GROMACS: Difference between revisions

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<ref>[http://dx.doi.org/10.1002/jcc.20291 David Van Der Spoel, Erik Lindahl, Berk Hess, Gerrit Groenhof, Alan E. Mark, Herman J. C. Berendsen "GROMACS: Fast, flexible, and free", Journal of Computational Chemistry '''26''' pp. 1701-1718 (2005)]</ref>
<ref>[http://dx.doi.org/10.1002/jcc.20291 David Van Der Spoel, Erik Lindahl, Berk Hess, Gerrit Groenhof, Alan E. Mark, Herman J. C. Berendsen "GROMACS: Fast, flexible, and free", Journal of Computational Chemistry '''26''' pp. 1701-1718 (2005)]</ref>
<ref>[http://dx.doi.org/10.1021/ct700301q Berk Hess, Carsten Kutzner, David van der Spoel and Erik Lindahl "GROMACS 4:  Algorithms for Highly Efficient, Load-Balanced, and Scalable Molecular Simulation", Journal of Chemical Theory and Computation '''4''' pp. 435–447 (2008)]</ref>
<ref>[http://dx.doi.org/10.1021/ct700301q Berk Hess, Carsten Kutzner, David van der Spoel and Erik Lindahl "GROMACS 4:  Algorithms for Highly Efficient, Load-Balanced, and Scalable Molecular Simulation", Journal of Chemical Theory and Computation '''4''' pp. 435–447 (2008)]</ref>
is a versatile package to perform [[molecular dynamics]], i.e. simulate the  
('''GRO'''ningen '''MA'''chine for '''C'''hemical '''S'''imulations) is a versatile package to perform [[molecular dynamics]], i.e. simulate the  
[[Newtons laws |Newtonian equations of motion]] for systems with hundreds to millions of particles.
[[Newtons laws |Newtonian equations of motion]] for systems with hundreds to millions of particles.
GROMACS is primarily designed for [[Biological systems |biochemical molecules]] like [[proteins]] and [[lipids]] that have a lot of complicated bonded interactions, but since GROMACS is extremely fast at calculating the non-bonded interactions (that usually dominate simulations) many groups are also using it for research on non-biological systems, e.g. [[polymers]].
GROMACS is primarily designed for [[Biological systems |biochemical molecules]] like [[proteins]] and [[lipids]] that have a lot of complicated bonded interactions, but since GROMACS is extremely fast at calculating the non-bonded interactions (that usually dominate simulations) many groups are also using it for research on non-biological systems, e.g. [[polymers]].
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==Constraint algorithms==
==Constraint algorithms==
GROMACS can use either the [[SHAKE]] or the [[LINCS]] algorithms <ref>[http://www.gromacs.org/@api/deki/files/82/=gromacs4_manual.pdf GROMACS 4 Manual] &sect; 3.6 </ref>.
GROMACS can use either the [[SHAKE]] or the [[LINCS]] algorithms <ref>[http://www.gromacs.org/@api/deki/files/82/=gromacs4_manual.pdf GROMACS 4 Manual] &sect; 3.6 </ref>.
==Force fields==
GROMACS comes with the following [[force fields]] <ref>Source: /usr/share/gromacs/top for gromacs-4.5.5 </ref><ref>GROMACS 4.5.6 manual &sect; 4.10 </ref>
* [[AMBER forcefield | AMBER]]
** amber03
** amber94 <ref>[http://dx.doi.org/10.1021/ja00124a002 Wendy D. Cornell , Piotr Cieplak , Christopher I. Bayly , Ian R. Gould , Kenneth M. Merz , David M. Ferguson , David C. Spellmeyer , Thomas Fox , James W. Caldwell , Peter A. Kollman "A Second Generation Force Field for the Simulation of Proteins, Nucleic Acids, and Organic Molecules", Journal of the American Chemical Society (JACS) '''117''' pp. 5179-5197 (1995)]</ref>
** amber96
** amber99
** amber99sb
** amber99sb-ildn
** amberGS <ref>[http://dx.doi.org/10.1073/pnas.042496899 Angel E. García and Kevin Y. Sanbonmatsu "α-Helical stabilization by side chain shielding of backbone hydrogen bonds", PNAS '''99''' pp. 2782-2787 (2002)]</ref>
*[[CHARMM]]
** charmm27
*[[ENCAD (force field) | ENCAD]]
** encads (full solvent charges)
** encadv (scaled-down vacuum charges)
*[[GROMOS]]
** gromos43a1
** gromos43a2
** gromos45a3
** gromos53a5
** gromos53a6
*[[MARTINI]]
*[[OPLS force field | OPLS-all atom]]
==References==
==References==
<references/>
<references/>

Latest revision as of 14:30, 14 October 2021

GROMACS [1] [2] [3] (GROningen MAchine for Chemical Simulations) is a versatile package to perform molecular dynamics, i.e. simulate the Newtonian equations of motion for systems with hundreds to millions of particles. GROMACS is primarily designed for biochemical molecules like proteins and lipids that have a lot of complicated bonded interactions, but since GROMACS is extremely fast at calculating the non-bonded interactions (that usually dominate simulations) many groups are also using it for research on non-biological systems, e.g. polymers.

GROMACS on Tesla GPUs[edit]

The CUDA port of GROMACS enabling GPU acceleration is now available in beta and supports Particle-Mesh-Ewald, arbitrary forms of non-bonded interactions, and implicit solvent Generalized Born methods [4]

Constraint algorithms[edit]

GROMACS can use either the SHAKE or the LINCS algorithms [5].

Force fields[edit]

GROMACS comes with the following force fields [6][7]

  • AMBER
    • amber03
    • amber94 [8]
    • amber96
    • amber99
    • amber99sb
    • amber99sb-ildn
    • amberGS [9]

References[edit]

External links[edit]