AMBER Archive (2007)

Subject: AMBER: metalloprotein dynamics

From: Sally Pias (sallypias_at_gmail.com)
Date: Mon Aug 27 2007 - 12:55:51 CDT

Hello. I wondered if anyone could help me develop a protocol for
examining the specific role of a metal ion in stabilizing a protein.

Three experimentally-determined structures (two X-ray and one NMR) are
available for the protein, all of them in the metal ion incorporating
form. I want to model the consequences of removing the metal from the
structure. It has been experimentally shown that metal ion removal
leads to aggregation of the protein and to a decrease in its thermal
stability. Yet, there is evidence to suggest that the proper folding
of the protein does not require interaction with the metal. I want to
learn the mechanism by which the metal ion contributes to the
protein's stability, and I suspect that it involves restriction of the
protein's dynamics.

Therefore, my goal is to be able to model the dynamics of the protein
in the absence of the metal cofactor. I have constructed a model of
the metal-deficient protein by simply deleting the metal ion from an
X-ray structure pdb file. However, 5 ns explicitly solvated MD
simulations of this model at 300 K (using Sander) show a very small
range of motion in the entire protein. The RMSD does increase
somewhat over time but reaches a maximum of only 1.75 angstroms. I
think the model is stuck in an energy minimum that is not reflective
of the lowest-energy structure for the metal-deficient protein.

I am trying to develop a protocol that would allow the model to leave
this energy minimum, so that I can observe more realistic dynamics of
the protein in its metal-deficient form. So far, I have two ideas.
(1) "Heat" the system a few degrees to escape the local energy
minimum, and simulate the dynamics at the new temperature (or drop
back to 300 K to observe the dynamics). For comparison, I would use
the same protocol to model the metal-incorporating structure. (2)
Perform MD simulations at 300 K using models constructed from the NMR
structure, which is likely to be less energetically "stuck" (less
stable) in the first place. I would plan to use a long equilibration
period (about 1 ns) for the NMR-based models, prior to the production
run.

This problem strikes me as similar to a case where in silico point
mutations have been introduced (or where a residue has been
computationally phosphorylated) and one wants to model the dynamics of
the mutant. It seems like a tutorial should exist for such a case,
but I have not yet located one.

Any suggestions would be appreciated, as would references to examples
of this sort of study in the literature.

Thanks in advance.

Sally Pias
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