Structure-Based Approach for the Study of Estrogen Receptor Binding Affinity and Subtype Selectivity

Estrogens exert important physiological effects through the modulation of two human estrogen receptor (hER) subtypes, alpa (hER alpha) and beta (hER beta). Because the levels and relative proportion of hER alpha and hER beta differ significantly in different target cells, selective hER ligands could target specific tissues or pathways regulated by one receptor subtype without affecting the other. To understand the structural and chemical basis by which small molecule modulators are able to discriminate between the two subtypes, we have applied three-dimensional target-based approaches employing a series of potent hER-ligands. Comparative molecular field analysis (CoMFA) studies were applied to a data set of 81 hER modulators, for which binding affinity values were collected for both hER alpha and hER beta. Significant statistical coefficients were obtained (hER alpha, q(2) = 0.76; hER beta, q(2) = 0.70), indicating the internal consistency of the models. The generated models were validated using external test sets, and the predicted values were in good agreement with the experimental results. Five hER crystal structures were used in GRID/PCA investigations to generate molecular interaction fields (MIF) maps. hER alpha and hER beta were separated using one factor. The resulting 3D information was integrated with the aim of revealing the most relevant structural features involved in hER subtype selectivity. The final QSAR and GRID/PCA models and the information gathered from 3D contour maps should be useful for the design or novel hER modulators with improved selectivity.

Multimilligram enantioresolution of sulfoxide proton pump inhibitors by liquid chromatography on polysaccharide-based chiral stationary phase

The enantiomers of sulfoxide proton pump inhibitors - omeprazole, lansoprazole, rabeprazole and Ro 18-5364 - were enantiomerically separated by liquid chromatography at multimilligram scale on a poly saccharide-based chiral stationary phase using normal and polar organic conditions as mobile phase. The values of the recovery and production rate were significant for each enantiomer; better results were achieved using a solid-phase injection system. However, this system was applied just for the enantionteric separation of omeprazole to demonstrate the applicability of this injection mode at milligram scale. The chiroptical characterization of the compounds was performed using a polarimeter and a circular dichroism detector. The higher enantiomeric purity obtained for the isolated enantiomers suggests that the methods here described should be considered as a simple and rapid way to obtain enantiomeric pure standards for analytical purpose. (C) 2007 Elsevier B.V. All rights reserved.

Estrogen receptor: Structural differences and potential implications on selectivity examined by the GRID/CPCA approach

Selective Estrogen Receptor Modulators ( SERMs) have been developed, but the selectivity towards the subtypes ( ER or ER is not well understood. Based on three-dimensional structural properties of ligand binding domains, a model that takes into account this aspect was developed via molecular interaction fields and consensus principal component analysis (GRID/CPCA).

Novel aryl beta-aminocarbonyl derivatives as inhibitors of Trypanosoma cruzi trypanothione reductase: binding mode revised by docking and GRIND2-based 3D-QSAR procedures

Trypanothione reductase has long been investigated as a promising target for chemotherapeutic intervention in Chagas disease, since it is an enzyme of a unique metabolic pathway that is exclusively present in the pathogen but not in the human host, which has the analog Glutathione reductase. In spite of the present data-set includes a small number of compounds, a combined use of flexible docking, pharmacophore perception, ligand binding site prediction, and Grid-Independent Descriptors GRIND2-based 3D-Quantitative Structure-Activity Relationships (QSAR) procedures allowed us to rationalize the different biological activities of a series of 11 aryl beta-aminocarbonyl derivatives, which are inhibitors of Trypanosoma cruzi trypanothione reductase (TcTR). Three QSAR models were built and validated using different alignments, which are based on docking with the TcTR crystal structure, pharmacophore, and molecular interaction fields. The high statistical significance of the models thus obtained assures the robustness of this second generation of GRIND descriptors here used, which were able to detect the most important residues of such enzyme for binding the aryl beta-aminocarbonyl derivatives, besides to rationalize distances among them. Finally, a revised binding mode has been proposed for our inhibitors and independently supported by the different methodologies here used, allowing further optimization of the lead compounds with such combined structure- and ligand-based approaches in the fight against the Chagas disease.

Identifiying human MHC supertypes using bioinformatic methods

Classification of MHC molecules into supertypes in terms of peptide-binding specificities is an important issue, with direct implications for the development of epitope-based vaccines with wide population coverage. In view of extremely high MHC polymorphism (948 class I and 633 class II HLA alleles) the experimental solution of this task is presently impossible. In this study, we describe a bioinformatics strategy for classifying MHC molecules into supertypes using information drawn solely from three-dimensional protein structure. Two chemometric techniques–hierarchical clustering and principal component analysis–were used independently on a set of 783 HLA class I molecules to identify supertypes based on structural similarities and molecular interaction fields calculated for the peptide binding site. Eight supertypes were defined: A2, A3, A24, B7, B27, B44, C1, and C4. The two techniques gave 77% consensus, i.e., 605 HLA class I alleles were classified in the same supertype by both methods. The proposed strategy allowed “supertype fingerprints” to be identified. Thus, the A2 supertype fingerprint is Tyr9/Phe9, Arg97, and His114 or Tyr116; the A3-Tyr9/Phe9/Ser9, Ile97/Met97 and Glu114 or Asp116; the A24-Ser9 and Met97; the B7-Asn63 and Leu81; the B27-Glu63 and Leu81; for B44-Ala81; the C1-Ser77; and the C4-Asn77. action fields calculated for the peptide binding site. Eight supertypes were defined: A2, A3, A24, B7, B27, B44, C1, and C4. The two techniques gave 77% consensus, i.e., 605 HLA class I alleles were classified in the same supertype by both methods. The proposed strategy allowed “supertype fingerprints” to be identified. Thus, the A2 supertype fingerprint is Tyr9/Phe9, Arg97, and His114 or Tyr116; the A3-Tyr9/Phe9/Ser9, Ile97/Met97 and Glu114 or Asp116; the A24-Ser9 and Met97; the B7-Asn63 and Leu81; the B27-Glu63 and Leu81; for B44-Ala81; the C1-Ser77; and the C4-Asn77.

Développement et applications d’un outil bio-informatique pour la détection de similarités de champs d’interaction moléculaire

Résumé : Les méthodes de détection de similarités de sites de liaison servent entre autres à la prédiction de fonction et à la prédiction de cibles croisées. Ces méthodes peuvent aider à prévenir les effets secondaires, suggérer le repositionnement de médicament existants, identifier des cibles polypharmacologiques et des remplacements bio-isostériques. La plupart des méthodes utilisent des représentations basées sur les atomes, même si les champs d’interaction moléculaire (MIFs) représentent plus directement ce qui cherche à être identifié. Nous avons développé une méthode bio-informatique, IsoMif, qui détecte les similarités de MIF entre différents sites de liaisons et qui ne nécessite aucun alignement de séquence ou de structure. Sa performance a été comparée à d’autres méthodes avec des bancs d’essais, ce qui n’a jamais été fait pour une méthode basée sur les MIFs. IsoMif performe mieux en moyenne et est plus robuste. Nous avons noté des limites intrinsèques à la méthodologie et d’autres qui proviennent de la nature. L’impact de choix de conception sur la performance est discuté. Nous avons développé une interface en ligne qui permet la détection de similarités entre une protéine et différents ensembles de MIFs précalculés ou à des MIFs choisis par l’utilisateur. Des sessions PyMOL peuvent être téléchargées afin de visualiser les similarités identifiées pour différentes interactions intermoléculaires. Nous avons appliqué IsoMif pour identifier des cibles croisées potentielles de drogues lors d’une analyse à large échelle (5,6 millions de comparaisons). Des simulations d’arrimage moléculaire ont également été effectuées pour les prédictions significatives. L’objectif est de générer des hypothèses de repositionnement et de mécanismes d’effets secondaires observés. Plusieurs exemples sont présentés à cet égard.

Molecular Modelling of Estrogen-Producing Enzymes CYP450 Aromatase and 17beta-Hydroxysteroid Dehydrogenase Type 1

Breast cancer is the most common cancer in women in the western countries. Approximately two-thirds of breast cancer tumours are hormone dependent, requiring estrogens to grow. Estrogens are formed in the human body via a multistep route starting from cholesterol. The final steps in the biosynthesis include the CYP450 aromatase enzyme, converting the male hormones androgens (preferred substrate androstenedione ASD) into estrogens(estrone E1), and the 17beta-HSD1 enzyme, converting the biologically less active E1 into the active hormone 17beta-hydroxyestradiol E2. E2 is bound to the nuclear estrogen receptors causing a cascade of biochemical reactions leading to cell proliferation in normal tissue, and to tumour growth in cancer tissue. Aromatase and 17beta-HSD1 are expressed in or near the breast tumour, locally providing the tissue with estrogens. One approach in treating hormone dependent breast tumours is to block the local estrogen production by inhibiting these two enzymes. Aromatase inhibitors are already on the market in treating breast cancer, despite the lack of an experimentally solved structure. The structure of 17beta-HSD1, on the other hand, has been solved, but no commercial drugs have emerged from the drug discovery projects reported in the literature. Computer-assisted molecular modelling is an invaluable tool in modern drug design projects. Modelling techniques can be used to generate a model of the target protein and to design novel inhibitors for them even if the target protein structure is unknown. Molecular modelling has applications in predicting the activities of theoretical inhibitors and in finding possible active inhibitors from a compound database. Inhibitor binding at atomic level can also be studied with molecular modelling. To clarify the interactions between the aromatase enzyme and its substrate and inhibitors, we generated a homology model based on a mammalian CYP450 enzyme, rabbit progesterone 21-hydroxylase CYP2C5. The model was carefully validated using molecular dynamics simulations (MDS) with and without the natural substrate ASD. Binding orientation of the inhibitors was based on the hypothesis that the inhibitors coordinate to the heme iron, and were studied using MDS. The inhibitors were dietary phytoestrogens, which have been shown to reduce the risk for breast cancer. To further validate the model, the interactions of a commercial breast cancer drug were studied with MDS and ligand–protein docking. In the case of 17beta-HSD1, a 3D QSAR model was generated on the basis of MDS of an enzyme complex with active inhibitor and ligand–protein docking, employing a compound library synthesised in our laboratory. Furthermore, four pharmacophore hypotheses with and without a bound substrate or an inhibitor were developed and used in screening a commercial database of drug-like compounds. The homology model of aromatase showed stable behaviour in MDS and was capable of explaining most of the results from mutagenesis studies. We were able to identify the active site residues contributing to the inhibitor binding, and explain differences in coordination geometry corresponding to the inhibitory activity. Interactions between the inhibitors and aromatase were in agreement with the mutagenesis studies reported for aromatase. Simulations of 17beta-HSD1 with inhibitors revealed an inhibitor binding mode with hydrogen bond interactions previously not reported, and a hydrophobic pocket capable of accommodating a bulky side chain. Pharmacophore hypothesis generation, followed by virtual screening, was able to identify several compounds that can be used in lead compound generation. The visualisation of the interaction fields from the QSAR model and the pharmacophores provided us with novel ideas for inhibitor development in our drug discovery project.

Studies in molecular dynamics: new criteria for evaluation of intramolecular force fields

The present thesis deals with some studies in molecular dynamics using spectroscopic data. Two new approximation procedures the variable method and the average bonding energy criterion have been developed for a reliable calculation of molecular force fields and applied to several molecular species belonging to the xy2 type.

A novel grass pollen allergen mimotope identified by phage display peptide library inhibits allergen-human IgE antibody interaction

The aim of this study was to investigate the molecular basis of human IgE-allergen interaction by screening a phage-displayed peptide library with an allergen-specific human IgE-mimicking monoclonal antibody (mAb). A mAb that reacted with major grass pollen allergens was successfully identified and shown to inhibit human IgE-allergen interaction. Biopanning of a phage-displayed random peptide library with this mAb yielded a 12 amino acid long mimotope. A synthetic peptide based on this 12-mer mimotope inhibited mAb and human IgE binding to grass pollen extracts. Our results indicate that such synthetic peptide mimotopes of allergens have potential as novel therapeutic agents. © 2001 Published by Elsevier Science B.V. on behalf of the Federation of European Biochemical Societies.

Molecule Modeling of Human Pentameric alpha(7) Neuronal Nicotinic Acetylcholine Receptor and Its Interaction with its Agonist and Competitive Antagonist

The nicotinic Acetylcholine Receptor (nAChR) is the major class of neurotransmitter receptors that is involved in many neurodegenerative conditions such as schizophrenia, Alzheimer's and Parkinson's diseases. The N-terminal region or Ligand Binding Domain (LBD) of nAChR is located at pre- and post-synaptic nervous system, which mediates synaptic transmission. nAChR acts as the drug target for agonist and competitive antagonist molecules that modulate signal transmission at the nerve terminals. Based on Acetylcholine Binding Protein (AChBP) from Lymnea stagnalis as the structural template, the homology modeling approach was carried out to build three dimensional model of the N-terminal region of human alpha(7)nAChR. This theoretical model is an assembly of five alpha(7) subunits with 5 fold axis symmetry, constituting a channel, with the binding picket present at the interface region of the subunits. alpha-netlrotoxin is a potent nAChR competitive antagonist that readily blocks the channel resulting in paralysis. The molecular interaction of alpha-Bungarotoxin, a long chain alpha-neurotoxin from (Bungarus multicinctus) and human alpha(7)nAChR seas studied. Agonists such as acetylcholine, nicotine, which are used in it diverse array of biological activities, such as enhancements of cognitive performances, were also docked with the theoretical model of human alpha(7)nAChR. These docked complexes were analyzed further for identifying the crucial residues involved i interaction. These results provide the details of interaction of agonists and competitive antagonists with three dimensional model of the N-terminal region of human alpha(7)nAChR and thereby point to the design of novel lead compounds.

Interface-assisted molecular spintronics

Molecular spintronics, a field that utilizes the spin state of organic molecules to develop magneto-electronic devices, has shown an enormous scientific activity for more than a decade. But, in the last couple of years, new insights in understanding the fundamental phenomena of molecular interaction on magnetic surfaces, forming a hybrid interface, are presenting a new pathway for developing the subfield of interface-assisted molecular spintronics. The recent exploration of such hybrid interfaces involving carbon based aromatic molecules shows a significant excitement and promise over the previously studied single molecular magnets. In the above new scenario, hybridization of the molecular orbitals with the spin-polarized bands of the surface creates new interface states with unique electronic and magnetic character. This study opens up a molecular-genome initiative in designing new handles to functionalize the spin dependent electronic properties of the hybrid interface to construct spin-functional tailor-made devices. Through this article, we review this subject by presenting a fundamental understanding of the interface spin-chemistry and spin-physics by taking support of advanced computational and spectroscopy tools to investigate molecular spin responses with demonstration of new interface phenomena. Spin-polarized scanning tunneling spectroscopy is favorably considered to be an important tool to investigate these hybrid interfaces with intra-molecular spatial resolution. Finally, by addressing some of the recent findings, we propose novel device schemes towards building interface tailored molecular spintronic devices for applications in sensor, memory, and quantum computing.

Probing biomolecular interaction forces using an anharmonic acoustic technique for selective detection of bacterial spores.

Receptor-based detection of pathogens often suffers from non-specific interactions, and as most detection techniques cannot distinguish between affinities of interactions, false positive responses remain a plaguing reality. Here, we report an anharmonic acoustic based method of detection that addresses the inherent weakness of current ligand dependant assays. Spores of Bacillus subtilis (Bacillus anthracis simulant) were immobilized on a thickness-shear mode AT-cut quartz crystal functionalized with anti-spore antibody and the sensor was driven by a pure sinusoidal oscillation at increasing amplitude. Biomolecular interaction forces between the coupled spores and the accelerating surface caused a nonlinear modulation of the acoustic response of the crystal. In particular, the deviation in the third harmonic of the transduced electrical response versus oscillation amplitude of the sensor (signal) was found to be significant. Signals from the specifically-bound spores were clearly distinguishable in shape from those of the physisorbed streptavidin-coated polystyrene microbeads. The analytical model presented here enables estimation of the biomolecular interaction forces from the measured response. Thus, probing biomolecular interaction forces using the described technique can quantitatively detect pathogens and distinguish specific from non-specific interactions, with potential applicability to rapid point-of-care detection. This also serves as a potential tool for rapid force-spectroscopy, affinity-based biomolecular screening and mapping of molecular interaction networks.

Probing biomolecular interaction forces using an anharmonic acoustic technique for selective detection of bacterial spores

Receptor-based detection of pathogens often suffers from non-specific interactions, and as most detection techniques cannot distinguish between affinities of interactions, false positive responses remain a plaguing reality. Here, we report an anharmonic acoustic based method of detection that addresses the inherent weakness of current ligand dependant assays. Spores of Bacillus subtilis (Bacillus anthracis simulant) were immobilized on a thickness-shear mode AT-cut quartz crystal functionalized with anti-spore antibody and the sensor was driven by a pure sinusoidal oscillation at increasing amplitude. Biomolecular interaction forces between the coupled spores and the accelerating surface caused a nonlinear modulation of the acoustic response of the crystal. In particular, the deviation in the third harmonic of the transduced electrical response versus oscillation amplitude of the sensor (signal) was found to be significant. Signals from the specifically-bound spores were clearly distinguishable in shape from those of the physisorbed streptavidin-coated polystyrene microbeads. The analytical model presented here enables estimation of the biomolecular interaction forces from the measured response. Thus, probing biomolecular interaction forces using the described technique can quantitatively detect pathogens and distinguish specific from non-specific interactions, with potential applicability to rapid point-of-care detection. This also serves as a potential tool for rapid force-spectroscopy, affinity-based biomolecular screening and mapping of molecular interaction networks. © 2011 Elsevier B.V.

Effect of end substitution on optical properties and molecular orientation of distyrylbenzene derivatives in thin film

Three distyrylbenzene (DSB) derivatives were vacuum-evaporated on a (001) surface of KBr. DSB derivative molecules formed nuclei by interaction between the electron donative methoxyl group and Br- ion of the substrate crystal and oriented their longitudinal axis obliquely to the substrate surface. The peak shift between the emission peaks of solution and film decreased depending on the number of substituent. This phenomenon was originated to reduction of molecular interaction between neighboring molecules by steric hindrance of end substituents. (C) 2000 Elsevier Science S.A. All rights reserved.