Don't be surprised about these differences ... I am also not sure why
you think the -47 is actually better than +8 ? Just because is negative
? Do you know the experimental value for your system or some similar
system ? If you rerun the PB calculation with some different parameters.
you might see even bigger differences.
Please take Jason's advice and go after ddGs or even dddGs if possible
... There is no magical recipee for MMPBSA. You need to play as much as
possible with the parameters and see what you get. You should compare
with experiment whenever you can. For absolute dGs, you also should not
forget the conformational entropy ....
If you would like to experiment with inp=1, please take care that all
the default parameters in MMPBSA are for inp=2 (e.g. cavity_surften and
cavity_offset) ... Please read the relevant literature and make sure you
understand the parameters.
Best wishes
Vlad
On 04/24/2014 01:19 PM, Jason Swails wrote:
> On Thu, 2014-04-24 at 08:38 +0530, Arunima Shilpi wrote:
>> Dear Sir
>>
>> Here while detlta G by MMPBSA for protein-ligand complex I am geting the
>> positive for delta G. Here one of the residue C1191 has been mutated to
>> C1191I and then the delta G binding have been calculated.
>>
>> Here are the details of input command and the Final results
>>
>> #!/bin/sh
>> #PBS -N C1191K_3781_r
>> #PBS -l select=1:ncpus=8
>> #PBS -j oe
>> #PBS -q small
>>
>> cd $PBS_O_WORKDIR > pwd
>> cat $PBS_NODEFILE > pbsnodes
>>
>> /opt/intel/impi/4.1.0.024/intel64/bin/mpirun -machinefile $PBS_NODEFILE -np
>> 8 $AMBERHOME/bin/MMPBSA.py.MPI -O -i mmpbsa.in -o FINAL_RESULTS_MMPBSA.dat
>> -sp C1191K_DRG_solvated.prmtop -cp C1191K_DRG.prmtop -rp C1191K.prmtop -lp
>> DRG.prmtop -y *.mdcrd
>>
>>
>> and final results is
>>
> [snip]
>
>> Differences (Complex - Receptor - Ligand):
>> Energy Component Average Std. Dev. Std. Err. of
>> Mean
>> -------------------------------------------------------------------------------
>> VDWAALS -59.7408 3.9526
>> 0.5590
>> EEL -67.1741 7.3094
>> 1.0337
>> EGB 87.3878 6.1042
>> 0.8633
>> ESURF -8.1986 0.2427
>> 0.0343
>>
>> DELTA G gas -126.9150 7.4496
>> 1.0535
>> DELTA G solv 79.1893 6.0356
>> 0.8536
>>
>> DELTA TOTAL -47.7257 3.3376
>> 0.4720
>>
>>
>> -------------------------------------------------------------------------------
>> -------------------------------------------------------------------------------
>>
>> POISSON BOLTZMANN:
> [snip]
>
>> Differences (Complex - Receptor - Ligand):
>> Energy Component Average Std. Dev. Std. Err. of
>> Mean
>> -------------------------------------------------------------------------------
>> VDWAALS -59.7408 3.9526
>> 0.5590
>> EEL -67.1741 7.3094
>> 1.0337
>> EPB 101.1607 7.3105
>> 1.0339
>> ENPOLAR -41.3671 1.2286
>> 0.1737
>> EDISPER 76.0735 1.3057
>> 0.1846
>>
>> DELTA G gas -126.9150 7.4496
>> 1.0535
>> DELTA G solv 135.8671 7.3979
>> 1.0462
>>
>> DELTA TOTAL 8.9521 5.0649
>> 0.7163
>>
>>
>> -------------------------------------------------------------------------------
>> -------------------------------------------------------------------------------
>>
>>
>> I request you yo kindly guide me in debugging the error.
> There is no error. The calculation finished correctly and did what you
> told it to do. The main difference between the GB and PB results lies
> in the fact that the nonpolar solvation model used by PB is a more
> destabilizing model than the simple, linear SASA-based model used by GB.
> You can use the "inp=1" variable in the &pb namelist to use a similar
> model for PB nonpolar energies if you want to.
>
> It's important to understand what MM/GBSA and MM/PBSA calculations can
> and cannot do. Despite the fact that MMPBSA.py is (somewhat) easy to
> use, MM/PBSA calculations should be considered advanced (indeed, the
> tutorial is in the "advanced" section of our tutorial list) and you
> should understand the underlying theory behind the methods you are
> using.
>
> Specifically, MM/PBSA calculations are typically bad for predicting
> absolute binding free energies, so only energy differences really
> matter. The polar solvation energies are typically pretty good, but the
> nonpolar solvation models are over-simplified in my opinion and in
> general unreliable for absolute energy predictions. The simple
> SASA-based model (inp=1) has worked fine in the studies I've seen, but I
> haven't looked into the new dispersion/cavitation model used by PBSA
> much so I can't comment on how well it works in general. The manual
> should contain helpful citations that I would suggest reading to get a
> better understanding of the model's strengths and weaknesses (the
> citation should be present where the "inp" variable is described).
>
> Good luck,
> Jason
>
--
Dr. Vlad Cojocaru
Computational Structural Biology Laboratory
Department of Cell and Developmental Biology
Max Planck Institute for Molecular Biomedicine
Röntgenstrasse 20, 48149 Münster, Germany
Tel: +49-251-70365-324; Fax: +49-251-70365-399
Email: vlad.cojocaru[at]mpi-muenster.mpg.de
http://www.mpi-muenster.mpg.de/research/teams/groups/rgcojocaru
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Received on Thu Apr 24 2014 - 05:00:04 PDT
