Electronic Structure of Fullerenelike Molecules Based on TiO2, SnO2, and SnS2

Quantum-chemical modeling of electronic structure and interatomic interaction parameters has been performed for a series of fullerenelike cage molecules based on the isoelectronic TiO₂, SnO₂, and SnS₂. The above characteristics are analyzed in relation to the type of atomic configuration, as well as the size and chemical composition of a nanostructure.     

An approach to computer-aided inhibitor design: Application to cathepsin L

Summary We have developed an approach to search for molecules that can be used as lead compounds in designing an inhibitor for a given proteolytic enzyme when the 3D structure of a homologous protein is known. This approach is based on taking the cast of the binding pocket of the protease and comparing its dimensions with that of the dimensions of small molecules. Herein the 3D structure of papain is used to model cathepsin L using the comparative modeling technique. The cast of the binding pocket is computed using the crystal structure of papain because the structures of papain and the model of cathepsin L are found to be similar at the binding site. The dimensions of the cast of the binding site of papain are used to screen for molecules from the Cambridge Structural Database (CSD) of small molecules. Twenty molecules out of the 80 000 small molecules in the CSD are found to have dimensions that are accommodated by the papain binding pocket. Visual comparison of the shapes of the cast and the 20 screened molecules resulted in identifying brevotoxin b, a toxin isolated from the red tide dinoflagellate Ptycho brevis (previously classified as Gymonodium breve), as the structure that best fits the binding pocket of papain. We tested the proteolytic activity of papain and cathepsin L in the presence of brevotoxin b and found inhibition of papain and cathepsin L with K_is of 25 M and 0.6 M, respectively. We also compare our method with a more elaborate method in the literature, by presenting our results on the computer search for inhibitors of the HIV-1 protease.     

Estimating reaction parameters in mechanism-enabled population balance models of nanoparticle size distributions: A Bayesian inverse problem approach

In order to quantitatively predict nano- as well as other particle-size distributions, one needs to have both a mathematical model and estimates of the parameters that appear in these models. Here, we show how one can use Bayesian inversion to obtain statistical estimates for the parameters that appear in recently derived mechanism-enabled population balance models (ME-PBM) of nanoparticle growth. The Bayesian approach addresses the question of “how well do we know our parameters, along with their uncertainties?.” The results reveal that Bayesian inversion statistical analysis on an example, prototype nanoparticle formation system allows one to estimate not just the most likely rate constants and other parameter values, but also their SDs, confidence intervals, and other statistical information. Moreover, knowing the reliability of the mechanistic model's parameters in turn helps inform one about the reliability of the proposed mechanism, as well as the reliability of its predictions. The paper can also be seen as a tutorial with the additional goal of achieving a “Gold Standard” Bayesian inversion ME-PBM benchmark that others can use as a control to check their own use of this methodology for other systems of interest throughout nature. Overall, the results provide strong support for the hypothesis that there is substantial value in using a Bayesian inversion methodology for parameter estimation in particle formation systems.     

Experimental and Theoretical Studies of a Pulsed Microwave Excited Ar/CF4 Plasma

The present work deals with a pulsed microwave discharge in an Ar/CF ₄ gas mixture under a low pressure (1–10 mbar). The discharge chamber developed has a cylindrical geometry with a coupling window alternatively made of quartz or alumina. The setup allows one to investigate the plasma–wall interactions (here etching of the quartz window) and the ignition process of the pulsed microwave plasma. Microwave pulses with a duration of 50–200 s and repetition rate between 1 and 10 kHz are typical for the experiments. The space-time behavior of the fluorine number density in the discharge has been investigated experimentally by optical actinometry. The discharge kinetics is modeled using electron-transport parameters and rate coefficients derived from solutions of the Boltzmann equation. Together with the solution of the continuity and electron balance equations and the rate equations describing the production of CF _x (x=2, 3, 4) radicals and F atoms, a good agreement between experimental and theoretical data can be achieved.     

Novel aromatic carboxamides from dehydroabietylamine as potential fungicides: Design,synthesis and antifungal evaluation

The present study was carried out to design and synthesize a number of novel aromatic carboxamide derivatives of dehydroabietylamine. The preliminary antifungal assay indicated that most of title compounds displayed moderate to good antifungal activity toward the six fungal strains in vitro. Compounds 3i, 3q, 4b and 4d showed significant antifungal activity against Sclerotinia sclerotiorum, with EC₅₀ values ranging from 0.067 ～ 0.393 mg/L. Compounds 3i, 4b and 4d also showed pronounced mycelial growth inhibition activities against B. cinerea and A. solani. Furthermore, in the in vivo assay, compound 4b exhibited brilliant protective activity against S. sclerotiorum-infected rape leaves. Meanwhile, the in vivo bioassay on tomato plants infected by B. cinerea showed that compound 3i and 4d displayed excellent protective activity at 200 mg/L, which were near to boscalid. Primary mechanistic study revealed that 4b could inhibit sclerotia formation as well as reduce the exopolysaccharide level. SEM and TEM analysis indicated that 4b possessed a strong ability to destroy the surface morphology of mycelia, cell structure and seriously interfere with the growth of the fungal pathogen. In addition, 4b exhibited good inhibitory activity (IC₅₀ = 23.3 ± 1.6 μM) toward succinate dehydrogenase (SDH). Molecular modeling study confirmed the binding modes between compound 4b and SDH. The above antifungal results and fungicidal mechanism study revealed that this class of dehydroabietylamine derivatives could be potential SDH inhibitors and lead compounds for novel fungicides development.     

Recognition of polymer-particle interfacial morphology in mixed matrix membranes through ideal permeation predictive models

Interfacial properties play an important role in determining characteristics and performance of composite materials, especially in membrane gas separation applications. Formation of any undesirable defect at polymer-particle interface can directly influence on membrane permeability and selectivity in addition to unwanted effects on the other mechanical/physical properties. For achieving a quick insight about the role and nature of interfacial morphologies in mixed matrix membranes (MMMs) and their effects on gas transport properties, a new technique mainly in terms of mathematical modeling was developed. Based on the proposed approach, although ideal models often failed in predicting MMMs performance, these models can provide guidelines for discernment of the types of formed interfacial morphology, like current methods in characterization.     

Reverse fragment based drug discovery approach via simple estimation of fragment contributions

1. Download : Download high-res image (110KB)
2. Download : Download full-size image

     

Spatiotemporal model for the progression of transgressive dunes

Transgressive dune fields, which are active sand areas surrounded by vegetation, exist on many coasts. In some regions like in Fraser Island in Australia, small dunes shrink while large ones grow, although both experience the same climatic conditions. We propose a general mathematical model for the spatiotemporal dynamics of vegetation cover on sand dunes and focus on the dynamics of transgressive dunes. Among other possibilities, the model predicts growth parallel to the wind with shrinkage perpendicular to the wind, where, depending on geometry and size, a transgressive dune can initially grow although eventually shrink. The larger is the initial area the slower its stabilization process. The model’s predictions are supported by field observations from Fraser Island in Australia.     

Unsupervised cell identification on multidimensional X‐ray fluorescence datasets

A novel approach to locate, identify and refine positions and whole areas of cell structures based on elemental contents measured by X‐ray fluorescence microscopy is introduced. It is shown that, by initializing with only a handful of prototypical cell regions, this approach can obtain consistent identification of whole cells, even when cells are overlapping, without training by explicit annotation. It is robust both to different measurements on the same sample and to different initializations. This effort provides a versatile framework to identify targeted cellular structures from datasets too complex for manual analysis, like most X‐ray fluorescence microscopy data. Possible future extensions are also discussed.