In my experience inp=2 gives far better affinities than inp=1 for protein-nucleic acids . As long as non-linear PB is used and sasopt=2. Therefore I disagree with changing the default to inp=1. In fact I would argue MMPBSA should not run with any defaults as users need to understand every single parameter.
For more info, look at the paper by Merino et al which was just published in Structure
http://www.cell.com/structure/abstract/S0969-2126(14)00206-8
Although here we just look at dddG, we are preparing a follow up manuscript in which we will discuss in detail the effect of every single parameter.
Best
Vlad
On August 20, 2014 9:21:13 PM CEST, "Ray Luo, Ph.D." <ray.luo.uci.edu> wrote:
>I think one reason is that the original inp=2 method was calibrated in
>reproducing relative affinities due to small changes, i.e. side chain
>mutations and/or different ligands.
>
>If you use it to model absolute binding affinities between proteins
>and nucleic acids, it breaks down. So neither inp=1 nor inp=2 gives
>"correct" absolute binding affinities when the "ligands" are also
>macromolecules. Nevertheless, I still think the relative affinities
>are better than inp=1 if the relative changes are small. So far, I
>haven't seen any data on this mailing list that show that the relative
>affinities by inp=2 are worse than those by inp=1.
>
>To address those large ligands, a different calibration has to be
>developed, i.e. solute scaling now matters and should be taken into
>account in the model. We are looking into improving the model for the
>next release.
>
>All the best,
>Ray
>--
>Ray Luo, Ph.D.
>Professor,
>Biochemistry, Molecular Biophysics, and
>Biomedical Engineering
>University of California, Irvine, CA 92697-3900
>
>
>On Wed, Aug 20, 2014 at 11:34 AM, Jason Swails <jason.swails.gmail.com>
>wrote:
>> On Wed, 2014-08-20 at 11:11 -0700, zahra khatti wrote:
>>> Dear Amber users
>>>
>>> I obtained positive free energy from mmpbsa.py.
>>
>> MM/PBSA absolute binding free energies are frequently unreliable. It
>is
>> useful mainly for rank-ordering binding affinities for related
>systems.
>>
>>> In my case the receptor and ligand didn't joint together. The
>distance between them
>>> is about 1-2 angstrom. Is this related to positive free energy?
>>
>> Let's have a look:
>>
>> [snip]
>>
>>> Differences (Complex - Receptor - Ligand):
>>> Energy Component Average Std. Dev. Std.
>Err. of Mean
>>>
>-------------------------------------------------------------------------------
>>> VDWAALS -50.0785 1.0295
> 0.0084
>>> EEL -1.1552 0.3301
> 0.0027
>>> EPB 7.3643 0.8011
> 0.0065
>>> ENPOLAR -22.2317 0.3450
> 0.0028
>>> EDISPER 354.9084 4.6963
> 0.0383
>>
>> Yikes. The EDISPER component of your binding free energy is +350
>> kcal/mole. Combining that with the repulsive ENPOLAR term, that
>means
>> your _total_ non-polar solvation free energy contribution to binding
>is
>> about +330 kcal/mole, which seems outrageous to me.
>>
>> It seems to me that this is a fairly frequent occurrence with the
>> "inp=2" non-polar solvation free energy model, so I can't say I
>> recommend using it. I suggest adding inp=1 to the &pb section of
>your
>> input file to use the more prototypical, simple SASA-based nonpolar
>> solvation approximation.
>>
>> .Developers: Perhaps we should consider either turning the default
>back
>> to inp=1 or removing the default choice altogether and requiring
>users
>> to specify it? inp=2 seems to be causing a lot more problems than it
>> solves and gives ludicrous answers more often than inp=1.
>>
>> All the best,
>> Jason
>>
>> --
>> Jason M. Swails
>> BioMaPS,
>> Rutgers University
>> Postdoctoral Researcher
>>
>>
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>
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Received on Wed Aug 20 2014 - 14:00:02 PDT
