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Ligand Properties (ligand + property)
Selected AbstractsSynthesis and evaluation of tritium labelled 10-methylgalanthamine iodide: a novel compound to examine the mechanism of interaction of galanthamine derivatives with the nicotinic acetylcholine receptorsJOURNAL OF LABELLED COMPOUNDS AND RADIOPHARMACEUTICALS, Issue 12 2003Andreas Schildan Abstract A new promising galanthamine derivative, 10-[3H]methylgalanthamine iodide, was synthesized for binding studies to nicotinic acetylcholine receptors expressed in Torpedo electric ray electroplaques. Galanthamine was reacted with [3H]methyl iodide to yield 10-[3H]methylgalanthamine iodide with a radiochemical yield of >70% and a specific activity of 32 Ci/mmol after purification via solid phase extraction. To test the ligand properties of the radioligand, calcium imaging and electrophysiology of the non-radioactive analogue were performed to obtain an EC50 of 270 nM, a Hill coefficient of 1.9 and the induced cell current. Copyright © 2003 John Wiley & Sons, Ltd. [source] Towards Proteome,Wide Interaction Models Using the Proteochemometrics ApproachMOLECULAR INFORMATICS, Issue 6-7 2010Helena Strömbergsson Abstract A proteochemometrics model was induced from all interaction data in the BindingDB database, comprizing in all 7078 protein-ligand complexes with representatives from all major drug target categories. Proteins were represented by alignment-independent sequence descriptors holding information on properties such as hydrophobicity, charge, and secondary structure. Ligands were represented by commonly used QSAR descriptors. The inhibition constant (pKi) values of protein-ligand complexes were discretized into "high" and "low" interaction activity. Different machine-learning techniques were used to induce models relating protein and ligand properties to the interaction activity. The best was decision trees, which gave an accuracy of 80,% and an area under the ROC curve of 0.81. The tree pointed to the protein and ligand properties, which are relevant for the interaction. As the approach does neither require alignments nor knowledge of protein 3D structures virtually all available protein-ligand interaction data could be utilized, thus opening a way to completely general interaction models that may span entire proteomes. [source] Defining the glycophenotype of squamous epithelia using plant and mammalian lectins.APMIS, Issue 12 20023-linked N-acetylneuraminic acid in squamous epithelia, Differentiation-dependent expression of, carcinomas, its differential effect on binding of the endogenous lectins galectins- A thorough characterization of the properties of squamous epithelial cells is necessary in order to improve our understanding of the functional aspects of normal development and malignant aberrations. Up to now, studies have focused almost exclusively on monitoring distinct protein markers. With our growing awareness of the coding function of glycan chains of cellular glycoconjugates and their interaction with receptors (lectins) in situ, defining the glycophenotype of these cells has become an important issue. Whereas the commonly applied plant lectins are tools used to map the presence and localization of biochemically defined saccharide epitopes, the introduction of endogenous (mammalian) lectins to this analysis enables us to take the step from monitoring the presence of glycan to understanding the functional implications by revealing ligand properties of the detected epitope for tissue lectin. Thus, in this study we investigated a distinct aspect of glycosylation using plant and mammalian lectins, i.e. the linkage type of sialylation. We first mapped the expression profile of the type of sialylation (,2,3- or ,2,6-linked) by plant lectins. Based on the hypothesis that this factor regulates accessibility of ligands for endogenous lectins we introduced two labeled galectins to this study. Galectin-3 (but not galectin-1) binding was related to cell differentiation in normal adult and developing epithelia, cultured epidermal cells, and carcinomas derived from these epithelia. The presented data suggest that ,2,6-linked N-acetyl- D -neuraminic acid moieties could serve to mask galectin-3-reactive glycoepitopes. As a consequence, monitoring of the linkage type of sialic acid in glycans by plant lectins therefore has implications for the extent of glycan reactivity with endogenous lectins, pointing to a potential function of changes in sialylation type beyond these cell and lectin systems. [source] Transition-Metal Complexes [(PMe3)2Cl2M(E)] and [(PMe3)2(CO)2M(E)] with Naked Group,14 Atoms (E=C,Sn) as Ligands; Part 2: Complexation with W(CO)5CHEMISTRY - A EUROPEAN JOURNAL, Issue 35 2009Pattiyil Parameswaran Dr. Abstract Density functional calculations at the BP86/TZ2P level were carried out to understand the ligand properties of the 16-valence-electron(VE) Group,14 complexes [(PMe3)2Cl2M(E)] (1ME) and the 18-VE Group,14 complexes [(PMe3)2(CO)2M(E)] (2ME; M=Fe, Ru, Os; E=C, Si, Ge, Sn) in complexation with W(CO)5. Calculations were also carried out for the complexes (CO)5W,EO. The complexes [(PMe3)2Cl2M(E)] and [(PMe3)2(CO)2M(E)] bind strongly to W(CO)5 yielding the adducts 1ME,W(CO)5 and 2ME,W(CO)5, which have C2v equilibrium geometries. The bond strengths of the heavier Group,14 ligands 1ME (E=Si,Sn) are uniformly larger, by about 6,7,kcal,mol,1, than those of the respective EO ligand in (CO)5W-EO, while the carbon complexes 1MC,W(CO)5 have comparable bond dissociation energies (BDE) to CO. The heavier 18-VE ligands 2ME (E=Si,Sn) are about 23,25,kcal,mol,1 more strongly bonded than the associated EO ligand, while the BDE of 2MC is about 17,21,kcal,mol,1 larger than that of CO. Analysis of the bonding with an energy-decomposition scheme reveals that 1ME is isolobal with EO and that the nature of the bonding in 1ME,W(CO)5 is very similar to that in (CO)5W,EO. The ligands 1ME are slightly weaker , acceptors than EO while the ,-acceptor strength of 2ME is even lower. [source] Modeling and Selection of Flexible Proteins for Structure-Based Drug Design: Backbone and Side Chain Movements in p38 MAPKCHEMMEDCHEM, Issue 2 2008Jyothi Subramanian Abstract Receptor rearrangement upon ligand binding (induced fit) is a major stumbling block in docking and virtual screening. Even though numerous studies have stressed the importance of including protein flexibility in ligand docking, currently available methods provide only a partial solution to the problem. Most of these methods, being computer intensive, are often impractical to use in actual drug discovery settings. We had earlier shown that ligand-induced receptor side-chain conformational changes could be modeled statistically using data on known receptor,ligand complexes. In this paper, we show that a similar approach can be used to model more complex changes like backbone flips and loop movements. We have used p38 MAPK as a test case and have shown that a few simple structural features of ligands are sufficient to predict the induced variation in receptor conformations. Rigorous validation, both by internal resampling methods and on an external test set, corroborates this finding and demonstrates the robustness of the models. We have also compared our results with those from an earlier molecular dynamics simulation study on DFG loop conformations of p38 MAPK, and found that the results matched in the two cases. Our statistical approach enables one to predict the final ligand-induced conformation of the active site of a protein, based on a few ligand properties, prior to docking the ligand. We can do this without having to trace the step-by-step process by which this state is arrived at (as in molecular dynamics simulations), thereby drastically reducing computational effort. [source] | ||||||||||