an average length of about 1 μm growing radially from the centers of the nanostructures, have a hollow interior with a diameter of about 2 μm. α-Fe₂O₃ nanocubes with a diameter of 700–900 nm were directly obtained by a hydrothermal reaction of FeCl₃ at 140 °C for 12 h. The response S_r (S_r = R_a/R_g) of the hollow sea urchin-like α-Fe₂O₃ nanostructures reached 2.4, 7.5, 5.9, 14.0 and 7.5 to 56 ppm ammonia, 32 ppm formaldehyde, 18 ppm triethylamine, 34 ppm acetone, and 42 ppm ethanol, respectively, which was excess twice that of the α-Fe₂O₃ nanocubes and the nanoparticle aggregations. Our results demonstrated that the hollow sea urchin-like α-Fe₂O₃ nanostructures were very promising for gas sensors for the detection of flammable and/or toxic gases with good-sensing characteristics.     

Mining the Chemical Abstracts database with pharmacophore-based queries

A method is described to convert 3D patterns of pharmacophoric groups into 2D queries for molecular substructure searches of the Chemical Abstracts database with SciFinder Scholar. The results of such searches and the options for refinement of the hit lists are presented using a rigid tetrahydroisoquinoline-carbazole (IQC) hybrid molecule fitted onto previously developed pharmacophores for subtype-selective alpha1-adrenergic receptor antagonists as an example. The compounds retrieved were further analysed by limiting their physical properties to 'drug-like' ranges and by enumerating the ring skeletons they contain. Selected ring skeletons were evaluated by fitting them on to the original pharmacophores. Several structurally novel rigid ring skeletons were found with this new database mining technique which are potentially useful as leads in the design of alpha1B selective adrenergic receptor antagonists.     

Corrigendum to “Exponential state estimation for recurrent neural networks with distributed delays” [Neurocomputing 71(1–3) (2007) 428–438]

In the letter [Neurocomputing 71(1–3) (2007) 428–438], there exists one minor error in computing the derivative of V₂((t)) and thus, the proof of Theorem 1 needs some improvement.     

Molecular recognition of docosahexaenoic acid by peroxisome proliferator-activated receptors and retinoid-X receptor alpha

The family of peroxisome proliferator-activated receptors (PPARs) is the molecular target of synthetic antidiabetic and hypolipidemic drugs. The side effects of these drugs are limiting their use in patients with high lipid levels. Natural compounds, like Docosahexaenoic acid (DHA) from fish oil, have beneficial effects in the treatment of metabolic diseases, and several DHA derivatives are known to activate PPAR genes. Experimental studies on affinities of DHA and its derivatives for PPARs are not available. In the present study we are therefore using computational docking, molecular dynamics simulation, and several scoring programs to predict affinities and binding modes of DHA for PPARs and retinoid-X receptor alpha, which is the DNA binding partner of PPARs. The calculations indicated that DHA binds to PPARs and the retinoid-X receptor alpha with high affinity, and that different PPARs exhibited different structural effects on the first four carbons atoms of DHA. Our data indicate that the beneficial health effects of DHA may be obtained by high affinity binding to the PPARs.     

Nanoplates of α-SnWO4 and SnW3O9 prepared via a facile hydrothermal method and their gas-sensing property

Nanoplates of α-SnWO₄ and SnW₃O₉ were selectively synthesized in large scale via a facile hydrothermal reaction method. The final products obtained were dependent on the reaction pH and the molar ratio of W⁶⁺ to Sn²⁺ in the precursors. The as-prepared nanoplates of α-SnWO₄ and SnW₃O₉ were characterized by X-ray powder diffraction (XRD), N₂-sorption BET surface area, transmission electron microscopy (TEM), high-resolution transmission electron microscopy (HRTEM) and X-ray photoelectron spectroscopy (XPS). The XPS results showed that Sn exists in divalent form (Sn²⁺) in SnW₃O₉ as well as in α-SnWO₄. The gas-sensing performances of the as-prepared α-SnWO₄ and SnW₃O₉ toward H₂S and H₂ were investigated. The hydrothermal prepared α-SnWO₄ showed higher response toward H₂ than that prepared via a solid-state reaction due to the high specific surface area. The gas-sensing property toward H₂S as well as H₂ over SnW₃O₉ was for the first time reported. As compared to α-SnWO₄, SnW₃O₉ exhibits higher response toward H₂S and its higher response can be well explained by the existence of the multivalent W (W⁶⁺/W⁴⁺) in SnW₃O₉.     

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.