Counterion and substrate effects on barrier heights of the hydrolytic kinetic resolution of terminal epoxides catalyzed by Co(III)-salen.

Density functional theory (DFT) has been applied to the proposed rate-limiting step of the hydrolytic kinetic resolution (HKR) of terminal epoxides as catalyzed by Co-salen-X (X = counterion) in order to resolve questions surrounding the mechanism. The present results indicate that the bimetallic mechanism proposed by Jacobsen shows nonadditive, cooperative catalysis with a larger reduction in barrier height than the sum of the barrier height reductions from the two monometallic reaction pathways. We computed barrier heights for the reaction using several counterions (chloride, acetate, tosylate, and hydroxide). For the three counterions that are experimentally active (chloride, acetate, and tosylate) the barrier heights are 35, 38, and 34 kJ mol(-1), respectively, while for hydroxide it is 48 kJ mol(-1). The similarity of the barrier heights for chloride, acetate, and tosylate is in agreement with their similar peak reaction rates. The finding that Co-salen-X with these counterions leads to rather different overall reaction profiles suggests that they have quite different rates of reaction with epoxide to form the activated Co-salen-OH required for the bimetallic mechanism. Co-salen-OH is inactive as the sole catalyst for HKR, and this inactivity is ascribed to its larger barrier height for the ring-opening step, rather than to any inability to activate epoxide. Barrier heights were also computed using propylene oxide, 1-hexene oxide, and epichlorohydrin; propylene oxide and 1-hexene oxide have similar barrier heights, 35.5 and 33.2 kJ mol(-1), respectively, and epichlorohydrin has a significantly lower barrier height of 18.8 kJ mol(-1), which is qualitatively consistent with experiments showing faster reactions for epicholorohydrin than propylene oxide when catalyzed by Co-salen-OAc.

A tyrosine-rich cell surface protein in the diatom Amphora coffeaeformis identified through transcriptome analysis and genetic transformation.

Diatoms are single-celled eukaryotic microalgae that are ubiquitously found in almost all aquatic ecosystems, and are characterized by their intricately structured SiO2 (silica)-based cell walls. Diatoms with a benthic life style are capable of attaching to any natural or man-made submerged surface, thus contributing substantially to both microbial biofilm communities and economic losses through biofouling. Surface attachment of diatoms is mediated by a carbohydrate- and protein- based glue, yet no protein involved in diatom underwater adhesion has been identified so far. In the present work, we have generated a normalized transcriptome database from the model adhesion diatom Amphora coffeaeformis. Using an unconventional bioinformatics analysis we have identified five proteins that exhibit unique amino acid sequences resembling the amino acid composition of the tyrosine-rich adhesion proteins from mussel footpads. Establishing the first method for the molecular genetic transformation of A. coffeaeformis has enabled investigations into the function of one of these proteins, AC3362, through expression as YFP fusion protein. Biochemical analysis and imaging by fluorescence microscopy revealed that AC3362 is not involved in adhesion, but rather plays a role in biosynthesis and/or structural stability of the cell wall. The methods established in the present study have paved the way for further molecular studies on the mechanisms of underwater adhesion and biological silica formation in the diatom A. coffeaeformis.

Communication: resolving the three-body contribution to the lattice energy of crystalline benzene: benchmark results from coupled-cluster theory.

Coupled-cluster theory including single, double, and perturbative triple excitations [CCSD(T)] has been applied to trimers that appear in crystalline benzene in order to resolve discrepancies in the literature about the magnitude of non-additive three-body contributions to the lattice energy. The present results indicate a non-additive three-body contribution of 0.89 kcal mol(-1), or 7.2% of the revised lattice energy of -12.3 kcal mol(-1). For the trimers for which we were able to compute CCSD(T) energies, we obtain a sizeable difference of 0.63 kcal mol(-1) between the CCSD(T) and MP2 three-body contributions to the lattice energy, confirming that three-body dispersion dominates over three-body induction. Taking this difference as an estimate of three-body dispersion for the closer trimers, and adding an Axilrod-Teller-Muto estimate of 0.13 kcal mol(-1) for long-range contributions yields an overall value of 0.76 kcal mol(-1) for three-body dispersion, a significantly smaller value than in several recent studies.

Buckyplates and buckybowls: examining the effects of curvature on π-π interactions.

π-π interactions are integral to many areas of chemistry, biochemistry, and materials science. Here we use electronic structure theory to analyze how π-π interactions change as the π-systems are curved in model complexes based on coronene and corannulene dimers. Curvature redistributes electronic charge in the π-cloud and creates a dipole moment in these systems, leading to enhanced intermolecular electrostatic interactions in the concave-convex (nested) geometries that are the focus of this work. Curvature of both monomers also has a geometric effect on the interaction by decreasing the average C-C distance between monomers and by increasing the magnitude of both favorable London dispersion interactions and unfavorable exchange-repulsion interactions. Overall, increasing curvature in nested π-π interactions leads to more favorable interaction energies regardless of the native state of the monomers, except at short distances where the most highly curved systems are less favorable as exchange repulsion terms begin to dominate the interaction.

Formal Estimation of Errors in Computed Absolute Interaction Energies of Protein-ligand Complexes.

A largely unsolved problem in computational biochemistry is the accurate prediction of binding affinities of small ligands to protein receptors. We present a detailed analysis of the systematic and random errors present in computational methods through the use of error probability density functions, specifically for computed interaction energies between chemical fragments comprising a protein-ligand complex. An HIV-II protease crystal structure with a bound ligand (indinavir) was chosen as a model protein-ligand complex. The complex was decomposed into twenty-one (21) interacting fragment pairs, which were studied using a number of computational methods. The chemically accurate complete basis set coupled cluster theory (CCSD(T)/CBS) interaction energies were used as reference values to generate our error estimates. In our analysis we observed significant systematic and random errors in most methods, which was surprising especially for parameterized classical and semiempirical quantum mechanical calculations. After propagating these fragment-based error estimates over the entire protein-ligand complex, our total error estimates for many methods are large compared to the experimentally determined free energy of binding. Thus, we conclude that statistical error analysis is a necessary addition to any scoring function attempting to produce reliable binding affinity predictions.