Effect of an ancillary ligand on single helix-double helix interconversion in copper complexes. Copper(I)-water bond

Reaction of Cu(ClO(4))(2)center dot 6H(2)O with the 1:2 condensate of benzildihydrazone and 2-acetylpyridine, in methanol in equimolar ratio yields a green compound which upon recrystallisation from 1:1 CH(2)Cl(2)-C(6)H(6) mixture affords [CuL(H(2)O)](ClO(4))(2)center dot 1/2C(6)H(6). The complex crystallises in the space group P-1 with a = 8.028(11) angstrom, b = 12.316(17) angstrom, c = 18.14(3) angstrom, alpha = 97.191(10)degrees, beta = 94.657(10)degrees and gamma = 108.039(10)degrees. It is single helical with the metal having a distorted trigonal bipyramidal N(4)O coordination sphere. The acid dissociation constant of the Cu(I) complex in CH(3)CN is 3.34 +/- 0.19. The X band EPR spectrum of the compound is rhombic with g(1) = 2.43, g(2) = 2.10 g(3) = 2.02 and A(1) = 79.3 x 10(-4) cm(-1). The Cu(II/I) potential of the complex in CH(2)Cl(2) at a glassy carbon electrode is 0.43 V vs SCE. It is argued that the copper-water bond persists in the corresponding copper(I) species. Its implications on the single helix-double helix interconversion in copper helicates are discussed. DFT calculations at the B3LYP/6-311G** level shows that the binding energy of water in the single helicol live-coordinate copper(I) species [CuL(H(2)O)](+) is similar to 40 kJ mol(-1).

Structural and magnetic studies of Schiff base complexes of nickel(ii) nitrite: change in crystalline state, ligand rearrangement and a very rare μ-nitrito-1κO:2κN:3κO′ bridging mode

Four new nickel(II) complexes, [Ni2L2(NO2)2]·CH2Cl2·C2H5OH, 2H2O (1), [Ni2L2(DMF)2(m-NO2)]ClO4·DMF (2a), [Ni2L2(DMF)2(m-NO2)]ClO4 (2b) and [Ni3L¢2(m3-NO2)2(CH2Cl2)]n·1.5H2O (3) where HL = 2-[(3-amino-propylimino)-methyl]-phenol, H2L¢ = 2-({3-[(2-hydroxy-benzylidene)-amino]-propylimino}-methyl)-phenol and DMF = N,N-dimethylformamide, have been synthesized starting with the precursor complex [NiL2]·2H2O, nickel(II) perchlorate and sodium nitrite and characterized structurally and magnetically. The structural analyses reveal that in all the complexes, NiII ions possess a distorted octahedral geometry. Complex 1 is a dinuclear di-m2-phenoxo bridged species in which nitrite ion acts as chelating co-ligand. Complexes 2a and 2b also consist of dinuclear entities, but in these two compounds a cis-(m-nitrito-1kO:2kN) bridge is present in addition to the di-m2-phenoxo bridge. The molecular structures of 2a and 2b are equivalent; they differ only in that 2a contains an additional solvated DMF molecule. Complex 3 is formed by ligand rearrangement and is a one-dimensional polymer in which double phenoxo as well as m-nitrito-1kO:2kN bridged trinuclear units are linked through a very rare m3-nitrito-1kO:2kN:3kO¢ bridge. Analysis of variable-temperature magnetic susceptibility data indicates that there is a global weak antiferromagnetic interaction between the nickel(II) ions in four complexes, with exchange parameters J of -5.26, -11.45, -10.66 and -5.99 cm-1 for 1, 2a, 2b and 3, respectively

The FunFOLD2 server for the prediction of protein-ligand interactions

The FunFOLD2 server is a new independent server that integrates our novel protein–ligand binding site and quality assessment protocols for the prediction of protein function (FN) from sequence via structure. Our guiding principles were, first, to provide a simple unified resource to make our function prediction software easily accessible to all via a simple web interface and, second, to produce integrated output for predictions that can be easily interpreted. The server provides a clean web interface so that results can be viewed on a single page and interpreted by non-experts at a glance. The output for the prediction is an image of the top predicted tertiary structure annotated to indicate putative ligand-binding site residues. The results page also includes a list of the most likely binding site residues and the types of predicted ligands and their frequencies in similar structures. The protein–ligand interactions can also be interactively visualized in 3D using the Jmol plug-in. The raw machine readable data are provided for developers, which comply with the Critical Assessment of Techniques for Protein Structure Prediction data standards for FN predictions. The FunFOLD2 webserver is freely available to all at the following web site: http://www.reading.ac.uk/bioinf/FunFOLD/FunFOLD_form_2_0.html.

RuII(α-diimine) or RuIII(α-diimine·–)? Structural, spectroscopic, and theoretical evidence for the stabilization of a prominent metal-to-Ligand charge- transfer excited-state configuration in the ground state

The new compounds [Ru(R-DAB)(acac)2] (R-DAB = 1,4-diorganyl- 1,4-diazabuta-1,3-diene; R = tert-butyl, 4-methoxyphenyl, 2,6-dimethylphenyl; acac– = 2,4-pentanedionate) exhibit intrachelate ring bond lengths 1.297ligand to produce UV/Vis/NIR and electron paramagnetic resonance (EPR) spectroelectrochemically detectable RuIII species, whereas the reduction proceeds less reversibly and yields predominantly (R-DAB)-ligand-based spin for the 4-methoxyphenyl derivative, measured at low temperature. The results are discussed with respect to metal-to-ligand chargetransfer (MLCT) excited states of conventional (α-diimine)- ruthenium(II) complexes and in view of other (α-diimine)- metal complexes with ambiguous oxidation-state assignments.

Electrocatalytic reduction of carbon dioxide with a manganese(I)tricarbonyl complex containing a nonaromatic α‑diimine ligand

The 2e reduced anion [Mn(CO)3(iPr-DAB)]− (DAB = 1,4- diazabuta-1,3-diene, iPr = isopropyl) was shown to convert in the presence of CO2 and a small amount of water to the unstable complex [Mn(CO)3(iPr-DAB)(η1-OCO2H)] (OCO2H− = unidentate bicarbonate) that was further reductively transformed to give a stable catalytic intermediate denoted as X2, showing νs(OCO) 1672 and 1646 (sh) cm−1. The subsequent cathodic shift by ca. 650 mV in comparison to the single 2e cathodic wave of the parent [Mn(CO)3(iPr-DAB)Br] triggers the reduction of intermediate X2 and catalytic activity converting CO2 to CO. Infrared spectroelectrochemistry has revealed that the high excess of CO generated at the cathode leads to the conversion of [Mn(CO)3(iPr-DAB)]− to inactive [Mn(CO)5]−. In contrast, the five-coordinate anion [Mn(CO)3(pTol-DAB)]−(pTol = 4-tolyl) is completely inert toward both CO2 and H2O (solvolysis). This detailed spectroelectrochemical study is a further contribution to the development of sustainable electro- and photoelectrocatalysts of CO2 reduction based on abundant first-row transition metals, in particular manganese.

Quantitative single-molecule localization microscopy combined with rule-based modeling reveals ligand-induced TNF-R1 reorganization toward higher-order oligomers

We report on the assembly of tumor necrosis factor receptor 1 (TNF-R1) prior to ligand activation and its ligand-induced reorganization at the cell membrane. We apply single-molecule localization microscopy to obtain quantitative information on receptor cluster sizes and copy numbers. Our data suggest a dimeric pre-assembly of TNF-R1, as well as receptor reorganization toward higher oligomeric states with stable populations comprising three to six TNF-R1. Our experimental results directly serve as input parameters for computational modeling of the ligand-receptor interaction. Simulations corroborate the experimental finding of higher-order oligomeric states. This work is a first demonstration how quantitative, super-resolution and advanced microscopy can be used for systems biology approaches at the single-molecule and single-cell level.

GRID and docking analyses reveal a molecular basis for flavonoid inhibition of src-family kinase activity

Flavonoids reduce cardiovascular disease risk through anti-inflammatory, anti-coagulant and anti-platelet actions. One key flavonoid inhibitory mechanism is blocking kinase activity that drives these processes. Flavonoids attenuate activities of kinases including phosphoinositide-3-kinase (PI3K), Fyn, Lyn, Src, Syk, PKC, PIM1/2, ERK, JNK, and PKA. X-ray crystallographic analyses of kinase-flavonoid complexes show that flavonoid ring systems and their hydroxyl substitutions are important structural features for their binding to kinases. A clearer understanding of structural interactions of flavonoids with kinases is necessary to allow construction of more potent and selective counterparts. We examined flavonoid (quercetin, apigenin and catechin) interactions with Src-family kinases (Lyn, Fyn and Hck) applying the Sybyl docking algorithm and GRID. A homology model (Lyn) was used in our analyses to demonstrate that high quality predicted kinase structures are suitable for flavonoid computational studies. Our docking results revealed potential hydrogen bond contacts between flavonoid hydroxyls and kinase catalytic site residues. Identification of plausible contacts indicated that quercetin formed the most energetically stable interactions, apigenin lacked hydroxyl groups necessary for important contacts, and the non-planar structure of catechin could not support predicted hydrogen bonding patterns. GRID analysis using a hydroxyl functional group supported docking results. Based on these findings, we predicted that quercetin would inhibit activities of Src-family kinases with greater potency than apigenin and catechin. We validated this prediction using in vitro kinase assays. We conclude that our study can be used as a basis to construct virtual flavonoid interaction libraries to guide drug discovery using these compounds as molecular templates.

CLEC-2 is not required for platelet aggregation at arteriolar shear

The C-type lectin receptor CLEC-2 is expressed primarily on the surface of platelets, where it is present as a dimer, and is found at low level on a subpopulation of other hematopoietic cells, including mouse neutrophils [1–4] Clustering of CLEC-2 by the snake venom toxin rhodocytin, specific antibodies or its endogenous ligand, podoplanin, elicits powerful activation of platelets through a pathway that is similar to that used by the collagen receptor glycoprotein VI (GPVI) [4–6]. The cytosolic tail of CLEC-2 contains a conserved YxxL sequence preceded by three upstream acidic amino acid residues, which together form a novel motif known as a hemITAM. Ligand engagement induces tyrosine phosphorylation of the hemITAM sequence providing docking sites for the tandem-SH2 domains of the tyrosine kinase Syk across a CLEC-2 receptor dimer [3]. Tyrosine phosphorylation of Syk by Src family kinases and through autophosphorylation leads to stimulation of a downstream signaling cascade that culminates in activation of phospholipase C γ2 (PLCγ2) [4,6]. Recently, CLEC-2 has been proposed to play a major role in supporting activation of platelets at arteriolar rates of flow [1]. Injection of a CLEC-2 antibody into mice causes a sustained depletion of the C-type lectin receptor from the platelet surface [1]. The CLEC-2-depleted platelets were unresponsive to rhodocytin but underwent normal aggregation and secretion responses after stimulation of other platelet receptors, including GPVI [1]. In contrast, there was a marked decrease in aggregate formation relative to controls when CLEC-2-depleted blood was flowed at arteriolar rates of shear over collagen (1000 s−1 and 1700 s−1) [1]. Furthermore, antibody treatment significantly increased tail bleeding times and mice were unable to occlude their vessels after ferric chloride injury [1]. These data provide evidence for a critical role for CLEC-2 in supporting platelet aggregation at arteriolar rates of flow. The underlying mechanism is unclear as platelets do not express podoplanin, the only known endogenous ligand of CLEC-2. In the present study, we have investigated the role of CLEC-2 in platelet aggregation and thrombus formation using platelets from a novel mutant mouse model that lacks functional CLEC-2.

Zero-Dimensional Units of Ligand-Bridged Gallium-Sulfide Supertetrahedra

The synthesis and characterization of the first anions containing two gallium-sulfide supertetrahedra linked via an organic moiety are described.

Understanding the link between single cell and population scale responses of Escherichia coli in differing ligand gradients

We formulate an agent-based population model of Escherichia coli cells which incorporates a description of the chemotaxis signalling cascade at the single cell scale. The model is used to gain insight into the link between the signalling cascade dynamics and the overall population response to differing chemoattractant gradients. Firstly, we consider how the observed variation in total (phosphorylated and unphosphorylated) signalling protein concentration affects the ability of cells to accumulate in differing chemoattractant gradients. Results reveal that a variation in total cell protein concentration between cells may be a mechanism for the survival of cell colonies across a wide range of differing environments. We then study the response of cells in the presence of two different chemoattractants.In doing so we demonstrate that the population scale response depends not on the absolute concentration of each chemoattractant but on the sensitivity of the chemoreceptors to their respective concentrations. Our results show the clear link between single cell features and the overall environment in which cells reside.

Synthesis and evaluation of a novel hydrophilic 6,6′-bis(1,2,4-triazin-3-yl)-2,2′-bipyridine ligand for separating actinide(III) from lanthanide(III)

We report the synthesis and evaluation of a novel hydrophilic 6,6′-bis(1,2,4-triazin-3-yl)-2,2′-bipyridine (BTBP) ligand containing carboxylate groups as a selective aqueous complexing agent for the minor actinides over lanthanides. The novel ligand is able to complex and separate Am(III) from Eu(III) in alkaline solutions selectively.

Retinoid-Related Receptor (ROR) alpha mRNA Expression Is Altered in the Brain of Male Mice Lacking All Ligand-Binding Thyroid Hormone Receptor (TR) Isoforms

In the vertebrate brain, the thalamus serves as a relay and integration station for diverse neuronal information en route from the periphery to the cortex. Deficiency of TH during development results in severe cerebral abnormalities similar to those seen in the mouse when the retinoic acid receptor (ROR)α gene is disrupted. To investigate the effect of the thyroid hormone recep-tors (TRs) on RORalpha gene expression, we used intact male mice, in which the genes encoding the α and beta TRs have been deleted. In situ hybridization for RORalpha mRNA revealed that this gene is expressed in specific areas of the brain including the thalamus, pons, cerebellum, cortex, and hippocampus. Our quantitative data showed differences in RORalpha mRNA expression in different subthalamic nuclei between wild-type and knock-out mice. For example, the centromedial nucleus of the thalamus, which plays a role in mediating nociceptive and visceral information from the brainstem to the basal ganglia and cortical regions, has less expression of RORalpha mRNA in the knockout mice (-37%) compared to the wild-type controls. Also, in the dorsal geniculate (+72%) and lateral posterior nuclei (+58%) we found more RORalpha mRNA in dKO as compared to dWT animals. Such differences in RORalpha mRNA expression may play a role in the behavioral alterations resulting from congenital hypothyroidism.

In silico identification and characterization of protein-ligand binding sites

Protein–ligand binding site prediction methods aim to predict, from amino acid sequence, protein–ligand interactions, putative ligands, and ligand binding site residues using either sequence information, structural information, or a combination of both. In silico characterization of protein–ligand interactions has become extremely important to help determine a protein’s functionality, as in vivo-based functional elucidation is unable to keep pace with the current growth of sequence databases. Additionally, in vitro biochemical functional elucidation is time-consuming, costly, and may not be feasible for large-scale analysis, such as drug discovery. Thus, in silico prediction of protein–ligand interactions must be utilized to aid in functional elucidation. Here, we briefly discuss protein function prediction, prediction of protein–ligand interactions, the Critical Assessment of Techniques for Protein Structure Prediction (CASP) and the Continuous Automated EvaluatiOn (CAMEO) competitions, along with their role in shaping the field. We also discuss, in detail, our cutting-edge web-server method, FunFOLD for the structurally informed prediction of protein–ligand interactions. Furthermore, we provide a step-by-step guide on using the FunFOLD web server and FunFOLD3 downloadable application, along with some real world examples, where the FunFOLD methods have been used to aid functional elucidation.

Melatonin Protects CD4(+) T Cells from Activation-Induced Cell Death by Blocking NFAT-Mediated CD95 Ligand Upregulation

Over the past 20 y, the hormone melatonin was found to be produced in extrapineal sites, including cells of the immune system. Despite the increasing data regarding the biological effects of melatonin on the regulation of the immune system, the effect of this molecule on T cell survival remains largely unknown. Activation-induced cell death plays a critical role in the maintenance of the homeostasis of the immune system by eliminating self-reactive or chronically stimulated T cells. Because activated T cells not only synthesize melatonin but also respond to it, we investigated whether melatonin could modulate activation-induced cell death. We found that melatonin protects human and murine CD4(+) T cells from apoptosis by inhibiting CD95 ligand mRNA and protein upregulation in response to TCR/CD3 stimulation. This inhibition is a result of the interference with calmodulin/calcineurin activation of NFAT that prevents the translocation of NFAT to the nucleus. Accordingly, melatonin has no effect on T cells transfected with a constitutively active form of NFAT capable of migrating to the nucleus and transactivating target genes in the absence of calcineurin activity. Our results revealed a novel biochemical pathway that regulates the expression of CD95 ligand and potentially other downstream targets of NFAT activation. The Journal of Immunology, 2010, 184: 3487-3494.