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About Threpp result

Posted: Fri Nov 18, 2022 7:12 am
by zn003881
Dear IT team,
I just received the Threpp result---TPP637. I noticed the the sequence of structure models that showed on Paymol is different from the input sequence that I submit to Threpp. Could you please help to explain the difference? Thanks a lot.

Re: About Threpp result

Posted: Fri Nov 18, 2022 12:51 pm
by Azog
Dear user,

Thank you for using our Threpp. Since the sequence you submitted has relatively few homologous templates in the PDB. The model predicted by Threpp is incomplete. The A chain starts from the 60th amino acid (RPVLRS...). The B chain starts from the 94th amino acid (SSSVPS...). At present, Threpp only targets the genome of Escherichia coli. For this structure, we recommend you use TACOS (https://zhanggroup.org/TACOS/) to predict the structure of the complex. Thanks a lot.

Best wishes,
IT Team

Re: About Threpp result

Posted: Sun Nov 20, 2022 8:28 am
by Azog
Dear user,

We ran TACOS through the sequence you gave. As a result, see the link below. Please check. Thanks a lot.
https://seq2fun.dcmb.med.umich.edu/TACO ... TACOS391B/

Best wishes,
IT Team

Re: About Threpp result

Posted: Tue Nov 22, 2022 12:59 pm
by zn003881
Dear IT team,
Thank you so much for the great help.

Best

Re: About Threpp result

Posted: Tue Nov 22, 2022 3:04 pm
by zn003881
Dear IT team,
Thank you for providing the TACOS result. I noticed that the article has not been published, if it's possible could you please tell me how to analyze the C-socre, Estimated TM-score and Estimated RMSD? Thanks.

Best
J

Re: About Threpp result

Posted: Wed Nov 23, 2022 7:58 am
by Azog
Dear user,

C-score is a confidence score for estimating the quality of predicted models by I-TASSER. It is calculated based on the significance of threading template alignments and the convergence parameters of the structure assembly simulations. C-score is typically in the range of [-5,2], where a C-score of higher value signifies a model with a high confidence and vice-versa (see Yang J, Yan R, Roy A, et al. The I-TASSER Suite: protein structure and function prediction[J]. Nature methods, 2015, 12(1): 7-8.).

TM-score and RMSD are known standards for measuring structural similarity between two structures which are usually used to measure the accuracy of structure modeling when the native structure is known. In case where the native structure is not known, it becomes necessary to predict the quality of the modeling prediction, i.e. what is the distance between the predicted model and the native structures? To answer this question, we tried predicted the TM-score and RMSD of the predicted models relative the native structures based on the C-score.

In a benchmark test set of 500 non-homologous proteins, we found that C-score is highly correlated with TM-score and RMSD. Correlation coefficient of C-score of the first model with TM-score to the native structure is 0.91, while the coefficient of C-score with RMSD to the native structure is 0.75. These data actually lay the base for the reliable prediction of the TM-score and RMSD using C-score. Values reported in Column 3 & 4 are the estimated values of TM-score and RMSD based on their correlation with C-score. Here we only report the quality prediction (TM-score and RMSD) for the first model, because we found that the correlation between C-score and TM-score is weak for lower rank models. However, we list the C-score of all models just for a reference.

What is TM-score?

TM-score is a recently proposed scale for measuring the structural similarity between two structures (see Zhang and Skolnick, Scoring function for automated assessment of protein structure template quality, Proteins, 2004 57: 702-710). The purpose of proposing TM-score is to solve the problem of RMSD which is sensitive to the local error. Because RMSD is an average distance of all residue pairs in two structures, a local error (e.g. a misorientation of the tail) will araise a big RMSD value although the global topology is correct. In TM-score, however, the small distance is weighted stronger than the big distance which makes the score insensitive to the local modeling error. A TM-score >0.5 indicates a model of correct topology and a TM-score<0.17 means a random similarity. These cutoff does not depends on the protein length.

Best wishes,
IT Team

Re: About Threpp result

Posted: Thu Nov 24, 2022 8:55 am
by zn003881
Dear IT team,
Thank you so much for the great help.

Best