Literature DB >> 18670040

Reconstruction of 3D structures from protein contact maps.

Marco Vassura1, Luciano Margara, Pietro Di Lena, Filippo Medri, Piero Fariselli, Rita Casadio.   

Abstract

The prediction of the protein tertiary structure from solely its residue sequence (the so called Protein Folding Problem) is one of the most challenging problems in Structural Bioinformatics. We focus on the protein residue contact map. When this map is assigned it is possible to reconstruct the 3D structure of the protein backbone. The general problem of recovering a set of 3D coordinates consistent with some given contact map is known as a unit-disk-graph realization problem and it has been recently proven to be NP-Hard. In this paper we describe a heuristic method (COMAR) that is able to reconstruct with an unprecedented rate (3-15 seconds) a 3D model that exactly matches the target contact map of a protein. Working with a non-redundant set of 1760 proteins, we find that the scoring efficiency of finding a 3D model very close to the protein native structure depends on the threshold value adopted to compute the protein residue contact map. Contact maps whose threshold values range from 10 to 18 Angstroms allow reconstructing 3D models that are very similar to the proteins native structure.

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Year:  2008        PMID: 18670040     DOI: 10.1109/TCBB.2008.27

Source DB:  PubMed          Journal:  IEEE/ACM Trans Comput Biol Bioinform        ISSN: 1545-5963            Impact factor:   3.710


  22 in total

1.  Towards an integrated understanding of the structural characteristics of protein residue networks.

Authors:  Susan Khor
Journal:  Theory Biosci       Date:  2011-09-27       Impact factor: 1.919

2.  Multi-Dimensional Scaling and MODELLER-Based Evolutionary Algorithms for Protein Model Refinement.

Authors:  Yan Chen; Yi Shang; Dong Xu
Journal:  Proc Congr Evol Comput       Date:  2014-07

3.  CONFOLD: Residue-residue contact-guided ab initio protein folding.

Authors:  Badri Adhikari; Debswapna Bhattacharya; Renzhi Cao; Jianlin Cheng
Journal:  Proteins       Date:  2015-06-06

4.  Improving accuracy of protein contact prediction using balanced network deconvolution.

Authors:  Hai-Ping Sun; Yan Huang; Xiao-Fan Wang; Yang Zhang; Hong-Bin Shen
Journal:  Proteins       Date:  2015-01-24

5.  Contact prediction for beta and alpha-beta proteins using integer linear optimization and its impact on the first principles 3D structure prediction method ASTRO-FOLD.

Authors:  R Rajgaria; Y Wei; C A Floudas
Journal:  Proteins       Date:  2010-06

6.  Defining an essence of structure determining residue contacts in proteins.

Authors:  R Sathyapriya; Jose M Duarte; Henning Stehr; Ioannis Filippis; Michael Lappe
Journal:  PLoS Comput Biol       Date:  2009-12-04       Impact factor: 4.475

7.  ProteinTools: a toolkit to analyze protein structures.

Authors:  Noelia Ferruz; Steffen Schmidt; Birte Höcker
Journal:  Nucleic Acids Res       Date:  2021-07-02       Impact factor: 16.971

8.  Optimal contact definition for reconstruction of contact maps.

Authors:  Jose M Duarte; Rajagopal Sathyapriya; Henning Stehr; Ioannis Filippis; Michael Lappe
Journal:  BMC Bioinformatics       Date:  2010-05-27       Impact factor: 3.169

9.  Blurring contact maps of thousands of proteins: what we can learn by reconstructing 3D structure.

Authors:  Marco Vassura; Pietro Di Lena; Luciano Margara; Maria Mirto; Giovanni Aloisio; Piero Fariselli; Rita Casadio
Journal:  BioData Min       Date:  2011-01-13       Impact factor: 2.522

10.  Predicting protein contact map using evolutionary and physical constraints by integer programming.

Authors:  Zhiyong Wang; Jinbo Xu
Journal:  Bioinformatics       Date:  2013-07-01       Impact factor: 6.937

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