Journal of Computational Chemistry

Cover image for Vol. 36 Issue 2

Edited By: Charles L. Brooks III, Masahiro Ehara, Gernot Frenking, and Peter R. Schreiner

Impact Factor: 3.601

ISI Journal Citation Reports © Ranking: 2013: 36/148 (Chemistry Multidisciplinary)

Online ISSN: 1096-987X

Associated Title(s): International Journal of Quantum Chemistry, Wiley Interdisciplinary Reviews: Computational Molecular Science

Virtual Issues

CHARMM and the Development of Methods and Techniques in Molecular Mechanics, August 2009

Edited by Charles L. Brooks III and Martin Karplus

CHARMM (Chemistry at HARvard Macromolecular Mechanics) is one of the oldest–established and best–known software programs used for the study of molecular dynamics. It is also the name of a widely used set of force fields for molecular dynamics.

CHARMM facilitates the generation and analysis of a wide range of molecular simulations, and has accumulated a huge number of features. More advanced features include free energy perturbation (FEP), quasi–harmonic entropy estimation, correlation analysis and combined quantum, and molecular mechanics (QM/MM) methods.

Journal of Computational Chemistry is proud to present the CHARMM related papers below.

CHARMM: The biomolecular simulation program
B. R. Brooks, C. L. Brooks III, A. D. Mackerell Jr., L. Nilsson, R. J. Petrella, B. Roux, Y. Won, G. Archontis, C. Bartels, S. Boresch, A. Caflisch, L. Caves, Q. Cui, A. R. Dinner, M. Feig, S. Fischer, J. Gao, M. Hodoscek, W. Im, K. Kuczera, T. Lazaridis, J. Ma, V. Ovchinnikov, E. Paci, R. W. Pastor, C. B. Post, J. Z. Pu, M. Schaefer, B. Tidor, R. M. Venable, H. L. Woodcock, X. Wu, W. Yang, D. M. York and M. Karplus
Journal of Computational Chemistry, 2009, 30(10), 1545–1614
DOI: 10.1002/polb.10.1002/jcc.21287

CHARMM: A program for macromolecular energy, minimization, and dynamics calculations
Bernard R. Brooks, Robert E. Bruccoleri, Barry D. Olafson, David J. States, S. Swaminathan and Martin Karplus
Journal of Computational Chemistry, 1983, 4(2), 187–217
DOI: 10.1002/jcc.540040211

CHARMM–GUI: A web–based graphical user interface for CHARMM
Sunhwan Jo, Taehoon Kim, Vidyashankara G. Iyer and Wonpil Im
Journal of Computational Chemistry, 2008, 29(11), 1859–1865
DOI: 10.1002/jcc.20945

A combined quantum mechanical and molecular mechanical potential for molecular dynamics simulations
Martin J. Field, Paul A. Bash and Martin Karplus
Journal of Computational Chemistry, 1990, 11(6), 700–733
DOI: 10.1002/jcc.540110605

Harmonic analysis of large systems. I. Methodology
Bernard R. Brooks, Dušanka Janežič and Martin Karplus
Journal of Computational Chemistry, 1995, 16(12), 1522–1542
DOI: 10.1002/jcc.540161209

Multidimensional adaptive umbrella sampling: Applications to main chain and side chain peptide conformations
Christian Bartels and Martin Karplus
Journal of Computational Chemistry, 1997, 18(12), 1450–1462
DOI: 10.1002/(SICI)1096-987X(199709)18:12<1450::AID-JCC3>3.0.CO;2-I

Docking by Monte Carlo minimization with a solvation correction: Application to an FKBP–substrate complex
Amedeo Caflisch, Stefan Fischer and Martin Karplus
Journal of Computational Chemistry, 1997, 18(6), 723–743
DOI: 10.1002/(SICI)1096-987X(19970430)18:6<723::AID-JCC1>3.0.CO;2-U>3.0.CO;2-U

Monte Carlo simulations of biomolecules: The MC module in CHARMM
Jie Hu, Ao Ma and Aaron R. Dinner
Journal of Computational Chemistry, 2006, 27(2), 203–216
DOI: 10.1002/jcc.20327

Interfacing Q–Chem and CHARMM to perform QM/MM reaction path calculations
H. Lee Woodcock III, Milan Hodošček, Andrew T. B. Gilbert, Peter M. W. Gill, Henry F. Schaefer III and Bernard R. Brooks
Journal of Computational Chemistry, 2007, 28(9), 1485–1502
DOI: 10.1002/jcc.20587

Empirical energy functions for energy minimization and dynamics of nucleic acids
Lennart Nilsson and Martin Karplus
Journal of Computational Chemistry, 1986, 7(5), 591–616
DOI: 10.1002/jcc.540070502

Extending the treatment of backbone energetics in protein force fields: Limitations of gas–phase quantum mechanics in reproducing protein conformational distributions in molecular dynamics simulations
Alexander D. Mackerell Jr., Michael Feig and Charles L. Brooks III
Journal of Computational Chemistry, 2004, 25(11), 1400–1415
DOI: 10.1002/jcc.20065

Additive empirical force field for hexopyranose monosaccharides
Olgun Guvench, Shannon N. Greene, Ganesh Kamath, John W. Brady, Richard M. Venable, Richard W. Pastor and Alexander D. Mackerell Jr
Journal of Computational Chemistry, 2004, 29(15), 2543–2564
DOI: 10.1002/jcc.21004

CHARMM general force field: A force field for drug–like molecules compatible with the CHARMM all–atom additive biological force fields
K. Vanommeslaeghe, E. Hatcher, C. Acharya, S. Kundu, S. Zhong, J. Shim, E. Darian, O. Guvench, P. Lopes, I. Vorobyov and A. D. Mackerell Jr.
Journal of Computational Chemistry, 2010, 31(4), 671–690
DOI: 10.1002/jcc.21367

CHARMM fluctuating charge force field for proteins: I parameterization and application to bulk organic liquid simulations
Sandeep Patel and Charles L. Brooks III
Journal of Computational Chemistry, 2004, 25(1), 1–16
DOI: 10.1002/jcc.10355

CHARMM fluctuating charge force field for proteins: II Protein/solvent properties from molecular dynamics simulations using a nonadditive electrostatic model
Sandeep Patel, Alexander D. Mackerell Jr. and Charles L. Brooks III
Journal of Computational Chemistry, 2004, 25(12), 1504–1514
DOI: 10.1002/jcc.20077