Automated structure prediction of weakly homologous proteins on a genomic scale.

By Yang Zhang, Jeffrey Skolnick. 2004

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In Molecular Biology

Citations in the corpus

Toward optimal fragment generations for ab initio protein structure assembly (2012, methodology): “…that is, sequence identity 30%, which has been mostly often used for excluding homologous templates in protein structure-prediction studies.22 ,47 The resultant contact accuracy of the fragments outperforms the machine-learning-based predictions for short-and medium-range contacts and…”
TM-align: a protein structure alignment algorithm based on the TM-score (2005, critical): “Figure 5 shows a typical example of this situation for 1c0fS, where the TASSER model has two tails and one loop incorrectly predicted.”
LOMETS: A local meta-threading-server for protein structure prediction (2007, methodology): “The threshold cutoff is determined by the minimization of the false positive (high Z-score but with low TM-score) and false negative rate (low Z-score but with high TM-score) of each threading program based on an independent benchmark set of 1489 non-redundant proteins (12).”
Ab Initio Protein Structure Assembly Using Continuous Structure Fragments and Optimized Knowledge-based Force Field (2012, background): “In Rosetta,14 TASSER,15 and I-TASSER,16 fragment sequences have the structures cop-ied from PDB templates which are kept rigid during the simulation.”
Automated protein structure modeling in CASP9 by I-TASSER pipeline combined with QUARK-based ab initio folding and FG-MD-based structure refinement (2011, methodology): “In I-TASSER, continuous fragments are excised from threading templates and exploited for assembling full-length models,23,36 while the unaligned loop regions are built by ab initio modeling procedure37 on a lattice sys-tem.”
FragQA: predicting local fragment quality of a sequence-structure alignment. (2007, neutral): “Even for those FM (free modeling) targets, a structural model generated by protein threading usually contains some good local regions, although the overall conformation of the model is incorrect [21].”
Template‐based modeling and free modeling by I‐TASSER in CASP7 (2007, methodology): “14 Typical to what is often found is that, the final models are closer to the templates rather than to the native structures15,16; (3) for the sequences without appropriate solved template structures, how to build models of correct topology/fold from scratch.”
MUSTER: Improving protein sequence profile–profile alignments by using multiple sources of structure information (2008, methodology): “For an independent set of 2234 nonhomologous proteins used by Zhang and Skolnick,49,50 the overall correlation coefficient between the predicted SA q ( i ) and the real exposed area assigned by STRIDE45 is 0.71, while the same correlation for the widely-used Hopp-Woods51 and Kyte-Doolittle 52 hydrop”
I-TASSER: Fully automated protein structure prediction in CASP8 (2009, methodology): “Continuous fragments excised from the threading templates are used to assemble full-length models15,36 with unaligned loop regions built by ab initio modeling in a lattice system.”
Ab initio protein structure prediction using chunk-TASSER. (2007, methodology): “Ab initio protein structure prediction is not only useful fo r providing low resolution structures that help the annotation of protein function(13, 156), but is also fundamentally important for understanding the mechanism of protein folding(17).”
Ab initio modeling of small proteins by iterative TASSER simulations (2007, neutral): “According to Zhang and Skolnick [22], TM-score = 1 indicates two identical structures and TM-score < 0.17 indicates random structure pairs.”
Progress and challenges in protein structure prediction. (2008, methodology): “In the recent CASP7 experiment [23 ], however, Zhang-Server (an automated server based on profile–profile threading and I-TASSER structure refinement [31 ]) clearly outperforms others (including the meta-servers which include it as an input [29 ]).”
Deep learning techniques have significantly impacted protein structure prediction and protein design. (2021, background): “TASSER represents one of the ﬁrst approaches that showed a consistent ability to draw the templates closer to the native structure [7].”
Protein Structure Prediction: Is It Useful? (2009, neutral): “developed by Zhang and Skolnick [34].”
MUFOLD: A new solution for protein 3D structure prediction (2010, background): “…the PDB that has a root-mean-square deviation (RMSD) 4 A˚ for 90% of its residues regardless of whether it is evolutionarily related to other proteins with solved structures,15 which suggests that the protein structure prediction problem can be solved in principle by using template-based methods.”
Protein Structure and Function Prediction Using I-TASSER (2015, methodology): “The lowest-free-energy conformations are identiﬁed by SPICKER (Zhang and Skolnick, 2004b) through the clustering of the Monte Carlo simulation trajectories.”