trRosetta results for job TR023658 (test)

[Click on TR023658_results.tar.bz2 to download the tarball file including all modeling results listed on this page]

   Predicted Structure Models

Download Model 1 (colored by rainbow from N to C terminus)
Estimated TM-score: 0.920
  

Summary of predicted models

  • The confidence of the predicted model on the left is very high (with esitmated TM-score=0.920).
  • The model was built by trRosetta with restraints from both deep learning and homologous templates (shown below).
  • You can download other lower-ranked models: model2, model3, model4, model5.
  • Download the multiple sequence alignment used by trRosetta (the seqeunce database used is uniclust30_2018_08).
  • Download the predicted inter-residue distance and orientations.

  •    Predicted 2D Information
    Contact    Distance    Omega    Theta    Phi


       Templates used by trRosetta
    The templates were detected by running HHsearch against the PDB70 database.
    Query sequence:   --------10--------20--------30--------40--------50--------60--------70--------80--------90-------100-------110-------120-------
    123456789|123456789|123456789|123456789|123456789|123456789|123456789|123456789|123456789|123456789|123456789|123456789|1234567
    AMIVGLGTDIAEIERVEKALARSGENFARRILTDSELEQFHASKQQGRFLAKRFAAKEAASKALGTGIAQGVTFHDFTISHDKLGKPLLILSGQAAELASQLQVENIHLSISDERHYAMATVILERR
    Predicted secondary structure (H: Helix; S: Strand; C: Coil.):   CCSSSSSSSSSSHHHHHHHHHHHCHHHHHHHCCHHHHHHHHHCCCHHHHHHHHHHHHHHHHHHHCCCCCCCCCSSSSSSSSCCCCCCSSSSCHHHHHHHHHHCCCSSSSSSSCCCCSSSSSSSSSSC
    Predicted disordered regions (D: Disorder; .: Order):   ...............................................................................................................................
    Rank
    Template
    Confidence
    Coverage
    Identity
    E-value
    Z-score
    MODELLER
    Alignment
    AMIVGLGTDIAEIERVEKALARSGENFARRILTDSELEQFHASKQQGRFLAKRFAAKEAASKALGTGIAQGVTFHDFTISHDKLGKPLLILSGQAAELASQLQVENIHLSISDERHYAMATVILERR
    1 6QL9_D 99.8 96.1 38.6 2.3E-20 23.052 download VSNGGVGVDVELITSINV----ENDTFIERNFTPQEIEYCSAQPSVQSSFAGTWSAKEAVFKSLGVSLGGGAALKDIEIVRVNKNAPAVELHGNAKKAAEEAGVTDVKVSISHDDLQAVAVAVSTK-
    2 6QL9_A 99.8 96.1 38.6 2.3E-20 23.052 download VSNGGVGVDVELITSINV----ENDTFIERNFTPQEIEYCSAQPSVQSSFAGTWSAKEAVFKSLGVSLGGGAALKDIEIVRVNKNAPAVELHGNAKKAAEEAGVTDVKVSISHDDLQAVAVAVSTK-
    3 6QL5_D 99.8 96.1 38.6 2.3E-20 23.052 download VSNGGVGVDVELITSINV----ENDTFIERNFTPQEIEYCSAQPSVQSSFAGTWSAKEAVFKSLGVSLGGGAALKDIEIVRVNKNAPAVELHGNAKKAAEEAGVTDVKVSISHDDLQAVAVAVSTK-
    4 3QMN_N 99.8 97.6 99.2 3.9E-19 21.913 download A-IVGLGTDIAEIERVEKALARSGENFARRILTDSELEQFHASKQQGRFLAKRFAAKEAASKALGTGIAQGVTFHDFTISHDKLGKPLLILSGQAAELASQLQVENIHLSISDERHYA-ATVILER-
    5 3QMN_O 99.8 98.4 99.2 3.9E-19 21.913 download A-IVGLGTDIAEIERVEKALARSGENFARRILTDSELEQFHASKQQGRFLAKRFAAKEAASKALGTGIAQGVTFHDFTISHDKLGKPLLILSGQAAELASQLQVENIHLSISDERHYA-ATVILERR



    Reference

  • J Yang, I Anishchenko, H Park, Z Peng, S Ovchinnikov, D Baker, Improved protein structure prediction using predicted interresidue orientations, PNAS, 117: 1496-1503 (2020)