Re: [AMBER] summary.ETOT analysis and MMPBSA.py

From: Jason Swails <jason.swails.gmail.com>
Date: Sun, 14 Feb 2016 09:15:24 -0500

On Sun, Feb 14, 2016 at 8:10 AM, Michael Shokhen <michael.shokhen.biu.ac.il>
wrote:

> Dear Jason,
>
> Thank you for your response and advaise to use MMPBSA.py.
>
> I have observed that ligand fluctuates between several different
> orientations in the receptor active site.
> I need to identify the average 3D structures of these conformational
> clusters of the ligand.
> That is why I want to analyse the energetic profile of receptor-ligand
> complex depending
> on different orientations of the ligand accepted during productive MD
> trajectory.
> For the analysis I need to eliminate a big energetic noise produced by
> bulk solvent water molecules.
> I am not sure, unfortunately, that the MMPBSA.py is a relevant option in
> my case,
> since it is impossible to applay MMPBSA.py for the analysis of md.mdcrd
> trajectory file
> generated on 25000 frames of productive MD.
> I would appreciate your advice that could be applied for my task.
>

​All MMPBSA.py does is to separate the trajectory of a bound complex in
solvent into 3 different systems -- one with the bound complex without
water, one with the unbound receptor, and one with the unbound ligand. It
then computes the energy of each structure (of each species) using an
implicit solvent model to eliminate bulk solvent noise (it effectively
averages over all solvent degrees of freedom).

MMPBSA.py then helpfully computes an average of these data sets, but you
can access the raw data as well (that is, the energy of the complex,
receptor, and ligand for each snapshot).

You can get the ligand-receptor energies by subtracting the unbound
energies from the bound energies. But it's important to realize that most
force fields employ an approach to calculating electrostatic interactions
that is *not* pairwise decomposable, so it's impossible to extract from a
single energy calculation the contributions between just two sets of atoms.

It sounds to me like what you are trying to do is exactly what MMPBSA.py
does, but without the final averaging at the end. You can access the raw
data in Python through the MMPBSA.py API, or at your option MMPBSA.py will
print a CSV file with all energies.

HTH,
Jason

-- 
Jason M. Swails
BioMaPS,
Rutgers University
Postdoctoral Researcher
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Received on Sun Feb 14 2016 - 06:30:03 PST
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