Methods for estimation of model accuracy in CASP12

被引:23
作者
Elofsson, Arne [1 ,2 ]
Joo, Keehyoung [3 ,4 ]
Keasar, Chen [5 ]
Lee, Jooyoung [3 ,6 ]
Maghrabi, Ali H. A. [7 ]
Manavalan, Balachandran [3 ,6 ]
McGuffin, Liam J. [7 ]
Hurtado, David Menendez [1 ,2 ]
Mirabello, Claudio [8 ]
Pilstal, Robert [8 ]
Sidi, Tomer [5 ]
Uziela, Karolis [1 ,2 ]
Wallner, Bjorn [8 ]
机构
[1] Stockholm Univ, Dept Biochem & Biophys, Box 1031, S-17121 Solna, Sweden
[2] Stockholm Univ, Sci Life Lab, Box 1031, S-17121 Solna, Sweden
[3] Korea Inst Adv Study, Ctr Silico Prot Sci, Seoul 130722, South Korea
[4] Korea Inst Adv Study, Ctr Adv Computat, Seoul 130722, South Korea
[5] Ben Gurion Univ Negev, Dept Comp Sci, Beer Sheva, Israel
[6] Korea Inst Adv Study, Sch Computat Sci, Seoul 130722, South Korea
[7] Univ Reading, Sch Biol Sci, Reading RG6 6AS, Berks, England
[8] Linkoping Univ, Bioinformat Div, Dept Phys Chem & Biol, S-58183 Linkoping, Sweden
基金
新加坡国家研究基金会; 以色列科学基金会; 瑞典研究理事会;
关键词
CASP; consensus predictions; estimates of model accuracy; machine learning; protein structure prediction; quality assessment; PROTEIN-STRUCTURE PREDICTION; QUALITY ASSESSMENT; FOLD RECOGNITION; STRUCTURAL MODELS; MODFOLD SERVER; ENERGY TERMS; CONSENSUS; INTFOLD; PCONS; SCORE;
D O I
10.1002/prot.25395
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Methods to reliably estimate the quality of 3D models of proteins are essential drivers for the wide adoption and serious acceptance of protein structure predictions by life scientists. In this article, the most successful groups in CASP12 describe their latest methods for estimates of model accuracy (EMA). We show that pure single model accuracy estimation methods have shown clear progress since CASP11; the 3 top methods (MESHI, ProQ3, SVMQA) all perform better than the top method of CASP11 (ProQ2). Although the pure single model accuracy estimation methods outperform quasi-single (ModFOLD6 variations) and consensus methods (Pcons, ModFOLDclust2, Pcomb-domain, and Wallner) in model selection, they are still not as good as those methods in absolute model quality estimation and predictions of local quality. Finally, we show that when using contact-based model quality measures (CAD, lDDT) the single model quality methods perform relatively better.
引用
收藏
页码:361 / 373
页数:13
相关论文
共 55 条
[31]   The ModFOLD4 server for the quality assessment of 3D protein models [J].
McGuffin, Liam J. ;
Buenavista, Maria T. ;
Roche, Daniel B. .
NUCLEIC ACIDS RESEARCH, 2013, 41 (W1) :W368-W372
[32]   Automated tertiary structure prediction with accurate local model quality assessment using the IntFOLD-TS method [J].
McGuffin, Liam J. ;
Roche, Daniel B. .
PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS, 2011, 79 :137-146
[33]   Rapid model quality assessment for protein structure predictions using the comparison of multiple models without structural alignments [J].
McGuffin, Liam J. ;
Roche, Daniel B. .
BIOINFORMATICS, 2010, 26 (02) :182-188
[34]   Prediction of global and local model quality in CASP8 using the ModFOLD server [J].
McGuffin, Liam J. .
PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS, 2009, 77 :185-190
[35]  
McGuffin LJ, 2017, PROTEINS, DOI [10. 1002/prot. 25360, DOI 10.1002/PR0T.25360]
[36]   Purely Structural Protein Scoring Functions Using Support Vector Machine and Ensemble Learning [J].
Mirzaei, Shokoufeh ;
Sidi, Tomer ;
Keasar, Chen ;
Crivelli, Silvia .
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS, 2019, 16 (05) :1515-1523
[37]   AN ANALYSIS OF INCORRECTLY FOLDED PROTEIN MODELS - IMPLICATIONS FOR STRUCTURE PREDICTIONS [J].
NOVOTNY, J ;
BRUCCOLERI, R ;
KARPLUS, M .
JOURNAL OF MOLECULAR BIOLOGY, 1984, 177 (04) :787-818
[38]   CAD-score: A new contact area difference-based function for evaluation of protein structural models [J].
Olechnovic, Kliment ;
Kulberkyte, Eleonora ;
Venclovas, Ceslovas .
PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS, 2013, 81 (01) :149-162
[39]   Improved model quality assessment using ProQ2 [J].
Ray, Arjun ;
Lindahl, Erik ;
Wallner, Bjorn .
BMC BIOINFORMATICS, 2012, 13
[40]   The IntFOLD server: an integrated web resource for protein fold recognition, 3D model quality assessment, intrinsic disorder prediction, domain prediction and ligand binding site prediction [J].
Roche, Daniel B. ;
Buenavista, Maria T. ;
Tetchner, Stuart J. ;
McGuffin, Liam J. .
NUCLEIC ACIDS RESEARCH, 2011, 39 :W171-W176