Journal of Computational Chemistry

Cover image for Vol. 35 Issue 12

5 May 2014

Volume 35, Issue 12

Pages i–vi, 891–963

  1. Cover Image

    1. Top of page
    2. Cover Image
    3. Full Papers
    4. Software News and Updates
    1. You have free access to this content
      Cover Image, Volume 35, Issue 12 (pages i–ii)

      Article first published online: 2 APR 2014 | DOI: 10.1002/jcc.23600

      Thumbnail image of graphical abstract

      On page 932 (DOI: 10.1002/jcc.23579), Sam Z. Grinter and Xiaoqin Zou introduce a new method of handing the sparse data problem in knowledge-based scoring functions and present the approach in a scoring function called STScore. This Bayesian statistical approach, though presented in the context of protein-ligand docking, may be used with other knowledge-based scoring functions for protein-protein docking and protein structure prediction. The cover compares the native binding mode of PDB:2cgr, correctly identified by STScore, with the binding mode predicted by a rudimentary potential of mean force. The cover also shows three example curves for the probability density function used in the derivation of STScore.

    2. You have free access to this content
      Cover Image, Volume 35, Issue 12 (pages iii–iv)

      Article first published online: 2 APR 2014 | DOI: 10.1002/jcc.23601

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      Density functional theory calculations are performed to construct the potential energy surface for the H2 release from ammonia-borane, with a novel bifunctional cationic ruthenium catalyst (1) based on the sterically bulky α-diketiminato ligand. On page 891 (DOI: 10.1002/jcc.23534), Sateesh Bandaru et al. accurately model the dehydrogenation step (rate-limiting), considering a selection of explicit protic solvent molecules, with the goal of lowering energy barriers for the H-H recombination. They find that tertiary (3°) alcohols are most suitable for enhancing the reaction rate.

    3. You have free access to this content
      Cover Image, Volume 35, Issue 12 (pages v–vi)

      Article first published online: 2 APR 2014 | DOI: 10.1002/jcc.23602

      Thumbnail image of graphical abstract

      The ST-analyzer is a standalone graphical user interface toolset used to perform molecular dynamics (MD) simulation trajectory analyses. Its unique implementation scheme and intuitive user interfaces are designed to reduce the user's learning curve and maximize software flexibility. The embedded database and quick search engine help users maintain both submitted and ongoing jobs. In addition to validated built-in modules, the ST-analyzer supports a range of computing sources that include personal computers, community-wide cluster machines, multiple operating systems, and MD simulation programs. The ST-analyzer, presented by Jong Cheol Jeong et al. on page 957 (DOI: 10.1002/jcc.23584), can be freely downloaded from http://im.bioinformatics.ku.edu/ST-analyzer.

  2. Full Papers

    1. Top of page
    2. Cover Image
    3. Full Papers
    4. Software News and Updates
    1. Towards the design of novel boron- and nitrogen-substituted ammonia-borane and bifunctional arene ruthenium catalysts for hydrogen storage (pages 891–903)

      Sateesh Bandaru, Niall J. English, Andrew D. Phillips and J.M.D. MacElroy

      Article first published online: 5 FEB 2014 | DOI: 10.1002/jcc.23534

      Thumbnail image of graphical abstract

      DFT calculations are performed to construct the potential energy surface for the H2 release from ammonia borane, with a novel ruthenium. To model dehydrogenation, a selection of explicit protic solvent molecules is considered, lowering energy barriers for the H-H recombination. Tertiary alcohols are shown to be the most suitable for enhancing the reaction rate.

    2. Exchange coupling and magnetic anisotropy in a family of bipyrimidyl radical-bridged dilanthanide complexes: Density functional theory and ab initio calculations (pages 904–909)

      Yi-Quan Zhang, Cheng-Lin Luo and Qiang Zhang

      Article first published online: 19 FEB 2014 | DOI: 10.1002/jcc.23565

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      DFT and ab initio calculations show that both the intramolecular coupling interaction and the single-ion anisotropy make important contributions to the full relaxation barriers of a series of 2,2′-bipyrimidine (bpym) radical-bridged dilanthanide complexes.

    3. Cooperativity and cluster growth patterns in acetonitrile: A DFT study (pages 910–922)

      Karunakaran Remya and Cherumuttathu H. Suresh

      Article first published online: 9 MAR 2014 | DOI: 10.1002/jcc.23575

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      Among several growth patterns of the acetonitrile cluster, the “stacked” pattern shows the highest interaction energy through the maximum cooperativity in CH···N and dipolar interactions. The results are further corroborated by the theory of atoms in molecules, the analysis of molecular electrostatic potential, and vibrational frequency analyses. A stacked hexadecamer pattern is significantly more stable than the two known crystal patterns of acetonitrile.

    4. Metalophilic interaction in gold halide: Quantum chemical study of AuX (X = F[BOND]at) (pages 923–931)

      Xinying Li

      Article first published online: 4 MAR 2014 | DOI: 10.1002/jcc.23577

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      A theoretical investigation of the metalophilic interaction in AuX (X = F[BOND]At) series at the CCSD(T) theoretical level with extended basis sets reveals their structures and stabilities. Insights into the nature of the gold–halide metalophilic interaction are obtained. Natural bond orbital and topological analyses of the Laplacian, electron density deformation, integrated charge transfer, electron localization function, bond critical point properties, and reduced density gradient are performed to explore the nature of the gold–halogen atom interaction.

      Corrected by:

      Erratum: Metalophilic interaction in gold halide: Quantum chemical study of AuX (X=F-At)

      Vol. 35, Issue 22, 1664, Article first published online: 3 JUL 2014

    5. A Bayesian statistical approach of improving knowledge-based scoring functions for protein–ligand interactions (pages 932–943)

      Sam Z. Grinter and Xiaoqin Zou

      Article first published online: 13 MAR 2014 | DOI: 10.1002/jcc.23579

      Thumbnail image of graphical abstract

      A new method deals with the sparse data problem faced by knowledge-based scoring functions that are commonly used for protein–ligand interactions, protein–protein interactions, and protein structure predictions. A Bayesian statistical approach is used to estimate the contribution of sparse data to inaccuracies in knowledge-based scoring functions. These error estimates can then be used to automatically weight the knowledge-based scoring function with an alternative, force-field-based potential in a consensus framework. This allows the inclusion of sparse atompair types and distances, while minimizing their inaccuracies.

    6. How much tetraradical character is present in the Si6Ge9 cluster? (pages 944–949)

      David Casanova

      Article first published online: 4 MAR 2014 | DOI: 10.1002/jcc.23580

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      This article explores the tetraradical character of the Si6Ge9 cluster in a stable spirobis(pentagerma[1.1.1]propellane) derivative by means of electronic structure calculations of the ground and low-lying states.

  3. Software News and Updates

    1. Top of page
    2. Cover Image
    3. Full Papers
    4. Software News and Updates
    1. Rapid determination of RMSDs corresponding to macromolecular rigid body motions (pages 950–956)

      Petr Popov and Sergei Grudinin

      Article first published online: 24 FEB 2014 | DOI: 10.1002/jcc.23569

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      Finding the root mean square deviations (RMSDs) between two coordinate vectors that correspond to the rigid body motion of a macromolecule is an important problem in structural bioinformatics. A new algorithm determines a set of RMSDs corresponding to a set of rigid body motions of a macromolecule in constant time with respect to the number of atoms in the molecule. This algorithm is particularly useful for rigid body docking applications and for high-throughput analysis of rigid body modeling and simulation results.

    2. ST-analyzer: A web-based user interface for simulation trajectory analysis (pages 957–963)

      Jong Cheol Jeong, Sunhwan Jo, Emilia L. Wu, Yifei Qi, Viviana Monje-Galvan, Min Sun Yeom, Lev Gorenstein, Feng Chen, Jeffery B. Klauda and Wonpil Im

      Article first published online: 17 MAR 2014 | DOI: 10.1002/jcc.23584

      Thumbnail image of graphical abstract

      The ST-analyzer, http://im.bioinformatics.ku.edu/st-analyzer, is a standalone graphical user interface toolset used to perform various simulation trajectory analyses.

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