Ubuntu Manpage: make_edi - generate input files for essential dynamics sampling

Provided by: gromacs-data_4.6.5-1build1_all

NAME

       make_edi - generate input files for essential dynamics sampling

       VERSION 4.6.5

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 analysis (
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 .xvg 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 implementation 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 and/or when the ED group contains a lot of atoms.

Please also note that if your ED group contains more than a single protein, then the .tpr
file must contain the correct PBC representation of the ED group. Take a look on the
initial RMSD from the reference structure, which is printed out at the start of the
simulation; if this is much higher than expected, one of the ED molecules might be shifted
by a box vector.

All ED-related output of mdrun (specify with -eo) is written to a .xvg file as a
function of time in intervals of OUTFRQ steps.

Note that you can impose multiple ED constraints and flooding potentials 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. Depending on what was
specified in the .edi input file, the output file contains for each ED dataset

* the RMSD of the fitted molecule to the reference structure (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 configuration 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  .xvg 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.

NAME

SYNOPSIS

DESCRIPTION

FILES

OTHER OPTIONS

SEE ALSO