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Interaction fingerprints are vector representations that summarize the three-dimensional nature of interactions in molecular complexes, typically formed between a protein and a ligand. This kind of encoding has found many applications in drug-discovery projects, from structure-based virtual-screening to machine-learning. Here, we present ProLIF, a Python library designed to generate interaction fingerprints for molecular complexes extracted from molecular dynamics trajectories, experimental structures, and docking simulations. It can handle complexes formed of any combination of ligand, protein, DNA, or RNA molecules. The available interaction types can be fully reparametrized or extended by user-defined ones. Several tutorials that cover typical use-case scenarios are available, and the documentation is accompanied with code snippets showcasing the integration with other data-analysis libraries for a more seamless user-experience. The library can be freely installed from our GitHub repository (https://github.com/chemosim-lab/ProLIF). [ABSTRACT FROM AUTHOR]

Lavender essential oils (EOs) of higher quality are produced by a few Lavandula angustifolia cultivars and mainly used in the perfume industry. Undesirable compounds such as camphor and borneol are also synthesized by lavender leading to a depreciated EO. Here, we report the cloning of bornyl diphosphate synthase of lavender ( LaBPPS ), an enzyme that catalyzes the production of bornyl diphosphate (BPP) and then by-products such as borneol or camphor, from an EST library. Compared to the BPPS of Salvia officinalis , the functional characterization of LaBPPS showed several differences in amino acid sequence, and the distribution of catalyzed products. Molecular modeling of the enzyme's active site suggests that the carbocation intermediates are more stable in LaBPPS than in SoBPPS leading probably to a lower efficiency of LaBPPS to convert GPP into BPP. Quantitative RT-PCR performed from leaves and flowers at different development stages of L. angustifolia samples show a clear correlation between transcript level of LaBPPS and accumulation of borneol/camphor, suggesting that LaBPPS is mainly responsible of in vivo biosynthesis of borneol/camphor in fine lavender. A phylogenetic analysis of terpene synthases (TPS) pointed out the basal position of LaBPPS in the TPSb clade, suggesting that LaBPPS could be an ancestor of others lavender TPSb. Finally, borneol could be one of the first monoterpenes to be synthesized in the Lavandula subgenus. Knowledge gained from these experiments will facilitate future studies to improve the lavender oils through metabolic engineering or plant breeding. Accession numbers: LaBPPS: KM015221. [ABSTRACT FROM AUTHOR]

Background: Macromolecular docking is a challenging field of bioinformatics. Developing new algorithms is a slow process generally involving routine tasks that should be found in a robust library and not programmed from scratch for every new software application. Results: We present an object-oriented Python/C++ library to help the development of new docking methods. This library contains low-level routines like PDB-format manipulation functions as well as high-level tools for docking and analyzing results. We also illustrate the ease of use of this library with the detailed implementation of a 3-body docking procedure. Conclusion: The PTools library can handle molecules at coarse-grained or atomic resolution and allows users to rapidly develop new software. The library is already in use for protein-protein and protein-DNA docking with the ATTRACT program and for simulation analysis. This library is freely available under the GNU GPL license, together with detailed documentation. [ABSTRACT FROM AUTHOR]

Citronellol is a pleasant-smelling compound produced in rose (Rosa spp.) flowers and in the leaves of many aromatic plants, including pelargoniums (Pelargonium spp.). Although geraniol production has been well studied in several plants, citronellol biosynthesis has been documented only in crab-lipped spider orchid (Caladenia plicata) and its mechanism remains open to question in other species. We therefore profiled 10 pelargonium accessions using RNA sequencing and gas chromatography-MS analysis. Three enzymes from the progesterone 5β-reductase and/or iridoid synthase-like enzymes (PRISE) family were characterized in vitroand subsequently identified as citral reductases (named PhCIRs). Transgenic RNAi lines supported a role for PhCIRs in the biosynthesis of citronellol as well as in the production of mint-scented terpenes. Despite their high amino acid sequence identity, the 3 enzymes showed contrasting stereoselectivity, either producing mainly (S)-citronellal or a racemate of both (R)- and (S)-citronellal. Using site-directed mutagenesis, we identified a single amino acid substitution as being primarily responsible for the enzyme's enantioselectivity. Phylogenetic analysis of pelargonium PRISEs revealed 3 clades and 7 groups of orthologs. PRISEs from different groups exhibited differential affinities toward substrates (citral and progesterone) and cofactors (NADH/NADPH), but most were able to reduce both substrates, prompting hypotheses regarding the evolutionary history of PhCIRs. Our results demonstrate that pelargoniums evolved citronellol biosynthesis independently through a 3-step pathway involving PRISE homologs and both citral and citronellal as intermediates. In addition, these enzymes control the enantiomeric ratio of citronellol thanks to small alterations of the catalytic site. Molecular biology, bioinformatics, and analytical chemistry techniques reveal how fragrant pelargoniums perfume the air with rose scent. [ABSTRACT FROM AUTHOR]

Hydrogenases are promising candidatesfor the catalytic productionof green energy by means of biological ways. The major impedimentto such a production is rooted in their inhibition under aerobic conditions.In this work, we model dioxygen migration rates in mutants of a hydrogenaseof Desulfovibrio fructusovorans. The approach relieson the calculation of the whole potential of mean force for O2migration within the wild-type as well as in V74M, V74F,and V74Q mutant channels. The three free-energy barriers along theentire migration pathway are converted into chemical rates throughmodeling based on Transition State Theory. The use of such a modelrecovers the trend of O2migration rates among the series. [ABSTRACT FROM AUTHOR]

Bitter taste receptors (TAS2Rs) are a poorly understood subgroup of G protein-coupled receptors (GPCRs). The experimental structure of these receptors has yet to be determined, and key-residues controlling their function remain mostly unknown. We designed an integrative approach to improve comparative modeling of TAS2Rs. Using current knowledge on class A GPCRs and existing experimental data in the literature as constraints, we pinpointed conserved motifs to entirely re-align the amino-acid sequences of TAS2Rs. We constructed accurate homology models of human TAS2Rs. As a test case, we examined the accuracy of the TAS2R16 model with site-directed mutagenesis and in vitro functional assays. This combination of in silico and in vitro results clarifies sequence-function relationships and proposes functional molecular switches that encode agonist sensing and downstream signaling mechanisms within mammalian TAS2Rs sequences. [ABSTRACT FROM AUTHOR]

The concept of reverse chemical ecology (exploitation of molecular knowledge for chemical ecology) has recently emerged in conservation biology and human health. Here, we extend this concept to crop protection. Targeting odorant receptors from a crop pest insect, the noctuid moth Spodoptera littoralis, we demonstrate that reverse chemical ecology has the potential to accelerate the discovery of novel crop pest insect attractants and repellents. Using machine learning, we first predicted novel natural ligands for two odorant receptors, SlitOR24 and 25. Then, electrophysiological validation proved in silico predictions to be highly sensitive, as 93% and 67% of predicted agonists triggered a response in Drosophila olfactory neurons expressing SlitOR24 and SlitOR25, respectively, despite a lack of specificity. Last, when tested in Y-maze behavioral assays, the most active novel ligands of the receptors were attractive to caterpillars. This work provides a template for rational design of new eco-friendly semiochemicals to manage crop pest populations. [ABSTRACT FROM AUTHOR]

Odorant receptors expressed at the peripheral olfactory organs are key proteins for animal volatile sensing. Although they determine the odor space of a given species, their functional characterization is a long process and remains limited. To date, machine learning virtual screening has been used to predict new ligands for such receptors in both mammals and insects, using chemical features of known ligands. In insects, such approach is yet limited to Diptera, whereas insect odorant receptors are known to be highly divergent between orders. Here, we extend this strategy to a Lepidoptera receptor, SlitOR25, involved in the recognition of attractive odorants in the crop pest Spodoptera littoralis larvae. Virtual screening of 3 million molecules predicted 32 purchasable ones whose function has been systematically tested on SlitOR25, revealing 11 novel agonists with a success rate of 28%. Our results show that Support Vector Machine optimizes the discovery of novel agonists and expands the chemical space of a Lepidoptera OR. More, it opens up structure-function relationship analyses through a comparison of the agonist chemical structures. This proof-of-concept in a crop pest could ultimately enable the identification of OR agonists or antagonists, capable of modifying olfactory behaviors in a context of biocontrol. [ABSTRACT FROM AUTHOR]

Divalent and trivalent salts exhibit a complex taste profile. They are perceived as being astringent/drying, sour, bitter, and metallic. We hypothesized that human bitter-taste receptors may mediate some taste attributes of these salts. Using a cell-based functional assay, we found that TAS2R7 responds to a broad range of divalent and trivalent salts, including zinc, calcium, magnesium, copper, manganese, and aluminum, but not to potassium, suggesting TAS2R7 may act as a metal cation receptor mediating bitterness of divalent and trivalent salts. Molecular modeling and mutagenesis analysis identified 2 residues, H943.37 and E2647.32, in TAS2R7 that appear to be responsible for the interaction of TAS2R7 with metallic ions. Taste receptors are found in both oral and extraoral tissues. The responsiveness of TAS2R7 to various mineral salts suggests it may act as a broad sensor, similar to the calcium-sensing receptor, for biologically relevant metal cations in both oral and extraoral tissues. [ABSTRACT FROM AUTHOR]

Mammalian sensory systems detect sweet taste through the activation of a single heteromeric T1R2/T1R3 receptor belonging to class C G-protein-coupled receptors. Allosteric ligands are known to interact within the transmembrane domain, yet a complete view of receptor activation remains elusive. By combining site-directed mutagenesis with computational modeling, we investigate the structure and dynamics of the allosteric binding pocket of the T1R3 sweet-taste receptor in its apo form, and in the presence of an allosteric ligand, cyclamate. A novel positively charged residue at the extracellular loop 2 is shown to interact with the ligand. Molecular dynamics simulations capture significant differences in the behavior of a network of conserved residues with and without cyclamate, although they do not directly interact with the allosteric ligand. Structural models show that they adopt alternate conformations, associated with a conformational change in the transmembrane region. Site-directed mutagenesis confirms that these residues are unequivocally involved in the receptor function and the allosteric signaling mechanism of the sweet-taste receptor. Similar to a large portion of the transmembrane domain, they are highly conserved among mammals, suggesting an activation mechanism that is evolutionarily conserved. This work provides a structural basis for describing the dynamics of the receptor, and for the rational design of new sweet-taste modulators. [ABSTRACT FROM AUTHOR]

Determining the protein-protein interactions is still a major challenge for molecular biology. Docking protocols has come of age in predicting the structure of macromolecular complexes. However, they still lack accuracy to estimate the binding affinities, the thermodynamic quantity that drives the formation of a complex. Here, an updated version of the protein-protein ATTRACT force field aiming at predicting experimental binding affinities is reported. It has been designed on a dataset of 218 protein-protein complexes. The correlation between the experimental and predicted affinities reaches 0.6, outperforming most of the available protocols. Focusing on a subset of rigid and flexible complexes, the performance raises to 0.76 and 0.69, respectively. © 2017 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Based on the most exhaustive database of sweeteners with known sweetness values, a new quantitative structure-activity relationship model for sweetness prediction has been set up. Analysis of the physico-chemical properties of sweeteners in the database indicates that the structure of most potent sweeteners combines a hydrophobic scaffold functionalized by a limited number of hydrogen bond sites (less than 4 hydrogen bond donors and 10 acceptors), with a moderate molecular weight ranging from 350 to 450 g·mol −1 . Prediction of sweetness, bitterness and toxicity properties of the largest database of natural compounds have been performed. In silico screening reveals that the majority of the predicted natural intense sweeteners comprise saponin or stevioside scaffolds. The model highlights that their sweetness potency is comparable to known natural sweeteners. The identified compounds provide a rational basis to initiate the design and chemosensory analysis of new low-calorie sweeteners. [ABSTRACT FROM AUTHOR]

• Identification of a new sweetener scaffold belonging to the lignan chemical family. • Update and curation of the SweetenersDB dataset. • Setup of a machine learning model for the prediction of sweetness. • Implementation of Predisweet, a webserver based on the machine learning model. Sugar replacement is still an active issue in the food industry. The use of structure-taste relationships remains one of the most rational strategy to expand the chemical space associated to sweet taste. A new machine learning model has been setup based on an update of the SweetenersDB and on open-source molecular features. It has been implemented on a freely accessible webserver. Cellular functional assays show that the sweet taste receptor is activated in vitro by a new scaffold of natural compounds identified by the in silico protocol. The newly identified sweetener belongs to the lignan chemical family and opens a new chemical space to explore. [ABSTRACT FROM AUTHOR]

Molecular motors transport various cargoes including vesicles, proteins and mRNAs, to distinct intracellular compartments. A significant challenge in the field of nanotechnology is to improve drug nuclear delivery by engineering nanocarriers transported by cytoskeletal motors. However, suitable in vivo models to assay transport and delivery efficiency remain very limited. Here, we develop a fast and genetically tractable assay to test the efficiency and dynamics of fluospheres (FS) using microinjection into Drosophila oocytes coupled with time-lapse microscopy. We designed dynein motor driven FS using a collection of dynein light chain 8 (LC8) peptide binding motifs as molecular linkers and characterized in real time the efficiency of the FS movement according to its linker’s sequence. Results show that the conserved LC8 binding motif allows fast perinuclear nanoparticle's accumulation in a microtubule and dynein dependent mechanism. These data reveal the Drosophila oocyte as a new valuable tool for the design of motor driven nanovectors. [ABSTRACT FROM AUTHOR]