SAM levels, gene expression of SAM synthetase, methionine synthase and ACC oxidase, and ethylene emission from N. suaveolens flowers

S′adenosyl-l-methionine (SAM) is a ubiquitous methyl donor and a precursor in the biosynthesis of ethylene, polyamines, biotin, and nicotianamine in plants. Only limited information is available regarding its synthesis (SAM cycle) and its concentrations in plant tissues. The SAM concentrations in flowers of Nicotiana suaveolens were determined during day/night cycles and found to fluctuate rhythmically between 10 and 50 nmol g−1 fresh weight. Troughs of SAM levels were measured in the evening and night, which corresponds to the time when the major floral scent compound, methyl benzoate, is synthesized by a SAM dependent methyltransferase (NsBSMT) and when this enzyme possesses its highest activity. The SAM synthetase (NsSAMS1) and methionine synthase (NsMS1) are enzymes, among others, which are involved in the synthesis and regeneration of SAM. Respective genes were isolated from a N. suaveolens petal cDNA library. Transcript accumulation patterns of both SAM regenerating enzymes matched perfectly those of the bifunctional NsBSMT; maximum mRNA accumulations of NsMS1 and NsSAMS1 were attained in the evening. Ethylene, which is synthesized from SAM, reached only low levels of 1–2 ppbv in N. suaveolens flowers. It is emitted in a burst at the end of the life span of the flowers, which correlates with the increased expression of the 1-aminocyclopropane-1-carboxylate oxidase (NsACO)

Development and validation of an improved algorithm for overlaying flexible molecules

A program for overlaying multiple flexible molecules has been developed. Candidate overlays are generated by a novel fingerprint algorithm, scored on three objective functions (union volume, hydrogen-bond match, and hydrophobic match), and ranked by constrained Pareto ranking. A diverse subset of the best ranked solutions is chosen using an overlay-dissimilarity metric. If necessary, the solutions can be optimised. A multi-objective genetic algorithm can be used to find additional overlays with a given mapping of chemical features but different ligand conformations. The fingerprint algorithm may also be used to produce constrained overlays, in which user-specified chemical groups are forced to be superimposed. The program has been tested on several sets of ligands, for each of which the true overlay is known from protein–ligand crystal structures. Both objective and subjective success criteria indicate that good results are obtained on the majority of these sets

Application of the PM6 semi-empirical method to modeling proteins enhances docking accuracy of AutoDock

<p>Abstract</p> <p>Background</p> <p>Molecular docking methods are commonly used for predicting binding modes and energies of ligands to proteins. For accurate complex geometry and binding energy estimation, an appropriate method for calculating partial charges is essential. AutoDockTools software, the interface for preparing input files for one of the most widely used docking programs AutoDock 4, utilizes the Gasteiger partial charge calculation method for both protein and ligand charge calculation. However, it has already been shown that more accurate partial charge calculation - and as a consequence, more accurate docking- can be achieved by using quantum chemical methods. For docking calculations quantum chemical partial charge calculation as a routine was only used for ligands so far. The newly developed Mozyme function of MOPAC2009 allows fast partial charge calculation of proteins by quantum mechanical semi-empirical methods. Thus, in the current study, the effect of semi-empirical quantum-mechanical partial charge calculation on docking accuracy could be investigated.</p> <p>Results</p> <p>The docking accuracy of AutoDock 4 using the original AutoDock scoring function was investigated on a set of 53 protein ligand complexes using Gasteiger and PM6 partial charge calculation methods. This has enabled us to compare the effect of the partial charge calculation method on docking accuracy utilizing AutoDock 4 software. Our results showed that the docking accuracy in regard to complex geometry (docking result defined as accurate when the RMSD of the first rank docking result complex is within 2 Å of the experimentally determined X-ray structure) significantly increased when partial charges of the ligands and proteins were calculated with the semi-empirical PM6 method.</p> <p>Out of the 53 complexes analyzed in the course of our study, the geometry of 42 complexes were accurately calculated using PM6 partial charges, while the use of Gasteiger charges resulted in only 28 accurate geometries. The binding affinity estimation was not influenced by the partial charge calculation method - for more accurate binding affinity prediction development of a new scoring function for AutoDock is needed.</p> <p>Conclusion</p> <p>Our results demonstrate that the accuracy of determination of complex geometry using AutoDock 4 for docking calculation greatly increases with the use of quantum chemical partial charge calculation on both the ligands and proteins.</p

How to do an evaluation: pitfalls and traps

The recent literature is replete with papers evaluating computational tools (often those operating on 3D structures) for their performance in a certain set of tasks. Most commonly these papers compare a number of docking tools for their performance in cognate re-docking (pose prediction) and/or virtual screening. Related papers have been published on ligand-based tools: pose prediction by conformer generators and virtual screening using a variety of ligand-based approaches. The reliability of these comparisons is critically affected by a number of factors usually ignored by the authors, including bias in the datasets used in virtual screening, the metrics used to assess performance in virtual screening and pose prediction and errors in crystal structures used

How to do an evaluation: pitfalls and traps

The recent literature is replete with papers evaluating computational tools (often those operating on 3D structures) for their performance in a certain set of tasks. Most commonly these papers compare a number of docking tools for their performance in cognate re-docking (pose prediction) and/or virtual screening. Related papers have been published on ligand-based tools: pose prediction by conformer generators and virtual screening using a variety of ligand-based approaches. The reliability of these comparisons is critically affected by a number of factors usually ignored by the authors, including bias in the datasets used in virtual screening, the metrics used to assess performance in virtual screening and pose prediction and errors in crystal structures used

Insights into the Complex Formed by Matrix Metalloproteinase-2 and Alloxan Inhibitors: Molecular Dynamics Simulations and Free Energy Calculations

Matrix metalloproteinases (MMP) are well-known biological targets implicated in tumour progression, homeostatic regulation, innate immunity, impaired delivery of pro-apoptotic ligands, and the release and cleavage of cell-surface receptors. Hence, the development of potent and selective inhibitors targeting these enzymes continues to be eagerly sought. In this paper, a number of alloxan-based compounds, initially conceived to bias other therapeutically relevant enzymes, were rationally modified and successfully repurposed to inhibit MMP-2 (also named gelatinase A) in the nanomolar range. Importantly, the alloxan core makes its debut as zinc binding group since it ensures a stable tetrahedral coordination of the catalytic zinc ion in concert with the three histidines of the HExxHxxGxxH metzincin signature motif, further stabilized by a hydrogen bond with the glutamate residue belonging to the same motif. The molecular decoration of the alloxan core with a biphenyl privileged structure allowed to sample the deep S1′ specificity pocket of MMP-2 and to relate the high affinity towards this enzyme with the chance of forming a hydrogen bond network with the backbone of Leu116 and Asn147 and the side chains of Tyr144, Thr145 and Arg149 at the bottom of the pocket. The effect of even slight structural changes in determining the interaction at the S1′ subsite of MMP-2 as well as the nature and strength of the binding is elucidated via molecular dynamics simulations and free energy calculations. Among the herein presented compounds, the highest affinity (pIC50 = 7.06) is found for BAM, a compound exhibiting also selectivity (>20) towards MMP-2, as compared to MMP-9, the other member of the gelatinases

Floral and insect-induced volatile formation in Arabidopsis lyrata ssp. petraea, a perennial, outcrossing relative of A. thaliana

Volatile organic compounds have been reported to serve some important roles in plant communication with other organisms, but little is known about the biological functions of most of these substances. To gain insight into this problem, we have compared differences in floral and vegetative volatiles between two closely related plant species with different life histories. The self-pollinating annual, Arabidopsis thaliana, and its relative, the outcrossing perennial, Arabidopsis lyrata, have markedly divergent life cycles and breeding systems. We show that these differences are in part reflected in the formation of distinct volatile mixtures in flowers and foliage. Volatiles emitted from flowers of a German A. lyrata ssp. petraea population are dominated by benzenoid compounds in contrast to the previously described sesquiterpene-dominated emissions of A. thaliana flowers. Flowers of A. lyrata ssp. petraea release benzenoid volatiles in a diurnal rhythm with highest emission rates at midday coinciding with observed visitations of pollinating insects. Insect feeding on leaves of A. lyrata ssp. petraea causes a variable release of the volatiles methyl salicylate, C11- and C16-homoterpenes, nerolidol, plus the sesquiterpene (E)-β-caryophyllene, which in A. thaliana is emitted exclusively from flowers. An insect-induced gene (AlCarS) with high sequence similarity to the florally expressed (E)-β-caryophyllene synthase (AtTPS21) from A. thaliana was identified from individuals of a German A. lyrata ssp. petraea population. Recombinant AlCarS converts the sesquiterpene precursor, farnesyl diphosphate, into (E)-β-caryophyllene with α-humulene and α-copaene as minor products indicating its close functional relationship to the A. thaliana AtTPS21. Differential regulation of these genes in flowers and foliage is consistent with the different functions of volatiles in the two Arabidopsis species

Bak Conformational Changes Induced by Ligand Binding: Insight into BH3 Domain Binding and Bak Homo-Oligomerization

Recently we reported that the BH3-only proteins Bim and Noxa bind tightly but transiently to the BH3-binding groove of Bak to initiate Bak homo-oligomerization. However, it is unclear how such tight binding can induce Bak homo-oligomerization. Here we report the ligand-induced Bak conformational changes observed in 3D models of Noxa·Bak and Bim·Bak refined by molecular dynamics simulations. In particular, upon binding to the BH3-binding groove, Bim and Noxa induce a large conformational change of the loop between helices 1 and 2 and in turn partially expose a remote groove between helices 1 and 6 in Bak. These observations, coupled with the reported experimental data, suggest formation of a pore-forming Bak octamer, in which the BH3-binding groove is at the interface on one side of each monomer and the groove between helices 1 and 6 is at the interface on the opposite side, initiated by ligand binding to the BH3-binding groove

The Complex Genetic Architecture of the Metabolome

Discovering links between the genotype of an organism and its metabolite levels can increase our understanding of metabolism, its controls, and the indirect effects of metabolism on other quantitative traits. Recent technological advances in both DNA sequencing and metabolite profiling allow the use of broad-spectrum, untargeted metabolite profiling to generate phenotypic data for genome-wide association studies that investigate quantitative genetic control of metabolism within species. We conducted a genome-wide association study of natural variation in plant metabolism using the results of untargeted metabolite analyses performed on a collection of wild Arabidopsis thaliana accessions. Testing 327 metabolites against >200,000 single nucleotide polymorphisms identified numerous genotype–metabolite associations distributed non-randomly within the genome. These clusters of genotype–metabolite associations (hotspots) included regions of the A. thaliana genome previously identified as subject to recent strong positive selection (selective sweeps) and regions showing trans-linkage to these putative sweeps, suggesting that these selective forces have impacted genome-wide control of A. thaliana metabolism. Comparing the metabolic variation detected within this collection of wild accessions to a laboratory-derived population of recombinant inbred lines (derived from two of the accessions used in this study) showed that the higher level of genetic variation present within the wild accessions did not correspond to higher variance in metabolic phenotypes, suggesting that evolutionary constraints limit metabolic variation. While a major goal of genome-wide association studies is to develop catalogues of intraspecific variation, the results of multiple independent experiments performed for this study showed that the genotype–metabolite associations identified are sensitive to environmental fluctuations. Thus, studies of intraspecific variation conducted via genome-wide association will require analyses of genotype by environment interaction. Interestingly, the network structure of metabolite linkages was also sensitive to environmental differences, suggesting that key aspects of network architecture are malleable