Recursive protein modeling: a divide and conquer strategy for protein structure prediction and its case study in CASP9

被引:0
|
作者
Cheng, Jianlin [1 ]
Eickholt, Jesse [2 ]
Wang, Zheng [2 ]
Deng, Xin [2 ]
机构
[1] Univ Missouri, Dept Comp Sci, Inst Informat, C Bond Life Sci Ctr, Columbia, MO 65211 USA
[2] Univ Missouri, Dept Comp Sci, Columbia, MO 65211 USA
来源
2011 IEEE INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICINE WORKSHOPS | 2011年
关键词
recursive protein modeling; template-free modeling; template-based modeling; CASP9; protein structure prediction; FOLD RECOGNITION; QUALITY; GENERATION; FRAGMENTS; MULTICOM; ENERGY; SERVER;
D O I
暂无
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
After decades of research, protein structure prediction remains a very challenging problem. In order to address the different levels of complexity of modeling structure, two types of modeling techniques - template-based modeling and template-free modeling - have been developed. Template-based modeling can often generate a moderate to high resolution model when a similar, homologous template structure is found for a query protein but fails if no template or only incorrect templates are found. Template-free modeling such as fragment-based assembly may generate models of moderate resolution for small proteins of low topological complexity. Seldom have the two techniques been integrated together to improve protein modeling. Here we develop a recursive protein modeling approach to selectively and collaboratively apply template-based and template-free modeling methods to model template-covered (i.e., certain) and template-free (i.e., uncertain) regions of a protein. A preliminary implementation of the approach was tested on a number of hard modeling cases during the 9th Critical Assessment of Techniques for Protein Structure Prediction (CASP9) and successfully improved the quality of modeling in most of these cases. Recursive modeling can significantly reduce the complexity of protein structure modeling and integrate template-based and template-free modeling to improve the quality and efficiency of protein structure prediction.
引用
收藏
页码:352 / 357
页数:6
相关论文
共 35 条
  • [1] RECURSIVE PROTEIN MODELING: A DIVIDE AND CONQUER STRATEGY FOR PROTEIN STRUCTURE PREDICTION AND ITS CASE STUDY IN CASP9
    Cheng, Jianlin
    Eickholt, Jesse
    Wang, Zheng
    Deng, Xin
    JOURNAL OF BIOINFORMATICS AND COMPUTATIONAL BIOLOGY, 2012, 10 (03)
  • [2] Assessment of protein structure refinement in CASP9
    MacCallum, Justin L.
    Perez, Alberto
    Schnieders, Michael J.
    Hua, Lan
    Jacobson, Matthew P.
    Dill, Ken A.
    PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS, 2011, 79 : 74 - 90
  • [3] Assessment of template based protein structure predictions in CASP9
    Mariani, Valerio
    Kiefer, Florian
    Schmidt, Tobias
    Haas, Juergen
    Schwede, Torsten
    PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS, 2011, 79 : 37 - 58
  • [4] An automatic method for CASP9 free modeling structure prediction assessment
    Cong, Qian
    Kinch, Lisa N.
    Pei, Jimin
    Shi, Shuoyong
    Grishin, Vyacheslav N.
    Li, Wenlin
    Grishin, Nick V.
    BIOINFORMATICS, 2011, 27 (24) : 3371 - 3378
  • [5] Target highlights in CASP9: Experimental target structures for the critical assessment of techniques for protein structure prediction
    Kryshtafovych, Andriy
    Moult, John
    Bartual, Sergio G.
    Bazan, J. Fernando
    Berman, Helen
    Casteel, Darren E.
    Christodoulou, Evangelos
    Everett, John K.
    Hausmann, Jens
    Heidebrecht, Tatjana
    Hills, Tanya
    Hui, Raymond
    Hunt, John F.
    Seetharaman, Jayaraman
    Joachimiak, Andrzej
    Kennedy, Michael A.
    Kim, Choel
    Lingel, Andreas
    Michalska, Karolina
    Montelione, Gaetano T.
    Otero, Jose M.
    Perrakis, Anastassis
    Pizarro, Juan C.
    van Raaij, Mark J.
    Ramelot, Theresa A.
    Rousseau, Francois
    Tong, Liang
    Wernimont, Amy K.
    Young, Jasmine
    Schwede, Torsten
    PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS, 2011, 79 : 6 - 20
  • [6] A Divide-and-Conquer Strategy for the Prediction of Protein Contact Map
    Santiesteban-Toca, Cosme E.
    Casanola-Martin, Gerardo M.
    Aguilar-Ruiz, Jesus S.
    LETTERS IN DRUG DESIGN & DISCOVERY, 2015, 12 (02) : 124 - 130
  • [7] An analysis and evaluation of the WeFold collaborative for protein structure prediction and its pipelines in CASP11 and CASP12
    Chen Keasar
    Liam J. McGuffin
    Björn Wallner
    Gaurav Chopra
    Badri Adhikari
    Debswapna Bhattacharya
    Lauren Blake
    Leandro Oliveira Bortot
    Renzhi Cao
    B. K. Dhanasekaran
    Itzhel Dimas
    Rodrigo Antonio Faccioli
    Eshel Faraggi
    Robert Ganzynkowicz
    Sambit Ghosh
    Soma Ghosh
    Artur Giełdoń
    Lukasz Golon
    Yi He
    Lim Heo
    Jie Hou
    Main Khan
    Firas Khatib
    George A. Khoury
    Chris Kieslich
    David E. Kim
    Pawel Krupa
    Gyu Rie Lee
    Hongbo Li
    Jilong Li
    Agnieszka Lipska
    Adam Liwo
    Ali Hassan A. Maghrabi
    Milot Mirdita
    Shokoufeh Mirzaei
    Magdalena A. Mozolewska
    Melis Onel
    Sergey Ovchinnikov
    Anand Shah
    Utkarsh Shah
    Tomer Sidi
    Adam K. Sieradzan
    Magdalena Ślusarz
    Rafal Ślusarz
    James Smadbeck
    Phanourios Tamamis
    Nicholas Trieber
    Tomasz Wirecki
    Yanping Yin
    Yang Zhang
    Scientific Reports, 8
  • [8] An analysis and evaluation of the WeFold collaborative for protein structure prediction and its pipelines in CASP11 and CASP12
    Keasar, Chen
    McGuffin, Liam J.
    Wallner, Bjorn
    Chopra, Gaurav
    Adhikari, Badri
    Bhattacharya, Debswapna
    Blake, Lauren
    Bortot, Leandro Oliveira
    Cao, Renzhi
    Dhanasekaran, B. K.
    Dimas, Itzhel
    Faccioli, Rodrigo Antonio
    Faraggi, Eshel
    Ganzynkowicz, Robert
    Ghosh, Sambit
    Ghosh, Soma
    Gieldon, Artur
    Golon, Lukasz
    He, Yi
    Heo, Lim
    Hou, Jie
    Khan, Main
    Khatib, Firas
    Khoury, George A.
    Kieslich, Chris
    Kim, David E.
    Krupa, Pawel
    Lee, Gyu Rie
    Li, Hongbo
    Li, Jilong
    Lipska, Agnieszka
    Liwo, Adam
    Maghrabi, Ali Hassan A.
    Mirdita, Milot
    Mirzaei, Shokoufeh
    Mozolewska, Magdalena A.
    Onel, Melis
    Ovchinnikov, Sergey
    Shah, Anand
    Shah, Utkarsh
    Sidi, Tomer
    Sieradzan, Adam K.
    Slusarz, Magdalena
    Slusarz, Rafal
    Smadbeck, James
    Tamamis, Phanourios
    Trieber, Nicholas
    Wirecki, Tomasz
    Yin, Yanping
    Zhang, Yang
    SCIENTIFIC REPORTS, 2018, 8
  • [9] Automated protein structure modeling in CASP9 by I-TASSER pipeline combined with QUARK-based ab initio folding and FG-MD-based structure refinement
    Xu, Dong
    Zhang, Jian
    Roy, Ambrish
    Zhang, Yang
    PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS, 2011, 79 : 147 - 160
  • [10] Protein Tertiary Structure Modeling Driven by Deep Learning and Contact Distance Prediction in CASP13
    Cheng, Jianlin
    ACM-BCB'19: PROCEEDINGS OF THE 10TH ACM INTERNATIONAL CONFERENCE ON BIOINFORMATICS, COMPUTATIONAL BIOLOGY AND HEALTH INFORMATICS, 2019, : 551 - 551