Visualization of large-scale aqueous solubility data using a novel hierarchical data visualization technique

It is a difficult task to recognize the trends in molecular physical properties relevant to a specific chemical class and find a way to optimize potential compounds. We present here a novel hierarchical data visualization technique, named "HeiankyoView", to visualize large-scale multidimensional chemical information. HeiankyoView represents hierarchically organized data objects by mapping leaf nodes as colored square icons and nonleaf nodes as rectangular borders. In this way, data objects can be expressed as equishaped icons without overlapping one another in the two-dimensional display space. HeiankyoView has been applied to visualize aqueous solubility data for 908 compounds collected from the published literature. When the results of a recursive partitioning analysis and hierarchical clustering analysis were visualized, the trends hidden in the solubility data could be effectively displayed as intuitively understandable visual images. Most interestingly, the data visualization technique, without any statistical computations, was able to assist us in extracting from such large-scale data meaningful information establishing that ClogP and the molecular weight are critical factors in determining aqueous solubility. Thus, HeiankyoView is a powerful tool to help us understand structure-activity relationships intuitively from a large-scale data set.     

Derived Equivalences of Actions of a Category

Let $\mathbb{k}$ be a commutative ring and I a category. As a generalization of a $\mathbb{k}$ -category with a (pseudo) action of a group we consider a family of $\mathbb{k}$ -categories with a (pseudo, lax, or oplax) action of I, namely an oplax functor from I to the 2-category of small $\mathbb{k}$ -categories. We investigate derived equivalences of those oplax functors, and establish a Morita type theorem for them. This gives a base of investigations of derived equivalences of Grothendieck constructions of those oplax functors.     

Structural phase transitions at clean and metal-covered Si(111) surfaces investigated by RHEED spot analysis

Structural phase transitions between various kinds of superlattice structures formed on a Si(111) surface have been investigated by spot analysis of reflection high-energy electron diffraction (RHEED). Reversible transitions induced by temperature changes and irreversible ones induced by metal depositions were observed. Detailed discussions on the dynamics of the phase transitions are made by quantitative analyses of integrated spot intensity and profile. For a phase transition of 7′7  1′1 structures on a clean Si(111) surface, a hysteresis with temperature difference of 5°C. between in heating and cooling processes was found in the spot intensity change, indicating a first-order transition. Hysteresis was hardly recognized, on the other hand, for transitions of Au-induced superstructures (5×2-Au or ×-Au)  1×1-Au. The spot profiles were found to be broadened during the transition of Si(111)-×-Au  1×1-Au, which was a signature of a continuous transition, while the profiles remained unchanged during the transitions of the 7×7  1×1 and 5×2-Au  1×1-Au phases. Structural conversions induced by In adsorption on the Si(111) surface kept at constant temperatures were also analyzed. The conversions at room temperature were totally dependent on the initial substrate surface structures; the 7×7 surface did not show any structural conversion with In adsorption, while the ×-In surface successively converted to a 2×2 and a × phase with coverage increase. The structural transitions at elevated temperatures were sensitively dependent on the temperatures. Sequences of transitions among the 7×7, 4×1, ×, 1×, and ×4 were quantitatively revealed as changes in RHEED spot intensity.     

Development of non-destructive isotopic analysis methods using muon beams and their application to the analysis of lead

Journal of Radioanalytical and Nuclear Chemistry - Elemental isotopic ratios are measured in various research fields and provide useful information regarding age, origin, geological and biological...     

Initial quantum levels of captured muons in CO,CO2, and COS

The role of valence electrons for the muon capture process by molecules is experimentally investigated with the aid of cascade calculations. Low-momentum muons are introduced to gas targets of CO, CO₂, and COS below atmospheric pressure. The initial states of captured muons are determined from the measured muonic X-ray structure of the Lyman and Balmer series. We propose that the lone pair electrons in the carbon atom of CO significantly contribute to the capture of a muon with large angular momenta.

     

Analysis of the nuclear quadrupole interaction of Disulfur Dichloride, S2Cl2

Pure rotational spectra of S₂³⁵Cl₂ and S₂³⁵Cl³⁷Cl have been observed using a Fourier-transform microwave spectrometer. An analysis of the hyperfine structure made by considering the nuclear spin statistics showed that S₂Cl₂ has C₂symmetry, where the hyperfine splittings due to the two Cl nuclei were analyzed precisely. The nuclear quadrupole coupling constants including the off-diagonal (χ_ab, χ_ac, χ_bc) components and the nuclear spin–rotation interaction constants associated with the two Cl nuclei have been determined for the first time. We have shown that the nuclear quadrupole interaction plays an important role in the ortho–para mixing.     

Fine-tuning of boron complexes with cage-shaped ligand geometry: rational design of triphenolic ligand as a template for structure control

Boron complexes surrounded with organic cages were controlled precisely by a remote atom placed at the bottom of the cage. A replacement of the bottom tether atom (carbon or silicon) changed the characteristics (kinetic and thermodynamic factors) of boron complexes by geometric effects. A theoretical study shows that the bottom atoms also control eigenvalues of MO. This cage complex will provide a systematic template for fine-tuning of metal complexes to create various properties.     

Novel hierarchical classification and visualization method for multiobjective optimization of drug properties: application to structure-activity relationship analysis of cytochrome P450 metabolism

In the lead optimization process, medicinal chemists must consider various chemical properties of active compounds, including ADME/Tox properties, and find the best compromise among these. This study presents a novel data mining method for multiobjective optimization of chemical properties, which consists of the hierarchical classification and visualization of multidimensional data. A hierarchical classification tree model is generated by an extension of recursive partitioning that utilizes averaged information gains for multiple objective variables as a quality-of-split criterion. All the hierarchically structured data objects are represented using a large-scale data visualization technique. The technique is an extension of HeiankyoView, which displays data objects as colored icons and group nodes as rectangular borders. Each icon is divided into subregions with different colors, so that it can present multidimensional data according to brightness of the colors. The proposed method was applied to the structure-activity relationship analysis for cytochrome P450 (CYP) substrates. The substrate specificity of six CYP isoforms was successfully delineated: e.g., CYP2C9 substrates are anionic compounds, while CYP2D6 substrates are cationic; and CYP2E1 substrates are smaller compounds, while CYP3A4 substrates are larger compounds.