Journal of Computational Chemistry

Cover image for Vol. 33 Issue 23

5 September 2012

Volume 33, Issue 23

Pages i–iv, 1845–1906

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      Cover Image, Volume 33, Issue 23 (pages i–ii)

      Version of Record online: 14 JUL 2012 | DOI: 10.1002/jcc.23077

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      The site identification by ligand competitive saturation (SILCS) methodology for computational fragmentbased drug design includes explicit molecular solvation and can include full target flexibility, as presented by Theresa J. Foster, Alexander D. MacKerell Jr., and Olgun Guvench on page 1880. This allows for the detection of ‘cryptic’ fragment binding ‘hot-spot’ pockets (green mesh) that are not present in the unliganded target starting structure used to seed a SILCS simulation.

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      Inside Cover, Volume 33, Issue 23 (pages iii–iv)

      Version of Record online: 14 JUL 2012 | DOI: 10.1002/jcc.23078

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      The adsorption of gas phase molecules on transition metal clusters is fundamentally important in basic science and practically vital in new functionality material and devices. On page 1854, J. Wang et al. report both molecularly and dissociated species of N2 and NO adsorbing on different-sized vanadium clusters. The adsorption of the two molecules shows quite different size-dependent behaviors: The adsorption energies for N2 exhibit clear size dependent variations, whereas, for NO, there are only trivial fluctuations; N2 plays an attenuation role on the magnetism, while NO can either reduce or increase the magnetic moment of vanadium clusters.

  2. Full Papers

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    1. Nuclear magnetic resonance J coupling constant polarizabilities of hydrogen peroxide: A basis set and correlation study (pages 1845–1853)

      Hanna Kjær, Monia R. Nielsen, Gabriel I. Pagola, Marta B. Ferraro, Paolo Lazzeretti and Stephan P. A. Sauer

      Version of Record online: 23 MAY 2012 | DOI: 10.1002/jcc.23013

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      The coupling constant polarizability of hydrogen peroxide has been calculated with density functional theory and correlated wavefunction methods. Large basis set and electron correlation effects are observed.

    2. Comparative DFT study of N2 and no adsorption on vanadium clusters Vn (n = 2–13) (pages 1854–1861)

      Guangfen Wu, Mingli Yang, Xingyu Guo and Jinlan Wang

      Version of Record online: 28 MAY 2012 | DOI: 10.1002/jcc.23017

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      The adsorption of N2 and NO on vanadium clusters up to 13 atoms were comparatively investigated. Both molecularly and dissociated species of N2 and NO were found and the adsorption of the two molecules shows quite different size-dependent behaviors. The cluster size, geometry, adsorption sites, and the adsorbate species (N2/NO) jointly determine the reactivity of the adsorption.

    3. Quantum chemical insights into the aggregation induced emission phenomena: A QM/MM study for pyrazine derivatives (pages 1862–1869)

      Qunyan Wu, Chunmei Deng, Qian Peng, Yingli Niu and Zhigang Shuai

      Version of Record online: 23 MAY 2012 | DOI: 10.1002/jcc.23019

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      Using QM/MM approach to investigate the aggregation effects on the radiative and nonradiative decays of the lowest excited state in 2,3-dicyano-5,6-diphenylpyrazine (DCPP) and 2,3-dicyanopyrazino-phenanthrene (DCPP) molecules. We showed that for DCDPP, the nonradiative decay process is strongly hindered by the intermolecular interaction, thus, exhibiting prominent aggregation enhanced light-emitting phenomena, in sharp contrast to the conventional aggregation quenching phenomena as found for its phenyl-locked counterpart DCPP.

    4. Kinetics for the hydrogen-abstraction of CH4 with NO2 (pages 1870–1879)

      Yulei Guan and Bolun Yang

      Version of Record online: 23 MAY 2012 | DOI: 10.1002/jcc.23020

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      The NO2 + CH4 reaction which is important for promoting the ignition of hydrocarbons proceeds by three distinct channels simultaneously, leading to the formation of trans-HONO, cis-HONO, and HNO2, respectively, and each channel involves the formation of intermediate having lower energy than final product. There exists anti-Hammond behavior for intersections of the three potential energy curves, and theoretical analysis is performed to reveal the reasonable explanation. Furthermore, we present direct dynamics calculation for each channel.

    5. Balancing target flexibility and target denaturation in computational fragment-based inhibitor discovery (pages 1880–1891)

      Theresa J. Foster, Alexander D. MacKerell Jr. and Olgun Guvench

      Version of Record online: 28 MAY 2012 | DOI: 10.1002/jcc.23026

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      Site Identification by Ligand Competitive Saturation (SILCS) is a computational method capable of detecting noncrystallographic (cryptic) binding sites through the creation of fragment-binding maps (FragMaps). Here, a SILCS FragMap corresponds with a cryptic binding site in interleukin-2 not present in the apo crystal structure, but seen in crystal structures with bound inhibitors (lines).

    6. Quantum chemical comparison of vertical, adiabatic, and 0-0 excitation energies: The PYP and GFP chromophores (pages 1892–1901)

      Malin Uppsten and Bo Durbeej

      Version of Record online: 28 MAY 2012 | DOI: 10.1002/jcc.23027

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      A variety of quantum chemical methods are used to calculate vertical, adiabatic, and 0-0 excitation energies for the chromophores of the photoactive yellow protein and the green fluorescent protein. As a valuable complement to an existing body of benchmark data mostly concerned with vertical excitation energies, the subsequent analysis then focuses on how the differences between the vertical, adiabatic, and 0-0 excitation energies vary with the choice of quantum chemical method.

  3. Software News and Updates

    1. Top of page
    2. Cover Image
    3. Full Papers
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      Coral: QSPR modeling of rate constants of reactions between organic aromatic pollutants and hydroxyl radical (pages 1902–1906)

      A. A. Toropov, A. P. Toropova, B. F. Rasulev, E. Benfenati, G. Gini, D. Leszczynska and J. Leszczynski

      Version of Record online: 28 MAY 2012 | DOI: 10.1002/jcc.23022

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      The general scheme of detection of the preferable model by means of selection of the threshold (for removing noise molecular attributes) and of the number of epochs of the Monte Carlo optimization.

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