coot

The power of jiggle fit in low resolution data

At the homepage for Garib Murshudov’s lab, there is a page dedicated to EM fitting tools and scripts. Among these scripts are some for Coot which adds jiggle-fit, morph modeling  and user-define restraints capabilities to Coot (you can read a bit about them here).

If you have not used Jiggle-fit yet, I can highly recommend it, especially for low resolution de-novo building.

Here is an example I did using jiggle-fit in Coot using my own map and a Coot generated ideal RNA double helix.

I just placed the helix randomly somewhere in the density,that  I want to fit the helix into, like so:

jiggle_1

I then ran jiggle fit on the whole molecule (I used 20000 loops) and about 30 sec later I get this:

jiggle_2

Due to the relative low resolution of the map, it can be a bit difficult to see just how good the fit actually is, but this zoom-in may help a bit:

jiggle_3

It is a very efficient tool, but of course it does not always work this well.


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