Literature DB >> 12855452

Protein structure prediction via combinatorial assembly of sub-structural units.

Yuval Inbar1, Hadar Benyamini, Ruth Nussinov, Haim J Wolfson.   

Abstract

Following the hierarchical nature of protein folding, we propose a three-stage scheme for the prediction of a protein structure from its sequence. First, the sequence is cut to fragments that are each assigned a structure. Second, the assigned structures are combinatorially assembled to form the overall 3D organization. Third, highly ranked predicted arrangements are completed and refined. This work focuses on the second stage of this scheme: the combinatorial assembly. We present CombDock, a combinatorial docking algorithm. CombDock gets an ordered set of protein sub-structures and predicts the inter-contacts that define their overall organization. We reduce the combinatorial assembly to a graph-theory problem, and give a heuristic polynomial solution to this computationally hard problem. We applied CombDock to various examples of structural units of two types: protein domains and building blocks, which are relatively stable sub-structures of domains. Moreover, we tested CombDock using increasingly distorted input, where the native structural units were replaced by similarly folded units extracted from homologous proteins and, in the more difficult cases, from globally unrelated proteins. The algorithm is robust, showing low sensitivity to input distortion. This suggests that CombDock is a useful tool in protein structure prediction that may be applied to large target proteins.

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Substances:

Year:  2003        PMID: 12855452     DOI: 10.1093/bioinformatics/btg1020

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  15 in total

1.  Reducing the computational complexity of protein folding via fragment folding and assembly.

Authors:  Nurit Haspel; Chung-Jung Tsai; Haim Wolfson; Ruth Nussinov
Journal:  Protein Sci       Date:  2003-06       Impact factor: 6.725

2.  BioInfo3D: a suite of tools for structural bioinformatics.

Authors:  Maxim Shatsky; Oranit Dror; Dina Schneidman-Duhovny; Ruth Nussinov; Haim J Wolfson
Journal:  Nucleic Acids Res       Date:  2004-07-01       Impact factor: 16.971

3.  Union of geometric constraint-based simulations with molecular dynamics for protein structure prediction.

Authors:  Tyler J Glembo; S Banu Ozkan
Journal:  Biophys J       Date:  2010-03-17       Impact factor: 4.033

4.  "Similarity trap" in protein-protein interactions could be carcinogenic: simulations of p53 core domain complexed with 53BP1 and BRCA1 BRCT domains.

Authors:  Jin Liu; Yongping Pan; Buyong Ma; Ruth Nussinov
Journal:  Structure       Date:  2006-12       Impact factor: 5.006

5.  Improving strand pairing prediction through exploring folding cooperativity.

Authors:  Jieun Jeong; Piotr Berman; Teresa M Przytycka
Journal:  IEEE/ACM Trans Comput Biol Bioinform       Date:  2008 Oct-Dec       Impact factor: 3.710

6.  SymmRef: a flexible refinement method for symmetric multimers.

Authors:  Efrat Mashiach-Farkash; Ruth Nussinov; Haim J Wolfson
Journal:  Proteins       Date:  2011-06-30

7.  Modeling protein assemblies in the proteome.

Authors:  Guray Kuzu; Ozlem Keskin; Ruth Nussinov; Attila Gursoy
Journal:  Mol Cell Proteomics       Date:  2014-01-20       Impact factor: 5.911

8.  Prediction of protein tertiary structures using MUFOLD.

Authors:  Jingfen Zhang; Zhiquan He; Qingguo Wang; Bogdan Barz; Ioan Kosztin; Yi Shang; Dong Xu
Journal:  Methods Mol Biol       Date:  2012

9.  MUFOLD: A new solution for protein 3D structure prediction.

Authors:  Jingfen Zhang; Qingguo Wang; Bogdan Barz; Zhiquan He; Ioan Kosztin; Yi Shang; Dong Xu
Journal:  Proteins       Date:  2010-04

10.  Designing succinct structural alphabets.

Authors:  Shuai Cheng Li; Dongbo Bu; Xin Gao; Jinbo Xu; Ming Li
Journal:  Bioinformatics       Date:  2008-07-01       Impact factor: 6.937

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