Hello, I have 10,000 models of a 5 chain protein assembly (1SAC.pdb). I need to rank them based on their nativeness (RMSD vs. 1sac.pdb). I have tried multiple tools for this, profitV3.1, maxcluster etc but in all cases I have a problem where models that superimpose very well with the native structure by eye (and which should be native) give very poor rmsd and will therefore be classified as non-native. Conversely, some models which poorly align by eye have a better rmsd with the native structure. Accordingly, I can run the programs but I do not trust their rmsd rankings.
I have tried joining the chains, specifying zones, and iterative fitting but in all cases I have many good models with low scores and many poor models with higher scores. I have been using these tools for some time and never had any problems with monomers and heterodimers. This protein is a homopentamer, I think this is significant in some way.
Any clues out there??