Job id S657705: two questions
Posted: Mon Nov 29, 2021 9:29 pm
I am analyzing a bacterial outer membrane protein that has pore-forming activity. We have considerable experimental data identifying the primary surface-exposed antigenic epitope in this protein. Unfortunately, there is little consensus in the literature on the potential structure of this protein, which is why I am using I-TASSER in the first place. I am trying to reconcile our experimental data with I-TASSER results. I have 2 questions:
1. Is it possible to generate further analysis of predicted models other than Model #1? In our case, Model #2 shows a more reliable C-score than Model #1 and seems to be a better fit with our data. It would be helpful to get other analytical information on this model as was provided for model #1, such as TM-score and RMSD. Importantly, it would be most helpful to have information on the further categories in the I-TASSER output: similar structures in PDB; and various predicted functions.
2. We also submitted the protein through C-I-TASSER (Job ID CIT 2898). I note that the two algorithms generate a similar, but definitely not identical set of predictive models. Do you have some suggestion as to how to interpret these differing models?
I am on campus here at U of M, and can be available for in person or Zoom meetings to discuss these issues or if you need more information for your reply. Thanks for your attention.
Sincerely,
Chris Fenno
1. Is it possible to generate further analysis of predicted models other than Model #1? In our case, Model #2 shows a more reliable C-score than Model #1 and seems to be a better fit with our data. It would be helpful to get other analytical information on this model as was provided for model #1, such as TM-score and RMSD. Importantly, it would be most helpful to have information on the further categories in the I-TASSER output: similar structures in PDB; and various predicted functions.
2. We also submitted the protein through C-I-TASSER (Job ID CIT 2898). I note that the two algorithms generate a similar, but definitely not identical set of predictive models. Do you have some suggestion as to how to interpret these differing models?
I am on campus here at U of M, and can be available for in person or Zoom meetings to discuss these issues or if you need more information for your reply. Thanks for your attention.
Sincerely,
Chris Fenno