make_edi VERSION 3.3_beta_20050823

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 -nice int -[no]xvgr -mon string -linfix string -linacc string -radfix string -radacc string -radcon string -flood string -outfrq int -logfrq int -slope real -maxedsteps int -deltaF0 real -deltaF real -tau real -eqsteps int -Eflnull real -T real -alpha real -linstep string -accdir string -radstep real -[no]restrain -[no]hesse -[no]harmonic

make_edi generates an 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, velocities and forces 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 x, v and f 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

-outfrq : frequency (in steps) of writing out projections etc.

-logfrq : frequency (in steps) of writing out statistics to log 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 (it would require much extra communication to fully parallelize the algorithms). Fortunately, however, a typical parallel protein simulation in gromacs has most or all protein coordinates on one processor (the master) and has only other atoms (solvent, lipid, ions etc) on the other processors. With such a setup, ED sampling will still work. If the atoms over which ED sampling should be performed are spread over multiple processors, a fatal error will result.

All output of mdrun (specify with -eo) is written to a .edo file (some extra information is written to the log file of mdrun too, actually). The .edo format is a simple ASCII file that should be easy to parse with standard unix tools like awk. A script (parse_edo) can be downloaded from contribution section at www.gromacs.org to extract information from the can be expected in the rest of the .edo file. After the header, per step the following information is present:

* the step number

* RMSD (for atoms in fitting prior to calculating ED constr.)

* projections of the positions onto selected eigenvectors

* projections of the velocities onto selected eigenvectors

* projections of the forces onto selected eigenvectors

All projections are in the same order as in the header, so if you have e.g. 2 groups (say one group over which acceptance radius expansion is performed, and another for which the projections are merely monitored) then you first get the position projections for each of the 2 groups, then the velocities and then the forces. Radii are not explicitly written to the .edo file, as they can be readily projected back from the positions. Alternatively, radii may be 'grepped from the log file.

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 strength 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 alpha1for restraining alpha1 can give you smaller width in the restraining potentialRESTART and FLOODING: If you want to restart a crashed flooding simulation please find the values deltaF and Efl in the output file and write them with your texteditor into the .edi file under DELTA_F0 and EFL_NULL

-f eigenvec.trr Input Full precision trajectory: trr trj

-eig eigenval.xvg Input, Opt. xvgr/xmgr file

-s topol.tpr Input Structure+mass(db): tpr tpb tpa gro g96 pdb xml

-n index.ndx Input, Opt. Index file

-tar target.gro Input, Opt. Generic structure: gro g96 pdb tpr tpb tpa xml

-ori origin.gro Input, Opt. Generic structure: gro g96 pdb tpr tpb tpa xml

-o sam.edi Output ED sampling input

-[no]h no Print help info and quit

-nice int 0 Set the nicelevel

-[no]xvgr yes Add specific codes (legends etc.) in the output xvg files for the xmgrace program

-mon string Indices of eigenvectors for projections of x, v and f (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

-logfrq int 100 frequency (in steps) of writing to log

-slope real 0 minimal slope in acceptance radius expamsion

-maxedsteps int 0 max nr of steps per cycle

-deltaF0 real 150 target destabilization energy - used for flooding

-deltaF real 0 start deltaF with this parameter - default 0, i.g. 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

-eqsteps int 0 number of steps to run without any perturbations

-Eflnull real 0 this is the starting value of the flooding strength. The flooding strength is updated according to the adaptive flooding scheme. To use 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

-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

-[no]restrain no use the flooding potential with inverted sign - effects as quasiharmonic restraining potential

-[no]hesse no the eigenvectors and eigenvalues are from a Hesse matrix

-[no]harmonic no the eigenvalues are interpreted as spring constant

gromacs(7)

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