NAME¶
make_edi - generate input files for essential dynamics sampling
VERSION 4.5.4-dev-20110404-bc5695c
SYNOPSIS¶
make_edi -f eigenvec.trr -eig eigenval.xvg
-s topol.tpr -n index.ndx -tar
target.gro -ori origin.gro -o sam.edi
-[no]h -[no]version -nice int
-xvg enum -mon string -linfix string
-linacc string -radfix string
-radacc string -radcon string -flood
string -outfrq int -slope real
-linstep string -accdir string
-radstep real -maxedsteps int -eqsteps
int -deltaF0 real -deltaF real
-tau real -Eflnull real -T real
-alpha real -[no]restrain
-[no]hessian -[no]harmonic -constF
string
DESCRIPTION¶
make_edi generates an essential dynamics (ED) sampling input file to be
used with
mdrun based on eigenvectors of a covariance matrix (
g_covar) or from a normal modes anaysis (
g_nmeig). ED sampling
can be used to manipulate the position along collective coordinates
(eigenvectors) of (biological) macromolecules during a simulation.
Particularly, it may be used to enhance the sampling efficiency of MD
simulations by stimulating the system to explore new regions along these
collective coordinates. A number of different algorithms are implemented to
drive the system along the eigenvectors (
-linfix,
-linacc,
-radfix,
-radacc,
-radcon), to keep the position along
a certain (set of) coordinate(s) fixed (
-linfix), or to only monitor
the projections of the positions onto these coordinates (
-mon).
References:
A. Amadei, A.B.M. Linssen, B.L. de Groot, D.M.F. van Aalten and H.J.C.
Berendsen; An efficient method for sampling the essential subspace of
proteins., J. Biomol. Struct. Dyn. 13:615-626 (1996)
B.L. de Groot, A. Amadei, D.M.F. van Aalten and H.J.C. Berendsen; Towards an
exhaustive sampling of the configurational spaces of the two forms of the
peptide hormone guanylin, J. Biomol. Struct. Dyn. 13 : 741-751 (1996)
B.L. de Groot, A.Amadei, R.M. Scheek, N.A.J. van Nuland and H.J.C. Berendsen; An
extended sampling of the configurational space of HPr from E. coli Proteins:
Struct. Funct. Gen. 26: 314-322 (1996)
You will be prompted for one or more index groups that correspond to the
eigenvectors, reference structure, target positions, etc.
-mon: monitor projections of the coordinates onto selected eigenvectors.
-linfix: perform fixed-step linear expansion along selected
eigenvectors.
-linacc: perform acceptance linear expansion along selected
eigenvectors. (steps in the desired directions will be accepted, others will
be rejected).
-radfix: perform fixed-step radius expansion along selected
eigenvectors.
-radacc: perform acceptance radius expansion along selected
eigenvectors. (steps in the desired direction will be accepted, others will be
rejected).
Note: by default the starting MD structure will be taken as
origin of the first expansion cycle for radius expansion. If
-ori is
specified, you will be able to read in a structure file that defines an
external origin.
-radcon: perform acceptance radius contraction along selected
eigenvectors towards a target structure specified with
-tar.
NOTE: each eigenvector can be selected only once.
-outfrq: frequency (in steps) of writing out projections etc. to
.edo file
-slope: minimal slope in acceptance radius expansion. A new expansion
cycle will be started if the spontaneous increase of the radius (in nm/step)
is less than the value specified.
-maxedsteps: maximum number of steps per cycle in radius expansion
before a new cycle is started.
Note on the parallel implementation: since ED sampling is a 'global' thing
(collective coordinates etc.), at least on the 'protein' side, ED sampling is
not very parallel-friendly from an implentation point of view. Because
parallel ED requires some extra communication, expect the performance to be
lower as in a free MD simulation, especially on a large number of nodes.
All output of
mdrun (specify with
-eo) is written to a .edo
file. In the output file, per OUTFRQ step the following information is
present:
* the step number
* the number of the ED dataset. (
Note that you can impose
multiple ED constraints in a single simulation (on different molecules) if
several
.edi files were concatenated first. The constraints are
applied in the order they appear in the
.edi file.)
* RMSD (for atoms involved in fitting prior to calculating the ED
constraints)
* projections of the positions onto selected eigenvectors
FLOODING:
with
-flood, you can specify which eigenvectors are used to compute a
flooding potential, which will lead to extra forces expelling the structure
out of the region described by the covariance matrix. If you switch -restrain
the potential is inverted and the structure is kept in that region.
The origin is normally the average structure stored in the
eigvec.trr
file. It can be changed with
-ori to an arbitrary position in
configurational space. With
-tau,
-deltaF0, and
-Eflnull you control the flooding behaviour. Efl is the flooding strength,
it is updated according to the rule of adaptive flooding. Tau is the time
constant of adaptive flooding, high tau means slow adaption (i.e. growth).
DeltaF0 is the flooding strength you want to reach after tau ps of simulation.
To use constant Efl set
-tau to zero.
-alpha is a fudge parameter to control the width of the flooding
potential. A value of 2 has been found to give good results for most standard
cases in flooding of proteins. alpha basically accounts for incomplete
sampling, if you sampled further the width of the ensemble would increase,
this is mimicked by alpha 1. For restraining, alpha 1 can give you smaller
width in the restraining potential.
RESTART and FLOODING: If you want to restart a crashed flooding simulation
please find the values deltaF and Efl in the output file and manually put them
into the
.edi file under DELTA_F0 and EFL_NULL.
FILES¶
-f eigenvec.trr Input
Full precision trajectory: trr trj cpt
-eig eigenval.xvg Input, Opt.
xvgr/xmgr file
-s topol.tpr Input
Structure+mass(db): tpr tpb tpa gro g96 pdb
-n index.ndx Input, Opt.
Index file
-tar target.gro Input, Opt.
Structure file: gro g96 pdb tpr etc.
-ori origin.gro Input, Opt.
Structure file: gro g96 pdb tpr etc.
-o sam.edi Output
ED sampling input
OTHER OPTIONS¶
-[no]hno
Print help info and quit
-[no]versionno
Print version info and quit
-nice int 0
Set the nicelevel
-xvg enum xmgrace
xvg plot formatting:
xmgrace,
xmgr or
none
-mon string
Indices of eigenvectors for projections of x (e.g. 1,2-5,9) or 1-100:10 means 1
11 21 31 ... 91
-linfix string
Indices of eigenvectors for fixed increment linear sampling
-linacc string
Indices of eigenvectors for acceptance linear sampling
-radfix string
Indices of eigenvectors for fixed increment radius expansion
-radacc string
Indices of eigenvectors for acceptance radius expansion
-radcon string
Indices of eigenvectors for acceptance radius contraction
-flood string
Indices of eigenvectors for flooding
-outfrq int 100
Freqency (in steps) of writing output in
.edo file
-slope real 0
Minimal slope in acceptance radius expansion
-linstep string
Stepsizes (nm/step) for fixed increment linear sampling (put in quotes!
"1.0 2.3 5.1 -3.1")
-accdir string
Directions for acceptance linear sampling - only sign counts! (put in quotes!
"-1 +1 -1.1")
-radstep real 0
Stepsize (nm/step) for fixed increment radius expansion
-maxedsteps int 0
Maximum number of steps per cycle
-eqsteps int 0
Number of steps to run without any perturbations
-deltaF0 real 150
Target destabilization energy for flooding
-deltaF real 0
Start deltaF with this parameter - default 0, nonzero values only needed for
restart
-tau real 0.1
Coupling constant for adaption of flooding strength according to deltaF0, 0 =
infinity i.e. constant flooding strength
-Eflnull real 0
The starting value of the flooding strength. The flooding strength is updated
according to the adaptive flooding scheme. For a constant flooding strength
use
-tau 0.
-T real 300
T is temperature, the value is needed if you want to do flooding
-alpha real 1
Scale width of gaussian flooding potential with alpha2
-[no]restrainno
Use the flooding potential with inverted sign - effects as quasiharmonic
restraining potential
-[no]hessianno
The eigenvectors and eigenvalues are from a Hessian matrix
-[no]harmonicno
The eigenvalues are interpreted as spring constant
-constF string
Constant force flooding: manually set the forces for the eigenvectors selected
with -flood (put in quotes! "1.0 2.3 5.1 -3.1"). No other flooding
parameters are needed when specifying the forces directly.
SEE ALSO¶
gromacs(7)
More information about
GROMACS is available at
<
http://www.gromacs.org/>.