Running Molecular Dynamics on Alliance clusters with AMBER: Glossary

Key Points

An Overview of Information Flow in AMBER
  • To run an MD simulation with AMBER 3 files are needed: an input file, a parameter file, and a file describing coordinates/velocities .

Checking and Preparing PDB Files
  • Small errors in the input structure may cause MD simulations to became unstable or give unrealistic results.

Assigning Protonation States to Residues in a Protein
  • Assigning correct protonation states of aminoacids in proteins is crucial for realistic MD simulations

  • Conformational changes in proteins may be accompanied by changes in protonation pattern.

Solvating a System, Adding Ions and Generating Input Files
  • Simulation system must be neutralized by adding counter-ions to obtain the correct electrostatic energy.

  • Ions are added to a simulations system to mimic composition of a local macromolecule environment.

  • Solvent box should be large enough to allow for unrestricted conformational dynamics of a macromolecule.

Running Molecular Dynamics Simulations with AMBER
Preparation and simulation of membrane and membrane-protein systems
Hands-on 1: Packing a complex mixture of different lipid species into a bilayer and simulating it
Hands-on 2: Transferring AMBER simulation to GROMACS
Hands-on 3A: Preparing a Complex RNA-protein System
  • ?

Hands-on 3B: Simulating a Complex RNA-protein System
Hands-on 4: Preparing a system for simulation with GROMACS
Hands-on 5: Generating topologies and parameters for small molecules.
Hands-on 6: A Comparative Performance Ranking of the Molecular Dynamics Software
  • To assess CPU efficiency, you need to know how fast a serial simulation runs

Glossary

FIXME

barostat
Pressure control algorithms in molecular dynamics (MD) simulations are commonly referred to as barostats and are needed to study isobaric systems. Barostats work by altering the size of the simulation box. Therefore they can only be used in conjunction with periodic boundary conditions (PBC).
ergodicity
In statistical mechanics ergodicity describes the principle that studying a single particle averaged over a long time is equivalent to averaging over many particles which are studied for a short time. See also: “Ergodicity” on Wikipedia
periodic boundary conditions
Periodic boundary conditions (PBC) … See also:
thermostat
Temperature control algorithms in molecular dynamics (MD) simulations are commonly referred to as thermostats and are needed to study isothermal systems. Thermostats work by altering the velocities of particles.

Bibliography

Ahmed-2010
Ahmed A, Sadus RJ.
Effect of potential truncations and shifts on the solid-liquid phase coexistence of Lennard-Jones fluids.
J Chem Phys. 2010;133: 124515. doi:10.1063/1.3481102
Allen-2017
Allen MP, Tildesley DJ.
Computer Simulation of Liquids. Second Edition
Oxford University Press; 2017. ISBN: 9780198803195 doi:10.1093/oso/9780198803195.001.0001
Andersen-1980
Andersen HC.
Molecular dynamics simulations at constant pressure and/or temperature.
J Chem Phys. 1980;72: 2384–2393. doi:10.1063/1.439486
Basconi-2013
Basconi JE, Shirts MR.
Effects of Temperature Control Algorithms on Transport Properties and Kinetics in Molecular Dynamics Simulations.
J Chem Theory Comput. 2013;9: 2887–2899. doi:10.1021/ct400109a
Berendsen-1984
Berendsen HJC, Postma JPM, van Gunsteren WF, DiNola A, Haak JR.
Molecular dynamics with coupling to an external bath.
J Chem Phys. $abstract.copyright_name.value; 1984;81: 3684–90. doi:10.1063/1.448118
Braun-2019
Braun E, Gilmer J, Mayes HB, Mobley DL, Monroe JI, Prasad S, et al.
Best Practices for Foundations in Molecular Simulations [Article v1.0].
Living J Comput Mol Sci. 2019;1: 1–28. doi:10.33011/livecoms.1.1.5957
Bussi-2007
Bussi G, Donadio D, Parrinello M.
Canonical sampling through velocity rescaling.
J Chem Phys. 2007;126: 014101. doi:10.1063/1.2408420
Dauber-Osguthorpe-2018
Dauber-Osguthorpe P, Hagler AT.
Biomolecular force fields: where have we been, where are we now, where do we need to go and how do we get there?
Journal of Computer-Aided Molecular Design. 2019;33: 133–203. doi:10.1007/s10822-018-0111-4
Grosfils-2009
Grosfils P, Lutsko JF.
Dependence of the liquid-vapor surface tension on the range of interaction: a test of the law of corresponding states.
J Chem Phys. 2009;130: 054703. doi:10.1063/1.3072156
Hagler-2019
Hagler AT.
Force field development phase II: Relaxation of physics-based criteria… or inclusion of more rigorous physics into the representation of molecular energetics.
J Comput Aided Mol Des. 2019;33: 205–264. doi:10.1007/s10822-018-0134-x
Hoover-1985
Hoover WG.
Canonical dynamics: Equilibrium phase-space distributions.
Phys Rev A. APS; 1985;31: 1695–1697. doi:10.1103/PhysRevA.31.1695
Huang-2014
Huang K, García AE.
Effects of truncating van der Waals interactions in lipid bilayer simulations.
Journal of Chemical Physics. 2014;141. doi:10.1063/1.4893965
Koopman-2006
Koopman EA, Lowe CP.
Advantages of a Lowe-Andersen thermostat in molecular dynamics simulations.
J Chem Phys. 2006;124: 1–6. doi:10.1063/1.2198824
Larsson-2011
Larsson P, Hess B, Lindahl E.
Algorithm improvements for molecular dynamics simulations.
Wiley Interdiscip Rev Comput Mol Sci. 2011;1: 93–108. doi:10.1002/wcms.3
Lifson-1968
Lifson S, Warshel A.
Consistent Force Field for Calculations of Conformations, Vibrational Spectra, and Enthalpies of Cycloalkane and n‐Alkane Molecules.
J Chem Phys. 1968;49: 5116–5129. doi:10.1063/1.1670007
Martyna-1992
Martyna GJ, Klein ML, Tuckerman M.
Nosé–Hoover chains: The canonical ensemble via continuous dynamics.
J Chem Phys. 1992;97: 2635–2643. doi:10.1063/1.463940
Nose-1984
Nosé S.
A molecular dynamics method for simulations in the canonical ensemble.
Mol Phys. 1984;52: 255–268. doi:10.1080/00268978400101201
Piana-2012
Piana S, Lindorff-Larsen K, Dirks RM, Salmon JK, Dror RO, Shaw DE.
Evaluating the Effects of Cutoffs and Treatment of Long-range Electrostatics in Protein Folding Simulations.
PLOS ONE. 2012;7: e39918. doi:10.1371/journal.pone.0039918
Shirts-2013
Shirts MR.
Simple Quantitative Tests to Validate Sampling from Thermodynamic Ensembles.
J Chem Theory Comput. 2013;9: 909–926. doi:10.1021/ct300688p
Verlet-1967
Verlet L. Computer “Experiments” on Classical Fluids. I.
Thermodynamical Properties of Lennard-Jones Molecules.
Phys Rev. 1967;159: 98–103. doi:10.1103/PhysRev.159.98
Winger-2009
Winger M, Trzesniak D, Baron R, van Gunsteren WF.
On using a too large integration time step in molecular dynamics simulations of coarse-grained molecular models.
Phys Chem Chem Phys. 2009;11: 1934–1941. doi:10.1039/b818713d
Wong-ekkabut-2016
Wong-ekkabut J, Karttunen M.
The good, the bad and the user in soft matter simulations.
Biochim Biophys Acta - Biomembr. Elsevier B.V.; 2016;1858: 2529–2538. doi:10.1016/j.bbamem.2016.02.004
Yonetani-2006
Yonetani Y.
Liquid water simulation: A critical examination of cutoff length.
Journal of Chemical Physics. 2006;124. doi:10.1063/1.2198208