Template-based protein structure prediction in CASP11 and retrospect of I-TASSER in the last decade

By Jianyi Yang, Wen-Xuan Zhang, Baoji He, S. Walker, Hongjiu Zhang, Brandon Govindarajoo, Jouko Virtanen, Zhidong Xue, Hongbin Shen, Yang Zhang. 2015

58 citations recorded by the source corpus.

We report the structure prediction results of a new composite pipeline for template‐based modeling (TBM) in the 11th CASP experiment. Starting from multiple structure templates identified by LOMETS based meta‐threading programs, the QUARK ab initio folding program is extended to generate initial full‐length models under strong constraints from template alignments. The final atomic models are then constructed by I‐TASSER based fragment reassembly simulations, followed by the fragment‐guided molecular dynamic simulation and the MQAP‐based model selection. It was found that the inclusion of QUARK‐TBM simulations as an intermediate modeling step could help improve the quality of the I‐TASSER models for both Easy and Hard TBM targets. Overall, the average TM‐score of the first I‐TASSER model is 12% higher than that of the best LOMETS templates, with the RMSD in the same threading‐aligned regions reduced from 5.8 to 4.7 Å. Nevertheless, there are nearly 18% of TBM domains with the templates deteriorated by the structure assembly pipeline, which may be attributed to the errors of secondary structure and domain orientation predictions that propagate through and degrade the procedures of template identification and final model selections. To examine the record of progress, we made a retrospective report of the I‐TASSER pipeline in the last five CASP experiments (CASP7‐11). The data show no clear progress of the LOMETS threading programs over PSI‐BLAST; but obvious progress on structural improvement relative to threading templates was witnessed in recent CASP experiments, which is probably attributed to the integration of the extended ab initio folding simulation with the threading assembly pipeline and the introduction of atomic‐level structure refinements following the reduced modeling simulations. Proteins 2016; 84(Suppl 1):233–246. © 2015 Wiley Periodicals, Inc.

Subfields: Materials Chemistry, Molecular Biology

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Materials Chemistry

In Molecular Biology

Citations in the corpus

Improving homology modeling from low-sequence identity templates in Rosetta: A case study in GPCRs (2020, background): “Servers for the prediction of GPCRs from multiple templates are available including GPCR-ModSim [12], GPCR-I-Tasser [13], GPCRM [14], GPCR-SSFE [15], and GPCRdb [16].”
Computational protein structure refinement: Almost there, yet still so far to go (2017, methodology): “27 – 36 Structure re ﬁ nement methods are widely used already to derive atomistic structures from nuclear magnetic resonance (NMR) restraints 37,38 and during crystallographic structure determination 39 – 41 either de novo or via molecular replacement.”