Descriptors for terpene esters from chromatographic and partition measurements: Estimation of human odor detection thresholds

We have used gas chromatographic retention data together with other data to obtain Abraham descriptors for 30 terpene esters. These include the air-water partition coefficient, as log Kw, for which no experimental values are available for any terpene ester. The other descriptors are the ester dipolarity, S, the hydrogen bond basicity, B, (the ester hydrogen bond acidity is zero for the esters studied), and L the logarithm of the air-hexadecane partition coefficient. Both S and B are larger than those for simple aliphatic esters, as expected from the terpene ester structures that include ring systems and ethylenic double bonds. These descriptors can then be used to obtain a large number of physicochemical and environmental properties of terpene esters. We have analyzed experimental results on human odor detection thresholds and have constructed another equation for the calculation of these thresholds, to go with a previous equation that we have reported. Then the descriptors for terpene esters can be used to estimate the important odor detection thresholds

De novo formation of an aggregation pheromone precursor by an isoprenyl diphosphate synthase-related terpene synthase in the harlequin bug.

Insects use a diverse array of specialized terpene metabolites as pheromones in intraspecific interactions. In contrast to plants and microbes, which employ enzymes called terpene synthases (TPSs) to synthesize terpene metabolites, limited information from few species is available about the enzymatic mechanisms underlying terpene pheromone biosynthesis in insects. Several stink bugs (Hemiptera: Pentatomidae), among them severe agricultural pests, release 15-carbon sesquiterpenes with a bisabolene skeleton as sex or aggregation pheromones. The harlequin bug, Murgantia histrionica, a specialist pest of crucifers, uses two stereoisomers of 10,11-epoxy-1-bisabolen-3-ol as a male-released aggregation pheromone called murgantiol. We show that MhTPS (MhIDS-1), an enzyme unrelated to plant and microbial TPSs but with similarity to trans-isoprenyl diphosphate synthases (IDS) of the core terpene biosynthetic pathway, catalyzes the formation of (1S,6S,7R)-1,10-bisaboladien-1-ol (sesquipiperitol) as a terpene intermediate in murgantiol biosynthesis. Sesquipiperitol, a so-far-unknown compound in animals, also occurs in plants, indicating convergent evolution in the biosynthesis of this sesquiterpene. RNAi-mediated knockdown of MhTPS mRNA confirmed the role of MhTPS in murgantiol biosynthesis. MhTPS expression is highly specific to tissues lining the cuticle of the abdominal sternites of mature males. Phylogenetic analysis suggests that MhTPS is derived from a trans-IDS progenitor and diverged from bona fide trans-IDS proteins including MhIDS-2, which functions as an (E,E)-farnesyl diphosphate (FPP) synthase. Structure-guided mutagenesis revealed several residues critical to MhTPS and MhFPPS activity. The emergence of an IDS-like protein with TPS activity in M. histrionica demonstrates that de novo terpene biosynthesis evolved in the Hemiptera in an adaptation for intraspecific communication

Weight matrix based identification of terpene synthases conserved motifs in Arabidopsis thaliana proteome

Terpenes comprise the most diverse collection of natural products. Out of more than 30,000 individual terpenoids identified, at least half are synthesized by plants. A relatively small, but quantitatively significant, number of terpenoids are involved in primary plant metabolism. However, the vast majorities are classified as secondary metabolites; compounds not required for plant growth and development but presumed to have an ecological function in communication or defense and are widely used in industrial applications. Terpene hydrocarbon scaffolds are generated by the action of the mechanistically intriguing family of mono-, sesqui-, and diterpene synthases collectively termed as terpene synthases, that catalyze multistep reactions with diphosphorylated substrates of 10 (geranyl diphosphate), 15 (farnesyl diphosphate) or 20 (geranylgeranyl diphosphate) carbons. In the studied work, we performed a computational study on proteome wide identification of terpene synthase motifs in Arabidopsis thaliana proteome on the basis of weight matrix approach. We have developed an optimal weight matrix for the identification of terpene synthase motifs in the plant’s proteome. Weight matrix was constructed by aligning orthologous sequences of known terpene synthases originated from diverse plant species viz., Abies grandis, Nicotiana tobaccum etc. Sequences of detected domains & motifs were retrieved through SwissProtKB/NCBI on the basis of specific conservation IDs of Prosite, Pfam, Interpro, Prodom, COG, TIGR databases, while position specific scoring matrices were made through MEME, MotifSampler, PossuMsearch tools. Weight matrix based search of conserved motifs in the proteome of A. thaliana was done through ESA, Lahead and Simple algorithm based search tools of PossuMsearch biosuite in Linux system. Prediction was first validated by using positive control data set and optimized the method to reach prediction accuracy upto >90%. After tool performance evaluation, prediction was made on whole proteome at specific threshold/score value. Significant results were found in A. thaliana with motif similarity ranges from 80% to 100%. This proteome wide search model paves the path to identify more terpene synthases genes in A. thaliana, as well as in other plant systems

Carbocations and the Complex Flavor and Bouquet of Wine: Mechanistic Aspects of Terpene Biosynthesis in Wine Grapes.

Computational chemistry approaches for studying the formation of terpenes/terpenoids in wines are presented, using five particular terpenes/terpenoids (1,8-cineole, α-ylangene, botrydial, rotundone, and the wine lactone), volatile compounds (or their precursors) found in wine and/or wine grapes, as representative examples. Through these examples, we show how modern computational quantum chemistry can be employed as an effective tool for assessing the validity of proposed mechanisms for terpene/terpenoid formation

Ambient new particle formation parameter indicates potential rise in future events

Atmospheric new particle formation is a general phenomenon observed over coniferous forests. So far nucleation is described as a function of gaseous sulfuric acid concentration only, which is unable to explain the observed seasonality of nucleation events at different measurement sites. Here we introduce a new nucleation parameter including ozone and water vapor concentrations as well as UV-B radiation as a proxy for OH radical formation. Applying this new parameter to field studies conducted at Finnish and German measurement sites it is found capable to predict the occurrence of nucleation events and their seasonal and annual variation indicating a significant role of organics. Extrapolation to possible future conditions of ozone, water vapor and organic concentrations leads to a significant potential increase in nucleation event number

Pushing the limits of concertedness. A waltz of wandering carbocations.

Among the array of complex terpene-forming carbocation cyclization/rearrangement reactions, the so-called "triple shift" reactions are among the most unexpected. Such reactions involve the asynchronous combination of three 1,n-shifts into a concerted process, e.g., a 1,2-alkyl shift followed by a 1,3-hydride shift followed by a second 1,2-alkyl shift. This type of reaction so far has been proposed to occur during the biosynthesis of diterpenes and the sidechains of sterols. Here we describe efforts to push the limits of concertedness in this type of carbocation reaction by designing, and characterizing with quantum chemical computations, systems that could couple additional 1,n-shift events to a triple shift leading, in principle to quadruple, pentuple, etc. shifts. While our designs did not lead to clear-cut examples of quadruple, etc. shifts, they did lead to reactions with surprisingly flat energy surfaces where more than five chemical events connect reactants and plausible products. Ab initio molecular dynamics simulations demonstrate that the formal minima on these surfaces interchange on short timescales, both with each other and with additional unexpected structures, allowing us a glimpse into a very complex manifold that allows ready access to great structural diversity

Honeybees Learn Odour Mixtures via a Selection of Key Odorants

BACKGROUND The honeybee has to detect, process and learn numerous complex odours from her natural environment on a daily basis. Most of these odours are floral scents, which are mixtures of dozens of different odorants. To date, it is still unclear how the bee brain unravels the complex information contained in scent mixtures. METHODOLOGY/PRINCIPAL FINDINGS This study investigates learning of complex odour mixtures in honeybees using a simple olfactory conditioning procedure, the Proboscis-Extension-Reflex (PER) paradigm. Restrained honeybees were trained to three scent mixtures composed of 14 floral odorants each, and then tested with the individual odorants of each mixture. Bees did not respond to all odorants of a mixture equally: They responded well to a selection of key odorants, which were unique for each of the three scent mixtures. Bees showed less or very little response to the other odorants of the mixtures. The bees' response to mixtures composed of only the key odorants was as good as to the original mixtures of 14 odorants. A mixture composed of the other, non-key-odorants elicited a significantly lower response. Neither an odorant's volatility or molecular structure, nor learning efficiencies for individual odorants affected whether an odorant became a key odorant for a particular mixture. Odorant concentration had a positive effect, with odorants at high concentration likely to become key odorants. CONCLUSIONS/SIGNIFICANCE Our study suggests that the brain processes complex scent mixtures by predominantly learning information from selected key odorants. Our observations on key odorant learning lend significant support to previous work on olfactory learning and mixture processing in honeybees.This work was supported by a grant from the Commonwealth Scientific and Industrial Research Organisation Food Futures Flagship Collaborative Research Fund (CBR3_45865_9 W2003, http://www.csiro.au/org/FoodFuturesFlagship.html). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Terzyme: a tool for identification and analysis of the plant terpenome.

BACKGROUND: Terpenoid hydrocarbons represent the largest and most ancient group of phytochemicals, such that the entire chemical library of a plant is often referred to as its 'terpenome'. Besides having numerous pharmacological properties, terpenes contribute to the scent of the rose, the flavors of cinnamon and the yellow of sunflowers. Rapidly increasing -omics datasets provide an unprecedented opportunity for terpenome detection, paving the way for automated web resources dedicated to phytochemical predictions in genomic data. RESULTS: We have developed Terzyme, a predictive algorithm for identification, classification and assignment of broad substrate unit to terpene synthase (TPS) and prenyl transferase (PT) enzymes, known to generate the enormous structural and functional diversity of terpenoid compounds across the plant kingdom. Terzyme uses sequence information, plant taxonomy and machine learning methods for predicting TPSs and PTs in genome and proteome datasets. We demonstrate a significant enrichment of the currently identified terpenome by running Terzyme on more than 40 plants. CONCLUSIONS: Terzyme is the result of a rigorous analysis of evolutionary relationships between hundreds of characterized sequences of TPSs and PTs with known specificities, followed by analysis of genome-wide gene distribution patterns, ontology based clustering and optimization of various parameters for building accurate profile Hidden Markov Models. The predictive webserver and database is freely available at http://nipgr.res.in/terzyme.html and would serve as a useful tool for deciphering the species-specific phytochemical potential of plant genomes