I am trying to do homology modeling. I thread around a thousand structures. Before performing the energy minimization, I want to identify broken structures and stitch them. What are the possible ways to do it? So basically,
1. I want to identify those structures that require loop modeling (broken structures)
2. Perform loop modeling on all those (say there are a couple of hundred structures).
3. Then perform energy minimization.
I looked at the loop modeling algorithm. It requires a loop file. But, how I create so many loop files? Is there a simpler way that says, look at the native, identify places where the target is broken and fix it by putting fragments from the native pdb?
If I'm not mistaken, there's a bunch of scripts running around which will take a structural alignment file, and then automatically create a loop file based on where the gaps in the alignment are. Unfortunately, I'm unable to locate an example in the Rosetta repository. -- But that's the general concept. You would take your alignment file, and then based on where the gaps are in the alignment you create the loops there.
That said, if you're doing homology modeling, I might recommend switching over to the new RosettaCM protocol. Even though the main improvement here is the multi-template ability, there's improvements in the protocol which means that even for a single template situation it's an improvement over the older threading/loop closure/relax single template protocol.
See https://www.rosettacommons.org/demos/latest/tutorials/rosetta_cm/rosetta_cm_tutorial and the demos directory in your local Rosetta install, for an example of how to use it. It uses the alignment file directly to figure out where/how to close the gap, so you don't need to specify a separate loops file. (Though you probably will need to spend some time making sure your alignment is good -- although you should be doing that anyway, as the quality of the alignment is directly related to the quality of the output structure - automatic, sequence-based alignments tend to be less than optimal sometimes.)