[gmx-users] Energy minimization: problems with ramachanrad score
chris.neale at utoronto.ca
chris.neale at utoronto.ca
Thu Jun 17 08:40:28 CEST 2010
This does not imply that less EM is better than more EM. It implies
that the native structure is not necessarily in an absolute energy
minimum according to our FF's. This is certainly true. We could take
the point of view that when an experimentalist refers to as a "native
structure" is actually a model that fits a particular electron density
map and another crystal form is bound to differ, but I guess we all
know that our FF's are less accurate than this difference so it's
probably a moot point.
EM with MM FF's is not rubbish. It's important and it has its place.
So randomizing a structure and running EM doesn't take you back to the
original minimum? sure, this is why we call the energy surface "rugged".
To get back to your homology modeling, I would always suspect that you
will need to run MD in order to explore conformational space. Homology
modeling is not my strong suit, but I've seen cases experimentally
where a single amino acid mutation can destabilize a folded protein
and cause it to be unfolded (and vice-versa), so in that light I'm
still astounded that homology modeling works at all.
Sorry to be a little vague, but then again you didn't really ask a
specific question, unless "plasmatic" is a real word...
-- original message --
I 'm trying to relax my homology models from steric clashes, and while
searching for the appropriate minimization scheme, I came across this old
The authors in the cited paper have created near-native structures as a test
set with RMSD 1.06 ± 0.14 Å over the native ones. Then they ran energy
minimization in vacuo with l-bfgs for 10000 steps or until convergence to
machine precision and they found that ordinary MM potentials (AMBER99,
OPLS-AA, GROMOS96, and ENCAD) showed no significant improvement on the
structures. On the contrary the last 3 were found to move the conformation
away from the native state by 11%, 40%, and 44% respectively. They also
tested their own 3 hybrid Knowledge-Based / Molecular Mechanics (KB/MM)
potentials and found that the best performing was moving the structures by
11% closer to the native fold.
Essentially they claimed that energy minimization with the ordinary MM
potentials is rubbish! I have one remark to make on this. Their decoy set
comprised no-native protein conformers with RMSD ~1A. I'm wondering if the
results will be similar for RMSDs ~3A as in my case where I'm building
homology models with average sequence identity to templates 25-30%?
And with respect to the original question, if you overdo it with energy
minimization the Ramachandran scores do deteriorate. However if you stop at
an intermediate step you can get the same score, bond lengths and angles but
with less steric clashes. Is this improvement plasmatic as the authors
claim, namely you have moved away from the native fold although
stereochemically the model look good?
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