I used the "comparative modeling" algorithm of the online tool ROBETTA to model a protein structure (http://robetta.bakerlab.org/). The tool always generates five models, to which the ROBETTA FAQs state "In the case of homology modeling predictions, the models are ordered by the likelihood of the alignment clusters. Each alignment cluster represents a particular topology."

Thus, if I understand it correctly, the model 1 will be more likely to be the "true structure" than model 2 and model 2 will be more likely to be the "true structure" than model 3 and so on. I am wondering whether this is quantifiable or with other words: I want to know HOW MUCH MORE LIKELY is model 2 than model 1. Is it possible to get "some numbers" for this?

I have a second problem. I generated a mutant of the protein that I am trying to model and the mutation (one single point mutant) is a complete loss-of-function mutant in vivo. When I run the comparative modeling algorithm on ROBETTA for the wildtype protein I get a structure that looks very plausible (for a lot of reasons) and it is the model ranking second ("model 2"). If I use the "mutant" with the "loss-of-function" mutation" under the same conditions in the same algorithm, I also get this structure (or something VERY SIMILAR). However, this structure is now not model 2 but instead model 4. It seems to be "ranking lower" (i.e. be "less likely"?). Can I interpret these data in a way that the loss-of-function mutation makes it harder to acquire this specific fold (e.g. can I at least say the data hint in this direction)? And if yes, would it be possible to quantify this (i.e. saying HOW MUCH does the mutation interfere with folding)?

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