Hi, Jason
Here i am attaching the MMPBSA_complex_nm.out, MMPBSA_receptor_nm.out,
MMPBSA_ligand_nm.out, Final output file of the entropy calculation with
drms=0.1,
Can you please explain me the nm.out files. As you said that negative
eigenvalues are omitted from entropy calculation.
On Thu, Jul 10, 2014 at 6:22 PM, Him Shweta <shwetahim.gmail.com> wrote:
> Thanks Jason for your suggestions.
>
> On 7/9/14, Jason Swails <jason.swails.gmail.com> wrote:
> > On Tue, Jul 8, 2014 at 10:12 PM, Him Shweta <shwetahim.gmail.com> wrote:
> >
> >> Dear all,
> >>
> >> I am running entrop calculation in MMPBSA.py for a quadruplex-ligand
> >> system with an input file as below:
> >>
> >> Input file for running entropy calculations using NMode
> >>
> >> &general
> >>
> >> endframe=100, keep_files=0,
> >>
> >> /
> >>
> >> &nmode
> >>
> >> nmstartframe=1, nmendframe=100,
> >>
> >> nminterval=1, maxcyc=10000, drms=0.1,
> >> nmode_igb=1, nmode_istrng=0.0,
> >>
> >> /
> >>
> >>
> >> Here, in this calculation when i am using convergence criteria (drms =
> >> 0.1), the result is more close to my experimental result, while with
> >> drms=0.001, the result does not match or is closer to my experimental
> >> result.
> >> The thing here which is confusing to me is, can i use a convergence
> >> criteria for minimized energy gradient as 0.1 (drms).
> >>
> >> Please give your input and suggestions.
> >>
> >
> > I think that the answer to your question is "no, you cannot use 0.1" as
> > the minimization convergence criteria. I suspect what is happening in
> > your calculation is that when you set the convergence criteria to 0.1,
> the
> > minimization stops farther away from a true local minimum, meaning that
> > more of the normal modes will have negative frequencies. At a true
> > stationary point representing a local minimum, all eigenvalues of the
> > Hessian will be positive (and these eigenvalues correspond to normal mode
> > frequencies).
> >
> > Negative eigenvalues are omitted from the entropy calculation, so if
> using
> > drms=0.1 leaves you farther from a local minimum, it's likely that more
> > modes have negative frequencies (and are therefore omitted) which could
> > artificially lower the entropy estimate. But this is a consequence of
> > doing a bad normal mode calculation, _not_ of improving your model. You
> > can look at the normal mode output files to see how many modes have
> > negative frequencies. It could be that making drms smaller could also
> > improve your results, since I think low frequency motions are more
> > sensitive to proximity to a local minimum (and the low frequency motions
> > dominate the entropy contribution).
> >
> > Hope this helps,
> > Jason
> >
> > --
> > Jason M. Swails
> > BioMaPS,
> > Rutgers University
> > Postdoctoral Researcher
> > _______________________________________________
> > AMBER mailing list
> > AMBER.ambermd.org
> > http://lists.ambermd.org/mailman/listinfo/amber
> >
>
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Received on Thu Jul 10 2014 - 10:00:02 PDT
