PROTEINS: Structure, Function, and Bioinformatics
04-Sep-2013
Dear Dr. Ramanathan Sowdhamini:
Experts in the field have carefully reviewed your manuscript entitled "Decoding the structural
events in substrate-gating mechanism of eukaryotic prolyl oligopeptidase using normal mode
analysis and molecular dynamics simulations". Although they found merit in your study, they
have raised a number of serious concerns that preclude its acceptance in the present form. This
paper has been recommended for MAJOR REVISIONS. I invite you to respond to the reviewers'
comments and revise your paper accordingly. The revised version will be re-evaluated by the
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PROTEINS.
Sincerely,
Dr. Bertrand Garcia-Moreno
Editor-in-Chief
PROTEINS: Structure, Function, and Bioinformatics
The Johns Hopkins University
Department of Biophysics
Baltimore, MD 21218 U.S.A.
----EDITORIAL MANAGER'S COMMENTS TO AUTHOR:
Editorial Manager
Comments to the Author:
(There are no comments.)
REVIEWERS' COMMENTS TO AUTHOR:
Reviewer: 1
Comments to the Author
This is an interesting article on the understanding of large-scale movements of prolyl oligopeptidases using both NMA and PCA of MD simulations. The results are convincing and
original, and the Figures illustrate them well.
Our response: Thank you for the encouraging comments. We have attempted to improve
the manuscript by incorporating your suggestions.
I have the following comments:
Major comments
-The main issue I would raise is that there is an inconsistency in the manuscript about the
use of the ENM: in the Materials and Methods section (p. 6) it is stated that all atoms are
taken into account, whereas in the Results section (p. 13), it is stated (twice) that only Caatoms were taken into account.
Which conditions were really used? If only Ca-atoms were taken, the cut-off radius of 8
Angstroms is probably too short (should be increased to 10 Angstrom), or at least a word
should be said about the sensitivity of the results with respect to this parameter.
Our response: Thank you for noticing this very important point. Please note that we have
considered all atoms while performing normal mode calculations with the cut-off radius of
8Å. On both page 6 and page 13 we have corrected it to all-atom ENMs and it is marked in
red.
-Finally, I noted that the PCA of MD trajectories were made on simulation runs of 100 ns
and 70 ns (p. 8): are these trajectories not too short to draw definite conclusions?
How would the results stand in longer simulations, say twice longer?
Our response: Thank you for your concern. We had performed 3 replicates each of 100ns
of bound and unbound forms of POP. We thought multiple simulations of same protein
might be a better way to analyze the conformational changes, instead of a single long run,
due to better conformational sampling. Therefore, PCA was performed on concatenated
trajectories of both bound and unbound forms of protein.
Now, we have extended our simulations to 200ns for both bound, unbound forms, modeled
structure, and bacterial forms of POP (but not for replicates) (page 8). PCA analysis is
again carried out on the concatenated and individual trajectories. In the whole analysis our
aim was to check the robustness of the NMA motions. We showed that some directions of
motions given by NMA were also observed in PCA.
Minor Comments:
Summary (p. 2)
-...oligopeptides shorter than 30...
-...which has been debated until now...
-...Reciprocation: unclear, please rephrase
Our response: Thanks for noticing these points. We have corrected them and all the
corrections are marked in red color.
-p. 5: "to be the only possible pathway"
-p. 5: is it Glu 397 or Gln 397? (Q397C)
Our response: Thank you. It is Gln397. We have corrected this.
-p. 6: ... where the latter...
-p. 7: Start a new sentence at "The larger the (overlap) value..."
-p. 8: PRODRUG or PRODRG??
-p. 13: " These overall similarities ... prompted us" (instead of intrigued us)
-p. 14: "Distance between propeller and hydrolase domains varied during the simulation
and representing oscillating nature of these domains": rephrase
-p. 14: "high collectivity does not allow the understanding of the fine role" (not
"precludes from")
-p. 15: "...were removed and (it was observed that) the resultant 'deletion' mutant'..."
-p. 15: "affirms" -> "suggests"
-p. 17: "This study showed that motions of inter-domain loop regions... are not sufficient
for ..."
-p. 18: "... in none of the earlier MD studies... could be observed"
-p. 18: "...St-Pierre et al." give Ref. here (53)
-p. 19: "depicted" -> "indicated"
-p. 19: "...we were able to delineate..."
Our response: Thanks for noticing these points. We have corrected them and all the
corrections are marked in red color.
Reviewer: 2
Comments to the Author
The manuscript describes the use of network models and molecular dynamics to model the
motions of activation of an enzyme. The problem is interesting, and overall the methods
seem appropriate. However, I have some serious reservations about the manuscript as it
stands:
Our response: Thank you very much for supporting comments. We have tried to improve
the manuscript with your useful suggestions.
1) The writing is extremely poor. There are a large number of grammar errors (mostly,
missing "the"s), as well as a lot of awkward sentence constructions. It's crucial that this
paper be carefully reviewed sentence by sentence by a native english speaker before it is
resubmitted.
Our response: Thanks for your comments. We have tried to correct the grammatical
mistakes in the manuscript.
2) The authors need to put in some assessment of the statistical significance of the MD.
While I credit them for performing multiple simulations, 100ns seems kind of short, and
they didn't take advantage of the multiple replicates to check the convergence. For
example, what is the RMSD between the averages from the 3 repeated trajectories of the
same system? (it might make sense to exclude the highly flexible loops from this
calculation) If one computes the PCA modes from each trajectory individually, how similar
are the modes? There are several techniques for using PCA to assess convergence that
could be applied (see e.g. Grossfield et al, Proteins, I think in 2006).
Our response: Thanks for your comments. We have extended the simulations to 200ns (not
for replicates). We have also calculated the RMSD between the averages from the three
trajectories (Table S2) and directions of modes of three replicates were checked using
overlap between matrices (Table S3). The Cα-RMSD between the averages of the
trajectories is less than 1Å. The results are summarized in the following table.
RMSD between average Å
Bound
Unbound
Rep1/Rep2
0.47
0.67
Rep1/200ns
0.69
0.64
Rep2/200ns
0.65
0.8
The covariance calculations were made on Cα only and on the data from equilibrium. We
calculated the overlap within and between trajectories. The results for the 10 first PCA,
which represent ~60% of the total covariance, are summarized in the table below.
Overlap within trajectories
Bound
Unbound
Rep1
Half1/Half2
0.46
0.45
Rep2
Half1/Half2
0.425
0.45
200ns
Half1/Half2
0.46
0.43
Overlap between
trajectories
Bound
Unbound
Rep1/Rep2
Rep1/200ns
Rep2/200ns
0.43
0.31
0.40
0.30
0.40
0.39
The results show that the conformational space visited along each simulation is different
and that the convergence for each simulation is not reached. This is why If PCA is
performed on the whole set of data, i.e. by concatenation of all the trajectories, it allows to
better highlight what are the most representative motions, and to filter out what are those
more specific to each simulation. In this case, the amount of data collected is rather large (~
half a s if we include MD at higher temperature) and allowed us to retrieve similar
directions of motions observed by NMA, confirming the robustness of conformational
changes identified with a crude coarse-grained model.
3) In the abstract, the sentence beginning "Indeed, there is..." should emphasize that
according to the crystal structures, there's no difference. The whole point of the paper is
that there probably _is_ a difference, and that the lack thereof is just an artifact of the
crystallization.
Our response: Thanks for pointing this. We have corrected this in the manuscript.
4) In the intro, the sentence beginning "Two POP inhibitors..." makes no sense. How do
clinical trials "explain insights" into significance?
Our response: Thanks for noticing this. We have changed these sentences in the
manuscript and are colored in red (refer page 3).
5) On page 4, the term "open-Velcro topology" is used without definition or explanation.
Our response: Thank you for the comments. The open-Velcro topology is described on
page 3 of the manuscript. We have tried to make it clearer now.
6) On the bottom of page 5, you say "each atom" is used in ENMs, where in reality it's
nearly always just alpha carbons (this is stated correctly later).
Our response: Thanks for noticing. Actually, we performed all atom normal mode analysis
using cutoff of 8Å. We have corrected the manuscript wherever we had mentioned it as Cα
atoms (page 6).
7) Why was an 8 ang cutoff used in the ENM? This is much shorter than is usually
recommended for a simple cutoff calculation, because you can get instabilities. See for
example the work of Ivet Bahar's group.
Our response: Thank you for the comments. We had used 8Å cutoff for all atom ENM.
This is the recommended cutoff for all atom NMA (Suhre and Sanejouand, NAR, 2004).
8) The authors state on page 6 that fitting c and Rc won't affect the directions of the modes.
This is completely wrong: both directions and relative amplitudes of motions are changed
by the cutoff. See for example recent work by Leioatts et al (Proteins, 2013).
Our response: Thanks for pointing this. We have modified this as it was a wrong statement
(page 6). The directions are not sensitive to c (the force constant).
9) In the second equation on page 6, where does Ck come from? Is it just from assuming
that amplitude is ~ 1/frequency? It's not clear to me why Ck would "depend on initial
conditions".
Our response: Thanks for your comments. Ck is amplitude which can be calculated from
frequency. According to the equipartition theorem, it also depends, in theory, to the
temperature. However, in the present case, we used a coarse-grained model that was
calibrated to reproduce the experimental B-factors profile. This choice influenced the
values of the frequencies.
10) As far as I can tell, Aik in the last equation on page 6 has the same meaning as Vik in
the previous equation. Why change notations? Not to mention, as a rule the normal modes
have unit length by default (the amplitude of the motion is encoded in the frequency, see
above).
Our response: Thanks for your query. In degree of collectivity equation, Aik is the
amplitude of the displacement of atom i in the mode k..
Degree of collectivity isN
1
 k  exp( Aik2 log Aik2 )
N
where Aik is the amplitude of the displacement of atom i in the mode k
while trajectories were obtained using:
3N

ri (t )   C kVik cos( k t  k )
K 1
where, Vik is the component i of the normal mode k, Vk, Ck, is the amplitude of mode Vk,
and k its frequency and phase respectively
So Aik is related to Vik but it is not same as Vik.
11) Strictly speaking, the overlap as written goes from -1 to 1. You should have an absolute
value surrounding the dot product, since eigenmodes are only defined up to a sign.
Our response: Thanks for your comments. In fact, calculations were carried out
considering absolute values and overlap range was considered between 0 to 1. We have
corrected this in the manuscript (page 7).
12) The axes should be labeled in Figure 4 so we can easily read off where in the sequence
we are (though the blue/black line thing is a good trick).
Our response: Thank you very much for your comments. We have changed this in the
manuscript for the easy understanding.
13) on page 9 and beyond, when you refer to mode numbers, are you skipping the 6 zerofrequency modes? eg, is mode 7 the first non-trivial mode? If so, this needs to be
emphasized. If not, some explanation for why you get to cherry-pick modes must be
provided? When discussing individual modes, it would be helpful to say what fraction of
the overall motion is contributed by that mode (e.g. %contrib by mode I = (1/ freq_i) / sum
( 1/freq_i).
Our response: Thanks for your comments and noticing the important point. Indeed, first 6
modes are six zero frequency modes, that’s why we have not considered them. Now, we
have included this in the text for the easy understanding (page 7). We have also added
percentage contribution of each mode in the text (page 9-11).
14) On the bottom of page 9 into page 10, you discuss the inter-domain motions and state
that they're absent when the domains are considered individually. Maybe I'm missing
something, but isn't that because in the absence of the second domain, the "clockwise and
anti-clockwise" motions would just be rigid body motions that are removed from the ENM
calculation? Also, it's "counter-clockwise", not "anti-".
Our response: Thanks for your comments. We have rephrased this sentence in the
manuscript.
15) On page 10, how significant is mode 31? Given that the amplitude of motion associated
with a mode decays roughly exponentially with the mode number, this is likely predicted by
the ENM to be a small motion.
Our response: Thanks for your comments. It is true that modes are sorted according to
amplitude or frequency and this number might be associated with a low amplitude or high
frequency. However, in our case, the situation is slightly different, due to the frequency
spectrum. As shown in the following figure, the contribution of each mode relative to the
lowest one (mode 7) is decreasing slowly and mode 31 still represents 40% contribution to
overall motions of protein as compared to mode 7.
In addition, we also examined an important parameter, i.e. the degree of collectivity (Tama
and Sanejouand, protein engineering, 2001) that reflects the number of atoms that are
significantly affected during the conformational changes. We made the hypothesis that
large structural rearrangements, like those able to be associated with POP function, would
require collective movement of a large number of atoms. Hence, Mode 31 is the mode
associated with a high collectivity value (0.55 as compared to 0.64 for mode 7 and 0.51 for
mode 8). It is the reason why we considered this mode to be important for the analysis.
Importance of this mode was again proved in the results of MD simulations, where we
could observe propeller pore opening.
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