Enantioselective Diels-Alder reactions with N-hydroxy-N-phenylacrylamide

[reaction: see text] The use of hydroxamic acids as templates for Lewis acid catalyzed enantioselective Diels-Alder reactions has been examined. A very simple chiral Lewis acid, prepared by mixing optically pure binaphthol with 3 equiv of trimethylaluminum, catalyzes the [4 + 2] cycloaddition of N-hydroxy-N-phenylacrylamide with cyclopentadiene at 0 degrees C in high yield (>96%) and with a fairly good level of enantioselectivity (91% ee). Facile conversion of the products to the corresponding alcohols or aldehydes makes the hydroxamic acid intermediates particularly useful.     

Reaction-based machine learning representations for predicting the enantioselectivity of organocatalysts

Hundreds of catalytic methods are developed each year to meet the demand for high-purity chiral compounds. The computational design of enantioselective organocatalysts remains a significant challenge, as catalysts are typically discovered through experimental screening. Recent advances in combining quantum chemical computations and machine learning (ML) hold great potential to propel the next leap forward in asymmetric catalysis. Within the context of quantum chemical machine learning (QML, or atomistic ML), the ML representations used to encode the three-dimensional structure of molecules and evaluate their similarity cannot easily capture the subtle energy differences that govern enantioselectivity. Here, we present a general strategy for improving molecular representations within an atomistic machine learning model to predict the DFT-computed enantiomeric excess of asymmetric propargylation organocatalysts solely from the structure of catalytic cycle intermediates. Mean absolute errors as low as 0.25 kcal mol⁻¹ were achieved in predictions of the activation energy with respect to DFT computations. By virtue of its design, this strategy is generalisable to other ML models, to experimental data and to any catalytic asymmetric reaction, enabling the rapid screening of structurally diverse organocatalysts from available structural information.

A machine learning model for enantioselectivity prediction using reaction-based molecular representations.     

The change of aromaticity along a Diels-Alder reaction path

[reaction: see text] Quinodimethanes are highly reactive toward dienophiles since Diels-Alder cycloaddition results in an aromatic product. Density functional-based (13)C, (1)H NMR, NICS, and MO-NICS calculations indicate that the increase of aromatic character of the developing benzenoid ring along the reaction path is especially pronounced after the transition state is reached, even though the number of pi orbitals decreases. The forming aliphatic ring exhibits large ring current effects during the reaction.     

A computational study of radical haloacetal cyclizations controlled by the acetal center

The stereochemical outcome of the radical haloacetal cyclization reaction (Ueno-Stork reaction) has been examined by ab initio and other molecular orbital techniques. It was found that the stereochemistry of 5-exo- and 6-exo trig cyclizations can be accurately predicted from calculations using moderate levels of theory (UHF/6-311G** or B3LYP/6-311G**). A simplified computational procedure, easily run on a standard desktop computer, has been developed that provides excellent predictive ability for the stereochemical outcome for the reactions in question. Interestingly, a novel twist transition state has been identified for the first time in 5-exo-trig radical cyclization reactions.     

Structure determination of slowly exchanging conformers in solution using high‐resolution NMR,computational modeling and DFT‐GIAO chemical shielding: application to an erythronolide A derivative

We discuss and demonstrate the potential of HSQC‐TOCSY and HSQC‐NOESY experiments to offer solutions for overlap problems in COSY and NOESY spectra, leading to improved signals that can be unambiguously assigned to individual carbons. Direct comparison of experimental ¹H and ¹³C chemical shielding with density functional theory (DFT)‐calculated values are uninformative; in contrast, the relative differences in experimental shielding between pairs of molecules correlates well with the relative differences in DFT‐GIAO shielding for the computed lowest energy conformers. A detailed application of both experimental and theoretical techniques is illustrated for slowly exchanging conformers of an erythronolide A derivative, which demonstrates that structure determination can strongly benefit from the interplay between experiment and theory. Copyright © 2009 John Wiley & Sons, Ltd.     

Investigating the relationship between cell cycle stage and diosgenin-induced megakaryocytic differentiation of HEL cells using sedimentation field-flow fractionation

Differentiation therapy could be one strategy for stopping cancer cell proliferation. A plant steroid, diosgenin, is known to induce megakaryocytic differentiation in human erythroleukemia (HEL) cells. In recent studies, the use of sedimentation field-flow fractionation (SdFFF) allowed the preparation of subpopulations that may differ in regard to sensitivity to differentiation induction. The specific goal of this study was to determine the relationship between cell cycle stage and sensitivity to megakaryocytic differentiation induction of HEL cells. After first confirming the capacity of diosgenin to specifically select targets, hyperlayer SdFFF cell sorting was used to prepare fractions according to cell cycle position from crude HEL cells. The sensitivities of these fractions to diosgenin-induced differentiation were then tested. The coupling of SdFFF cell separation to imaging flow cytometry showed that G1-phase cells were more sensitive to differentiation induction than S/G2M-phase cells, confirming the relationship between cell status at the start of induction, the extent of the biological event, and the potential of SdFFF in cancer research.     

Efficiency of random search procedures along the silicon cluster series: Si(n) (n=5-10, 15, and 20)

The efficiency of the simplest isomeric search procedure consisting in random generation of sets of atomic coordinates followed by density functional theory geometry optimization is tested on the silicon cluster series (Si(5-10, 15, 20)). Criteria such as yield, isomer distributions and recurrences are used to clearly establish the performance of the approach with respect to increasing cluster size. The elimination of unphysical candidate structures and the use of distinct box shapes and theoretical levels are also investigated. For the smaller Si(n) (n=5-10) clusters, the generation of random coordinates within a spherical box is found to offer a reasonable alternative to more complex algorithms by allowing straightforward identification of every known low-lying local minima. The simple stochastic search of larger clusters (i.e. Si(15) and Si(20)) is however complicated by the exponentially increasing number of both low- and high-lying minima leading to rather arbitrary and non-comprehensive results.     

A nonstandard finite difference scheme for contaminant transport with kinetic langmuir sorption

This study focuses on a contaminant transport model with Langmuir sorption under nonequilibrium conditions. The numerical instabilities of the standard finite difference schemes including the upwind method are investigated. By using the nonstandard finite difference method, a better finite difference model is constructed. The numerical simulation on a specific system configuration proves the advantages of the new finite difference model. © 2009 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq 27: 767–785, 2011     

Dispersion-corrected energy decomposition analysis for intermolecular interactions based on the BLW and dDXDM methods

As the simplest variant of the valence bond (VB) theory, the block-localized wave function (BLW) method defines the intermediate electron-localized state self-consistently at the DFT level and can be used to explore the nature of intermolecular interactions in terms of several physically intuitive energy components. Yet, it is unclear how the dispersion interaction affects such a kind of energy decomposition analysis (EDA) as standard density functional approximations neglect the long-range dispersion attractive interactions. Three electron densities corresponding to the initial electron-localized state, optimal electron-localized state, and final electron-delocalized state are involved in the BLW-ED approach; a density-dependent dispersion correction, such as the recently proposed dDXDM approach, can thus uniquely probe the impact of the long-range dispersion effect on EDA results computed at the DFT level. In this paper, we incorporate the dDXDM dispersion corrections into the BLW-ED approach and investigate a range of representative systems such as hydrogen-bonding systems, acid-base pairs, and van der Waals complexes. Results show that both the polarization and charge-transfer energies are little affected by the inclusion of the long-range dispersion effect, which thus can be regarded as an independent energy component in EDA.