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Journal Of Computational Chemistry

Print ISSN
0192-8651
Electronic ISSN
1096-987X
Impact factor
4.05
Publisher
wiley
URL
http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1096-987X
Usage rank
449
Article count
2537
Free count
89
Free percentage
0.0350808
PDFs via platforms
Wiley from 1980

  1. Nature of the water/aromatic parallel alignment interactions.

    Journal Of Computational Chemistry 36(3):171 (2015) PMID 25393085

    The water/aromatic parallel alignment interactions are interactions where the water molecule or one of its OH bonds is parallel to the aromatic ring plane. The calculated energies of the interactions are significant, up to ΔECCSD(T)(limit) = -2.45 kcal mol(-1) at large horizontal displacement, out...
  2. Cover image, volume 35, issue 28.
    Author(s) unavailable

    Journal Of Computational Chemistry 35(28):iii (2014) PMID 25243934

    On page 2070 (DOI: 10.1002/jcc.23733), Martin Andersson and Susan L. S. Stipp report the prediction of the free energy of hydration for 40 mono- and multivalent cations and anions using density functional theory and the implicit solvent model COSMO-RS. No significant systematic errors for mono- and...
  3. Cover image, volume 33, issue 26.
    Author(s) unavailable

    Journal Of Computational Chemistry 33(26):i (2012) PMID 22961766

    A HOBDI (4-hydroxybenzylidene-1,2-dimethylimidazolinone) solute molecule in aqueous solution was used as one of the test systems to validate the newly implemented quantum-chemical/molecular-mechanical (QM/MM) functionality of the GROMOS (Groningen Molecular Simulation) software for (...
  4. Inside cover, volume 33, issue 24.
    Author(s) unavailable

    Journal Of Computational Chemistry 33(24):iii (2012) PMID 22865278

    As presented by Chuan Li, Lin Li, Jie Zhang, and Emil Alexov on page 1960, the image shows the distribution of electrostatic field mapped onto the surface of the adeno-associated virus, PDB ID 3KIC. The structural file, after a standard protonation, contains approximately 484,500 ato...
  5. Automatic analysis of computed catalytic cycles.

    Journal Of Computational Chemistry 32(5):978 (2011) PMID 21077208

    We present the AUTOF program that allows the user to apply the complete model in a black box fashion. © 2010 Wiley Periodicals, Inc. J Comput Chem, 2011. Copyright © 2010 Wiley Periodicals, Inc....
  6. Melting of icosahedral nickel clusters under hydrostatic pressure.

    Journal Of Computational Chemistry 35(31):2231 (2014) PMID 25241855

    The thermal stabilities and melting behavior of icosahedral nickel clusters under hydrostatic pressure have been studied by constant-pressure molecular dynamics simulation. The potential energy and Lindemann index are calculated. The overall melting temperature exhibits a strong dependence on pressu...
  7. Bayesian inference of conformational state populations from computational models and sparse experimental observables.

    Journal Of Computational Chemistry 35(30):2215 (2014) PMID 25250719

    We present a Bayesian inference approach to estimating conformational state populations from a combination of molecular modeling and sparse experimental data. Unlike alternative approaches, our method is designed for use with small molecules and emphasizes high-resolution structural models, using in...
  8. Using operators to expand the block matrices forming the Hessian of a molecular potential.

    Journal Of Computational Chemistry 35(15):1149 (2014) PMID 24740591

    We derive compact expressions of the second-order derivatives of bond length, bond angle, and proper and improper torsion angle potentials, in terms of operators represented in two orthonormal bases. Hereby, simple rules to generate the Hessian of an internal coordinate or a molecular potential can...
  9. Assessment of the orbital-optimized coupled-electron pair theory for thermochemistry and kinetics: improving on CCSD and CEPA(1).

    Journal Of Computational Chemistry 35(14):1073 (2014) PMID 24668486

    We conclude that the OCEPA(0) method is quite helpful not only for problematic open-shell systems and transition-states but also for closed-shell molecules. Hence, one may prefer OCEPA(0) over CEPA(0), CEPA(1), and CCSD as an O(N6) method, where N is the number of basis functions, for thermochemistr...
  10. A Bayesian statistical approach of improving knowledge-based scoring functions for protein-ligand interactions.

    Journal Of Computational Chemistry 35(12):932 (2014) PMID 24623011

    We have developed a novel approach for handling the sparse data problem that is based on estimating the inaccuracies in knowledge-based scoring functions. This inaccuracy estimation is used to automatically weight the knowledge-based scoring function with an alternative, force-field-based potential...