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From: Jesper Sørensen <lists.jsx.dk>

Date: Tue, 5 Apr 2011 09:25:47 +0200

Hi Jason,

Thanks for the reply. I understand how MMPBSA.py comes up with that number

now - but I am not sure that it makes sense to me why it is calculated that

way. Isn't it more reasonable to calculate the standard deviation off of the

column with the ddG per frame? I mean shouldn't that take advantage of

cancellation of errors? And in any case from an ALA-scanning with a

1-trajectory approach, wouldn't you expect the numbers to be correlated?

The two ways of looking at it gives huge differences, so I am just curious

which number to use for publication purposes. I don't recall seeing people

having reported numbers like the first below, but on the other hand if that

is the more correct number then that is the one I should use...

Is there a problem using the standard error of the mean instead of the

standard deviation, since it is not also reported?

0.3974 +/- 24.2708

0.397356 +/- 0.937653

Best,

Jesper

-----Original Message-----

From: Jason Swails [mailto:jason.swails.gmail.com]

Sent: 4. april 2011 18:05

To: AMBER Mailing List

Subject: Re: [AMBER] MMPBSA.py ala-scanning output results

2011/4/4 Jesper Sørensen <lists.jsx.dk>

*> Hi,
*

*>
*

*> I have a question about the output produced by the MMPBSA.py script
*

*> from an alanine scanning.
*

*>
*

*> I think the value of the standard error is wrong - mostly because it
*

*> is really high.
*

*>
*

*> RESULT OF ALANINE SCANNING: (L12A MUTANT:) DELTA DELTA G binding =
*

*> 0.3974
*

*> +/- 24.2708
*

*>
*

*> I have taken the output files and run them through my own matlab script.
*

*> If I subtract the two columns with the "DELTA G binding" numbers I get:
*

*>
*

*> AVG -0.397356
*

*> STD 0.937653
*

*>
*

This standard deviation appears (?) to be a population standard deviation;

i.e. you have a list of numbers and calculate the stdev. MMPBSA.py

calculates this standard deviation in a propagation of errors type of way

(sqrt(std1**2 + std2**2 + ...)). The first approach takes into account all

of the correlation in the data (which lowers the variance), whereas the

latter approach assumes no correlation.

Hope this helps,

Jason

*> The average is the same, but the STD is very different. Does anybody
*

*> have a comment on this?
*

*> I have performed this calculation of a lot of residues in my complex
*

*> and they all produce +/- around 24 to 25, no matter the value of the ddG.
*

*>
*

*> Best regards,
*

*> Jesper
*

*>
*

*>
*

*> _______________________________________________
*

*> AMBER mailing list
*

*> AMBER.ambermd.org
*

*> http://lists.ambermd.org/mailman/listinfo/amber
*

*>
*

Date: Tue, 5 Apr 2011 09:25:47 +0200

Hi Jason,

Thanks for the reply. I understand how MMPBSA.py comes up with that number

now - but I am not sure that it makes sense to me why it is calculated that

way. Isn't it more reasonable to calculate the standard deviation off of the

column with the ddG per frame? I mean shouldn't that take advantage of

cancellation of errors? And in any case from an ALA-scanning with a

1-trajectory approach, wouldn't you expect the numbers to be correlated?

The two ways of looking at it gives huge differences, so I am just curious

which number to use for publication purposes. I don't recall seeing people

having reported numbers like the first below, but on the other hand if that

is the more correct number then that is the one I should use...

Is there a problem using the standard error of the mean instead of the

standard deviation, since it is not also reported?

0.3974 +/- 24.2708

0.397356 +/- 0.937653

Best,

Jesper

-----Original Message-----

From: Jason Swails [mailto:jason.swails.gmail.com]

Sent: 4. april 2011 18:05

To: AMBER Mailing List

Subject: Re: [AMBER] MMPBSA.py ala-scanning output results

2011/4/4 Jesper Sørensen <lists.jsx.dk>

This standard deviation appears (?) to be a population standard deviation;

i.e. you have a list of numbers and calculate the stdev. MMPBSA.py

calculates this standard deviation in a propagation of errors type of way

(sqrt(std1**2 + std2**2 + ...)). The first approach takes into account all

of the correlation in the data (which lowers the variance), whereas the

latter approach assumes no correlation.

Hope this helps,

Jason

-- Jason M. Swails Quantum Theory Project, University of Florida Ph.D. Candidate 352-392-4032 _______________________________________________ AMBER mailing list AMBER.ambermd.org http://lists.ambermd.org/mailman/listinfo/amber _______________________________________________ AMBER mailing list AMBER.ambermd.org http://lists.ambermd.org/mailman/listinfo/amberReceived on Tue Apr 05 2011 - 00:30:02 PDT

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