Evaluation of residue-residue contact predictions in CASP9
By Bohdan Monastyrskyy, Krzysztof Fidelis, Anna Tramontano, Andriy Kryshtafovych. 2011
95 citations recorded by the source corpus.
This work presents the results of the assessment of the intramolecular residue–residue contact predictions submitted to CASP9. The methodology for the assessment does not differ from that used in previous CASPs, with two basic evaluation measures being the precision in recognizing contacts and the difference between the distribution of distances in the subset of predicted contact pairs versus all pairs of residues in the structure. The emphasis is placed on the prediction of long‐range contacts (i.e., contacts between residues separated by at least 24 residues along sequence) in target proteins that cannot be easily modeled by homology. Although there is considerable activity in the field, the current analysis reports no discernable progress since CASP8. Proteins 2011; © 2011 Wiley‐Liss, Inc.
Subfields: Materials Chemistry, Molecular Biology, Computational Biology & Bioinformatics
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In Materials Chemistry
- Yang Zhang
- Jianlin Cheng
- Robin Pearce
- Badri Adhikari
- Andriy Kryshtafovych
- Debswapna Bhattacharya
- Renzhi Cao
- Bohdan Monastyrskyy
In Molecular Biology
- Yang Zhang
- Jianlin Cheng
- Robin Pearce
- Badri Adhikari
- Jinbo Xu
- Andriy Kryshtafovych
- Chengxin Zhang
- Debswapna Bhattacharya
In Computational Biology & Bioinformatics
- Yang Zhang
- Jianlin Cheng
- Robin Pearce
- Badri Adhikari
- Jinbo Xu
- Andriy Kryshtafovych
- Debswapna Bhattacharya
- Renzhi Cao
Citations in the corpus
- Toward optimal fragment generations for ab initio protein structure assembly (2012, methodology): “46,48 In the table, distance profile-based method outperforms the machine-learning-based methods for short and medium-range contacts and has a similar performance for the long-range contact prediction.”
- Protein structure prediction from sequence variation (2012, neutral): “…contacts using three-dimensional information with machine-learning techniques, such as support vector machines, random forests and neural networks, but contact prediction accuracy remained “still quite low” 10 with substantial improvements to models achieved only for some small proteins 11,12 .”
- ConEVA: a toolbox for comprehensive assessment of protein contacts (2016, background): “Similarly, it is widely accepted that long-range contacts [12, 14, 15] are the most useful of the three contact types (short-, medium-, and long-range), but some structural domains introduced in CASP like T0765-D1, T0709-D1, T0711-D1, T0756-D2, T0700-D1 have very few or no long-range contacts at all”
- Assessing the accuracy of contact predictions in CASP13 (2019, background): “As early as the second CASP meeting in 1996,(2,3) contact predictions were made and assessed.(4-13) In general, protein structures are very well packed,(14) with densities comparable”
- CONFOLD: Residue-Residue Contact-guided ab initio Protein Folding (2015, methodology): “We used two standard protein data sets for our experiments: (1) 15 test proteins of different fold classes ranging from 48 to 248 residues used in EVFOLD,9 and (2) 150 diverse globular proteins with average length of 145 residues used in FRAGFOLD.”
- De novo Protein Structure Prediction by Coupling Contact With Distance Profile (2020, background): “Currently, researchers consider that the top L , L= 2 , L= 5 and L= 10 are reasonable, where L is the length of the protein sequence, and the rank of contacts is determined by the prediction confidence score [15], [16], [48].”
- Evaluation of residue-residue contact prediction in CASP10 (2013, methodology): “The prediction of residue-residue contacts has been a part of the CASP experiment since CASP2 39 (1996), however, the prediction format and the assessment procedures have been standardized only in CASP6 – CASP9 40–43 .”
- Deep architectures for protein contact map prediction (2012, methodology): “, 2009) and CASP9 (Monastyrskyy et al., 2011) for contact prediction”