[modeller_usage] strategies for model refinement

I'm a relatively new user of modeller & successfully built a fairly nice model of a protein with 258 residues. It forms a homodimer, and has to be modeled as a dimer, because there's a very flexible loop that can easily adopt conformation that prevent dimerization if the 2nd unit isn't present. [I confirmed that by trying it].

Someone on this group suggested the Molprobity server as a way to assess model quality, for which I'm very grateful. He also suggested relaxing the structure with Rosetta, & after epic battles with python setup & my operating system, I got it up & running. Only to learn from the RosettaCommons forum that Rosetta relax doesn't scale well with chain length & isn't useful for proteins with >200 residues. I managed to get the Molprobity score down to a respectable 2.-something using lots & lots of iterations of Schrodinger Prime loop refinement & side chain minimization. It took about a week of setting up a loop, running it, checking to see if it refined, iterating 'til I could move on, etc. So I'm looking for something a bit less hands-on, if possible. Also, Schrodinger is expensive & my boss may not renew the licenses when this lot expires in March. And finally, Molprobity signaled several C-beta issues in my structure, & Schrodinger just doesn't seem to do much about those. Therefore, I'm looking for other suggestions, preferably freeware, for model refinement. I have tried some loop refinement with Modeller itself, but wasn't thrilled with the outcome. This could easily be because I couldn't find sample scripts to copy, or an explanation of how to tweak the parameters if the loop doesn't seem to be refining. If anyone can point me in those directions, I'd be grateful, too.