Literature DB >> 10328269

Identification of structural domains in proteins by a graph heuristic.

L Wernisch1, M Hunting, S J Wodak.   

Abstract

A novel automatic procedure for identifying domains from protein atomic coordinates is presented. The procedure, termed STRUDL (STRUctural Domain Limits), does not take into account information on secondary structures and handles any number of domains made up of contiguous or non-contiguous chain segments. The core algorithm uses the Kernighan-Lin graph heuristic to partition the protein into residue sets which display minimum interactions between them. These interactions are deduced from the weighted Voronoi diagram. The generated partitions are accepted or rejected on the basis of optimized criteria, representing basic expected physical properties of structural domains. The graph heuristic approach is shown to be very effective, it approximates closely the exact solution provided by a branch and bound algorithm for a number of test proteins. In addition, the overall performance of STRUDL is assessed on a set of 787 representative proteins from the Protein Data Bank by comparison to domain definitions in the CATH protein classification. The domains assigned by STRUDL agree with the CATH assignments in at least 81% of the tested proteins. This result is comparable to that obtained previously using PUU (Holm and Sander, Proteins 1994;9:256-268), the only other available algorithm designed to identify domains with any number of non-contiguous chain segments. A detailed discussion of the structures for which our assignments differ from those in CATH brings to light some clear inconsistencies between the concept of structural domains based on minimizing inter-domain interactions and that of delimiting structural motifs that represent acceptable folding topologies or architectures. Considering both concepts as complementary and combining them in a layered approach might be the way forward.

Mesh:

Year:  1999        PMID: 10328269

Source DB:  PubMed          Journal:  Proteins        ISSN: 0887-3585


  8 in total

1.  Improving the performance of DomainParser for structural domain partition using neural network.

Authors:  Jun-tao Guo; Dong Xu; Dongsup Kim; Ying Xu
Journal:  Nucleic Acids Res       Date:  2003-02-01       Impact factor: 16.971

Review 2.  The Landscape of Intertwined Associations in Homooligomeric Proteins.

Authors:  Shoshana J Wodak; Anatoly Malevanets; Stephen S MacKinnon
Journal:  Biophys J       Date:  2015-09-01       Impact factor: 4.033

3.  DDOMAIN: Dividing structures into domains using a normalized domain-domain interaction profile.

Authors:  Hongyi Zhou; Bin Xue; Yaoqi Zhou
Journal:  Protein Sci       Date:  2007-05       Impact factor: 6.725

4.  Comparative docking study of anibamine as the first natural product CCR5 antagonist in CCR5 homology models.

Authors:  Guo Li; Kendra M Haney; Glen E Kellogg; Yan Zhang
Journal:  J Chem Inf Model       Date:  2009-01       Impact factor: 4.956

5.  Graph theoretic network analysis reveals protein pathways underlying cell death following neurotropic viral infection.

Authors:  Sourish Ghosh; G Vinodh Kumar; Anirban Basu; Arpan Banerjee
Journal:  Sci Rep       Date:  2015-09-25       Impact factor: 4.379

6.  Bhageerath-H: a homology/ab initio hybrid server for predicting tertiary structures of monomeric soluble proteins.

Authors:  B Jayaram; Priyanka Dhingra; Avinash Mishra; Rahul Kaushik; Goutam Mukherjee; Ankita Singh; Shashank Shekhar
Journal:  BMC Bioinformatics       Date:  2014-12-08       Impact factor: 3.169

7.  An ambiguity principle for assigning protein structural domains.

Authors:  Guillaume Postic; Yassine Ghouzam; Romain Chebrek; Jean-Christophe Gelly
Journal:  Sci Adv       Date:  2017-01-13       Impact factor: 14.136

8.  Assignment of structural domains in proteins using diffusion kernels on graphs.

Authors:  Mohammad Taheri-Ledari; Amirali Zandieh; Seyed Peyman Shariatpanahi; Changiz Eslahchi
Journal:  BMC Bioinformatics       Date:  2022-09-08       Impact factor: 3.307

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.