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Reliably producing a competent oocyte entails a deeper comprehension of ovarian follicle maturation, a very complex process that includes meiotic maturation of the female gamete, the oocyte, together with the mitotic divisions of the hormone-producing somatic cells. In this report, we investigate murine ovarian folliculogenesis in vivo using publicly available time-series microarrays from primordial to antral stage follicles. Manually curated protein interaction networks were employed to identify autocrine and paracrine signaling between the oocyte and the somatic cells (granulosa and theca cells) at multiple stages of follicle development. We established plausible protein-binding interactions between expressed genes that encode secreted factors and expressed genes that encode cellular receptors. Some computationally identified signaling interactions are well established, such as the paracrine signaling from the oocyte to the somatic cells through the oocyte-secreted growth factor Gdf9, while others are novel connections in term of ovarian folliculogenesis, such as the possible paracrine connection from somatic-secreted factor Ntn3 to the oocyte receptor Neo1. Additionally, we identified several of the likely transcription factors that might control the dynamic transcriptome during ovarian follicle development, noting that the YAP/TAZ signaling pathway is very active in vivo. This novel dynamic model of signaling and regulation can be employed to generate testable hypotheses regarding follicle development that could be validated experimentally, guiding the improvement of culture media to enhance in vitro ovarian follicle maturation and possibly novel therapeutic targets for reproductive diseases. [ABSTRACT FROM AUTHOR]

Quantum chemical calculations are emerging as an effective way to screen catalysts for particular applications. In this contribution, we demonstrate the power of density functional theory to study CO2 hydrolysisby six carbonic anhydrase mimics, evaluating thermodynamic and kinetic parameters at the mechanistic level. A microkinetic model was then built based on the kinetics and thermodynamics calculated from first principles. The intrinsic reaction rate constant was calculated from the results of the microkinetic model and compared with experimental data. Overall, the rate constants were in good agreement with experimental values, except for zinc-tri and complex b, which were overestimated. This was ascribed to their ineffective complexation with Zn2+. How the reaction rate constants vary with time was also investigated. From 0 to 12 ms, the rate constants of complexes a and d decreased to 50 and 67% of their initial values, respectively; the rate constants of complexes b and f2 were almost invariant with time; the rate constant of complex f1 showed an unusual double sigmoidal shape. The pKa values of these six carbonic anhydrase mimics as well as three additional mimics were calculated. A correlation between pKa values and the binding free energy of OH-was obtained by fitting data from five zinc(II) aza-macrocyclic complexes. The reaction rate constants were found to increase linearly with the pKa value, indicating CO2 adsorption is the rate-limiting step. [ABSTRACT FROM AUTHOR]

Background: In spite of its great promise, metabolomics has proven difficult to execute in an untargeted and generalizable manner. Liquid chromatography–mass spectrometry (LC–MS) has made it possible to gather data on thousands of cellular metabolites. However, matching metabolites to their spectral features continues to be a bottleneck, meaning that much of the collected information remains uninterpreted and that new metabolites are seldom discovered in untargeted studies. These challenges require new approaches that consider compounds beyond those available in curated biochemistry databases. Description: Here we present Metabolic In silico Network Expansions (MINEs), an extension of known metabolite databases to include molecules that have not been observed, but are likely to occur based on known metabolites and common biochemical reactions. We utilize an algorithm called the Biochemical Network Integrated Computational Explorer (BNICE) and expert-curated reaction rules based on the Enzyme Commission classification system to propose the novel chemical structures and reactions that comprise MINE databases. Starting from the Kyoto Encyclopedia of Genes and Genomes (KEGG) COMPOUND database, the MINE contains over 571,000 compounds, of which 93% are not present in the PubChem database. However, these MINE compounds have on average higher structural similarity to natural products than compounds from KEGG or PubChem. MINE databases were able to propose annotations for 98.6% of a set of 667 MassBank spectra, 14% more than KEGG alone and equivalent to PubChem while returning far fewer candidates per spectra than PubChem (46 vs. 1715 median candidates). Application of MINEs to LC–MS accurate mass data enabled the identity of an unknown peak to be confidently predicted. Conclusions: MINE databases are freely accessible for non-commercial use via user-friendly web-tools at http:// minedatabase.mcs.anl.gov and developer-friendly APIs. MINEs improve metabolomics peak identification as compared to general chemical databases whose results include irrelevant synthetic compounds. Furthermore, MINEs complement and expand on previous in silico generated compound databases that focus on human metabolism. We are actively developing the database; future versions of this resource will incorporate transformation rules for spontaneous chemical reactions and more advanced filtering and prioritization of candidate structures. [ABSTRACT FROM AUTHOR]

molecular modeling strategy to screen the capacity of known enzymes to catalyze the reactions of non-native substrates is presented. The binding of pyruvic acid and non-native ketoacids in the active site of pyruvate ferredoxin oxidoreductase was examined using docking analysis, and our results suggest that enzyme-non-native ketoacid-bound species are feasible. Quantum mechanics/molecular mechanics methods were then used to study the geometry of the covalent intermediate formed from the enzyme and the various ketoacids. Finally, quantum mechanical methods were used to study the decarboxylation reaction of 2-keto acids at the mechanistic level. This hierarchical screening ranked the substrates from those that cannot be accommodated by the enzyme (phenyl pyruvate) to those whose conversion rate would most closely approach that of the native substrate (2-ketobutanoic acid and 2-ketovaleric acid). Most notably, our investigation suggests that novel pathways generated using generalized enzyme actions may be screened using the hierarchical approach employed here. [ABSTRACT FROM AUTHOR]

In this study, the formation of oxazolidinone intermediates along the reaction coordinates of two l-proline-catalyzed reactions was investigated using high-level quantum mechanical calculations. Our results suggest that the final product is produced via routes other than the currently-adopted catalytic cycle for l-proline, including routes where oxazolidinones are directly involved. [ABSTRACT FROM AUTHOR]

We offer an overview of the popular one- dimensional (1-D) hindered rotor model that is often used for quantum mechanical treatment of internal rotation. This model is put in context with other methods used for treating anharmonic motions. The 1-D hindered rotor scheme is general for tops of any symmetry and has been used to provide accurate treatment of hindered rotors in a wide range of systems. One obstacle preventing wider use of the model is its lack of incorporation into common electronic structure codes. We have developed an algorithm for consistently treating all tops in a molecule, and we present simple codes which interface with electronic structure codes to provide thermochemical properties (S, C p , H) of individual species and reactions that have been corrected for internal rotations. Finally, we use this approach to give sensible advice about how the model can be used best. We show that dramatic changes in the reduced moment of inertia do not necessarily cause comparable changes in the properties of individual hindered rotors. We demonstrate that the rotational hindrance potential can be accurately determined using relatively coarse step sizes. Finally, we show that internal rotation in transition states can be treated using a “frozen transition state” approximation at a significant computational savings. We also discuss the relationship between calculated properties of hindered rotors and the choice of method and basis set used. [ABSTRACT FROM AUTHOR]

Owing to the improvement of properties including conductivity, toughness and permeability, polymer nanocomposites are slated for applications ranging from membranes to fuel cells. The enhancement of polymer properties by the addition of inorganic nanoparticles is a complex function of interfacial interactions, interfacial area and the distribution of inter-nanofiller distances. The latter two factors depend on nanofiller dispersion, making it difficult to develop a fundamental understanding of their effects on nanocomposite properties. Here, we design model poly(methyl methacrylate)–silica and poly(2-vinyl pyridine)–silica nanocomposites consisting of polymer films confined between silica slides. We compare the dependence of the glass-transition temperature (Tg) and physical ageing on the interlayer distance in model nanocomposites with the dependence of silica nanoparticle content in real nanocomposites. We show that model nanocomposites provide a simple way to gain insight into the effect of interparticle spacing on Tg and to predict the approximate ageing response of real nanocomposites. [ABSTRACT FROM AUTHOR]