Scoring function for automated assessment of protein structure template quality

By Yang Zhang, Jeffrey Skolnick. 2007

415 citations recorded by the source corpus.

Subfields: Materials Chemistry, Computational Biology & Bioinformatics

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Citations in the corpus

DockQ: A Quality Measure for Protein-Protein Docking Models (2016, background): “…the protein structure prediction field, where there are several widely accepted quality measures; e.g., C α -RMSD, GDT_TS [3], MaxSub [4], TM-score [5], and S-score [6], the IS-score [7] for assessing protein complex models has not achieved wide adoption by the field and the current state of the…”
lDDT: a local superposition-free score for comparing protein structures and models using distance difference tests (2013, methodology): “To overcome some of the limitations of RMSD in the context of CASP, the Global Distance Test (GDT) was introduced in CASP4 (Zemla, 2003; Zemla et al., 2001).”
I-TASSER server: new development for protein structure and function predictions (2015, background): “The structural alignments between the query and the 10 closest proteins are ranked by TM-score (32).”
Protein 3D Structure Computed from Evolutionary Sequence Variation (2011, methodology): “Accuracy of prediction of 3D structure is quantified in 3 ways: (i) using the TM score [53]; (ii) using GDT-TS [54]; and (iii) using the Pymol [81] ‘align’ routine, which reports the Ca-RMSD for a moderately trimmed set of residues after iteratively removing the worst residue pairs from consideratio”
Protein threading using residue co-variation and deep learning (2018, methodology): “Here, we evaluate the quality of a 3 D model by TM-score (Zhang and Skolnick, 2004), GDT (Zemla, 2003) and uGDT (i.e. unnormalized GDT) as the model quality.”
Improving protein structure prediction using multiple sequence-based contact predictions. (2011, methodology): “In this work, we aim to provide a systematic examination of these open questions in the framework of I-TASSER (Roy et al., 2010; Wu et al., 2007; Zhang and Skolnick, 2004a) that was designed to construct protein structures by assembling template structure fragments identified by threading (Wu and…”
Advancing RNA 3D Structure Prediction: Exploring Hierarchical and Hybrid Approaches in CASP15 (2023, background): “TM-score (Template Modeling score) 36 quantifies structural similarity between two structures by measuring their degrees of overlap following optimal alignment.”
Deep convolutional networks for quality assessment of protein folds (2018, methodology): “GDT_TS values are computed using the TM-score program (Zhang and Skolnick, 2004).”
Generating Novel, Designable, and Diverse Protein Structures by Equivariantly Diffusing Oriented Residue Clouds (2023, methodology): “Finally, we compute scTM by measuring the TM-score (Zhang & Skolnick, 2004) — a metric of structural congruence — of the OmegaFold-predicted structure with respect to the original generated structure. scTM scores range from 0 to 1, with higher numbers corresponding to increased likelihoods that an…”