Loop Refinement - Clustering necessary?
Dear Modeller users,
according to posts in this mailing list as well as the background information to ModLoop, the best loop-model is chosen by lowest pseudo-energy score (http://modbase.compbio.ucsf.edu/modloop/ - Fiser's and Sali's papers cited at the bottom of the page). However, the tutorial of Modeller indicates that "it is important to note that a most accurate approach to loop refinement requires the modeling of hundreds of independent conformations and their clustering to select the most representative structures of the loop" http://www.salilab.org/modeller/tutorial/advanced.html).
I have been comparing different loop-models generated by loop.model for a selected region of a pdb-file and I am tempted to simply choose the best DOPE-HR-scoring model. Yet the clustering idea does makes sense. So far, the greatest cluster of models often contains (one of) the best scoring model(s), but not in every case.
My question is therefore: Should the best model be chosen, or should the best model of the greatest cluster be chosen?
I wonder about your opinions regarding this issue. In case anyone is voting for the clustering method: What method is easily suitable for clustering - unfortunately, the loop.model-class does not seem to have an integrated clustering option, does it?
Regards
Jan
Jan H. Löhr Univ. Hamburg, Germany
This is quite similar to the question I posted recently quoted below:
3) I also attempted to cluster the models with > dopehr_loopmodel.cluster(cluster_cut=1.5), which generated a representative > structure with the parts of the protein that remained similar in most of the > models but without the variable parts (files cluster.ini and cluster.opt). > Does it make sense to select the model that is closer to that consensus > structure? If yes is there a way to do it with Modeller? I know it can been > found with Maxcluster program. Or alternatively, do you reckon it is better > to select the model based on the normalized DOPE z-score? >
I'm also curious to read your comments.
2010/5/3 Jan H. Löhr loehr@chemie.uni-hamburg.de
> Dear Modeller users, > > according to posts in this mailing list as well as the background > information to ModLoop, the best loop-model is chosen by lowest > pseudo-energy score > (http://modbase.compbio.ucsf.edu/modloop/ - Fiser's and Sali's papers > cited > at the bottom of the page). > However, the tutorial of Modeller indicates that "it is important to note > that a most accurate approach to loop refinement requires the modeling of > hundreds of independent conformations and their clustering to select the > most representative structures of the loop" > http://www.salilab.org/modeller/tutorial/advanced.html). > > I have been comparing different loop-models generated by loop.model for a > selected region of a pdb-file and I am tempted to simply choose the best > DOPE-HR-scoring model. Yet the clustering idea does makes sense. So far, > the > greatest cluster of models often contains (one of) the best scoring > model(s), but not in every case. > > My question is therefore: Should the best model be chosen, or should the > best model of the greatest cluster be chosen? > > I wonder about your opinions regarding this issue. > In case anyone is voting for the clustering method: What method is easily > suitable for clustering - unfortunately, the loop.model-class does not seem > to have an integrated clustering option, does it? > > Regards > > Jan > > Jan H. Löhr > Univ. Hamburg, Germany > > > _______________________________________________ > modeller_usage mailing list > modeller_usage@salilab.org > https://salilab.org/mailman/listinfo/modeller_usage >
participants (2)
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Jan H. Löhr -
Thomas Evangelidis