- Contemporary messages sorted: [ by date ] [ by thread ] [ by subject ] [ by author ] [ by messages with attachments ]

From: Carlos Simmerling <carlos.simmerling.gmail.com>

Date: Wed, 7 Aug 2019 05:58:07 -0600

The first thing to do is to choose the coordinate or descriptor along which

free energy will be estimated. That is something that you will need to

decide based on your knowledge of the system and what you are trying to

study. Next you will calculate (probably in cpptraj) the value of that

coordinate for each frame of the trajectory, then histogram these values.

In order to convert to free energy you need to ensure that this histogram

represents an equilibrium ensemble. This is very important and should not

be skipped. The minimum you would want to do is to break your trajectory

into subsets (such as first and second half, or perhaps smaller chunks) and

make sure the histograms match. This isn't sufficient but is really the

minimum you should do. Independent runs from independent initial

coordinates is more reliable.

You should also plot this data stream to get a sense of the timescale of

the dynamics along this coordinate. Ideally you will see many transitions

back and forth along the full range of the coordinate. If not, this

suggests that calculation of free energy is not possible using just this

data set. More detailed analysis would involve calculation of correlation

times for this coordinate.

Assuming the data subsets match well, you can convert the histogram bins to

free energy by using a script that calculates

-RTln(Pi/P0)

where Pi is the population in bin at coordinate value i and P0 is the

population of the most populated bin. This sets the minimum free energy at

0 (which is arbitrary).

Next you can repeat this for your data subsets to calculate the

uncertainties in the free energy values. Don't neglect this part, or you

may generate very misleading data if the populations are not converged. I

microsecond may be enough, or it may be far too short. It depends on your

system and the timescale of the motions along the coordinate you selected.

This is why viewing the time dependence of the calculated coordinate values

is important.

On Tue, Aug 6, 2019, 11:18 PM M RCC <mkr3j2c1.gmail.com> wrote:

*> Dear Amber users,
*

*>
*

*> I have performed amber simulation for 1 microsecond using pmemd module. I
*

*> want to generate free energy landscape from the trajectory. Is there any
*

*> software tools/tutorials /protocols available for this?
*

*>
*

*> (I have generated in Gromacs trajectory, But no tutorials are available for
*

*> this in Amber)
*

*> Thank You
*

*> _______________________________________________
*

*> 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/amber

Received on Wed Aug 07 2019 - 05:00:03 PDT

Date: Wed, 7 Aug 2019 05:58:07 -0600

The first thing to do is to choose the coordinate or descriptor along which

free energy will be estimated. That is something that you will need to

decide based on your knowledge of the system and what you are trying to

study. Next you will calculate (probably in cpptraj) the value of that

coordinate for each frame of the trajectory, then histogram these values.

In order to convert to free energy you need to ensure that this histogram

represents an equilibrium ensemble. This is very important and should not

be skipped. The minimum you would want to do is to break your trajectory

into subsets (such as first and second half, or perhaps smaller chunks) and

make sure the histograms match. This isn't sufficient but is really the

minimum you should do. Independent runs from independent initial

coordinates is more reliable.

You should also plot this data stream to get a sense of the timescale of

the dynamics along this coordinate. Ideally you will see many transitions

back and forth along the full range of the coordinate. If not, this

suggests that calculation of free energy is not possible using just this

data set. More detailed analysis would involve calculation of correlation

times for this coordinate.

Assuming the data subsets match well, you can convert the histogram bins to

free energy by using a script that calculates

-RTln(Pi/P0)

where Pi is the population in bin at coordinate value i and P0 is the

population of the most populated bin. This sets the minimum free energy at

0 (which is arbitrary).

Next you can repeat this for your data subsets to calculate the

uncertainties in the free energy values. Don't neglect this part, or you

may generate very misleading data if the populations are not converged. I

microsecond may be enough, or it may be far too short. It depends on your

system and the timescale of the motions along the coordinate you selected.

This is why viewing the time dependence of the calculated coordinate values

is important.

On Tue, Aug 6, 2019, 11:18 PM M RCC <mkr3j2c1.gmail.com> wrote:

_______________________________________________

AMBER mailing list

AMBER.ambermd.org

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

Received on Wed Aug 07 2019 - 05:00:03 PDT

Custom Search