Hi Mark,
Thanks a lot. This was very helpful. I have also a question concerning single 
vs double precision gromacs simulation. Which one is more suitable for this 
kind of simulation and are there general rules to decide which precision should 
be used depending on the simulation?

All the best
Otto


On 12 Dec 2011, at 12:55, Mark Abraham <[email protected]> wrote:

> On 12/12/2011 8:42 PM, Patrick Fuchs wrote:
>> Hi Otto,
>> in my lab we tried to implement this REST variant in GROMACS as proposed by 
>> those authors. We figured out that it was easier to manipulate directly the 
>> parameters files in the top directory. There you know exactly what you are 
>> doing; recall that some interactions (i.e. solvent/solvent) mustn't be 
>> scaled whereas some others have to be scaled (solute/solute and 
>> solute/solvent).
>> It's probably possible to do it in the tpr file, but it looked less trivial 
>> to me: i) you have to know how atoms are coded in the file (e.g. in the 
>> functype[???]=LJ_SR[...] matrix, you have to understand how atom numbers are 
>> coded there), ii) you have to regenerate a tpr from plain text file; it's 
>> probably doable, but I don't know how. Actually, maybe some developers can 
>> tell if it's possible.
> 
> It's possible, but far from desirable to attempt to manipulate the contents 
> of the .tpr directly.
> 
> Instead, use grompp -pp to write a complete stand-alone topology, which you 
> can then use as input to a script to do the appropriate solute parameter 
> scaling for each replica. Then use grompp normally on the new set of .top 
> files to generate a set of .tpr files that differ not only in lambda but in 
> their solute parameters.
> 
> Mark
> 
>> Good luck,
>> 
>> Patrick
>> 
>> Le 08/12/2011 19:01, Otto Master a écrit :
>>> Dear gromacs users,
>>> 
>>> Recently I stumbled over following paper:
>>> T. Terakawa, T. Kameda, and S. Takada, On Easy Implementation of a
>>> Variant of the Replica Exchange with Solute Tempering in GROMACS.
>>> Journal of Computational Chemistry 32 (2011) 1228-1234.
>>> 
>>> The authors suggested an easy way to run this kind of simulation with
>>> Gromacs, without even changing the code. The only thing that is need, is
>>> the the rescaling of the parameters in the parameter file. Since the
>>> reduction of the replica number is quite appealing to me I wonder which
>>> file I have to change? Actually, I thought of manipulating the .tpr file
>>> or to rescale and creating the force fields for every replicate. Is this
>>> feasible, or is there a better way?
>>> 
>>> Manipulating the .tpr file could be easier, since it unifies (right?)
>>> the parameters from the different force fields, before sending it to the
>>> mdrun application. But for this I would like to understand the tpr file
>>> first.There are quite a lot of entries and first I try to understand LJ
>>> interactions and how they are defined in this file. I found two entries
>>> 
>>> LJ14
>>>          functype[154]=LJ14, c6A= 0.00000000e+00, c12A= 0.00000000e+00,
>>> c6B= 0.00000000e+00, c12B= 0.00000000e+00
>>>          functype[155]=LJ14, c6A= 4.46680887e-03, c12A= 4.74702711e-06,
>>> c6B= 4.46680887e-03, c12B= 4.74702711e-06
>>> 
>>> which corresponds to following interactions
>>> 
>>>       LJ-14:
>>>          nr: 876
>>>          iatoms:
>>>             0 type=154 (LJ14) 0 4
>>>             1 type=155 (LJ14) 0 5
>>> 
>>> When I tried to calculate the parameters from the combination rules (in
>>> this case Gromos 53A6 force field), I found (the highlighted columns
>>> contain the original parameters for the specific atom groups from the
>>> Gromos  documentation and the calculated value for combining the two
>>> parameters:
>>> 
>>> 
>>> 
>>> 
>>>    sqrt(C6i) (from ff)     sqrt(C6j) (from ff)     sqrt(C6i)*sqrt(C6j)     
>>> value
>>> from tpr file
>>> functype[154]=LJ14,     c6A=     CH3     H     0.09805     0     0     
>>> 0.00E+00
>>> functype[155]=LJ14,     c6A=     CH3     CH1     0.09805     0.0779     
>>> 0.007638095     4.47E-03
>>> functype[156]=LJ14,     c6A=     C     CH2     0.04838     0.08642     
>>> 0.004181     3.33E-03
>>> functype[157]=LJ14,     c6A=     C     C     0.04838     0.04838     
>>> 0.002340624     2.34E-03
>>> 
>>> 
>>> The values for N, C, O, H seems to be OK, but I have problems to get the
>>> same value, when CH1, CH2, CH3 are involved. Since I do not have too
>>> much experience, I would like to know how the value from the .tpr file
>>> can be derived.
>>> 
>>> The other entry for LJ potential is the short range term LJ_SR (.tpr file
>>> 
>>>    ffparams:
>>>       atnr=11
>>>       ntypes=170
>>>          functype[0]=LJ_SR, c6= 9.61380266e-03, c12= 2.66462448e-05
>>>          functype[1]=LJ_SR, c6= 4.74365894e-03, c12= 1.14699596e-05
>>>          functype[2]=LJ_SR, c6= 4.66325786e-03, c12= 5.16199998e-06
>>> 
>>> Unfortunately, I do not find the section where the function is assigned
>>> to a specific pair of interaction. Where are these functions assigned to
>>> a specific interaction? Furthermore, is it possible to distinguish
>>> between intra-nonbonded (solute-solute) and inter-bonded (water-solute)
>>> interaction?
>>> 
>>> For you this might be an easy question to answer, and you immediately
>>> realize there is a beginner at work, but nevertheless I would appreciate
>>> any help.
>>> 
>>> All the best
>>> Otto
>>> 
>>> 
>> 
> 
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