Literature DB >> 27159634

Predicting Designability of Small Proteins from Graph Features of Contact Maps.

Sumudu P Leelananda1, Robert L Jernigan2,3, Andrzej Kloczkowski1,4.   

Abstract

Highly designable structures can be distinguished based on certain geometric graphical features of the interactions, confirming the fact that the topology of a protein structure and its residue-residue interaction network are important determinants of its designability. The most designable structures and least designable structures obtained for sets of proteins having the same number of residues are compared. It is shown that the most designable structures predicted by the graph features of the contact diagrams are more densely packed, whereas the poorly designable structures are more open structures or structures that are loosely packed. Interestingly enough, it can also be seen that the highly designable identified are also common structural motifs found in nature.

Keywords:  contact maps; designability; graph features; interaction network; lattice models; machine learning; network; prediction; structure

Mesh:

Substances:

Year:  2016        PMID: 27159634      PMCID: PMC4876523          DOI: 10.1089/cmb.2015.0209

Source DB:  PubMed          Journal:  J Comput Biol        ISSN: 1066-5277            Impact factor:   1.479


  31 in total

1.  Clusters in alpha/beta barrel proteins: implications for protein structure, function, and folding: a graph theoretical approach.

Authors:  N Kannan; S Selvaraj; M M Gromiha; S Vishveshwara
Journal:  Proteins       Date:  2001-05-01

2.  Backbone cluster identification in proteins by a graph theoretical method.

Authors:  S M Patra; S Vishveshwara
Journal:  Biophys Chem       Date:  2000-02-14       Impact factor: 2.352

3.  Identifying proteins of high designability via surface-exposure patterns.

Authors:  Eldon G Emberly; Jonathan Miller; Chen Zeng; Ned S Wingreen; Chao Tang
Journal:  Proteins       Date:  2002-05-15

4.  Small-world communication of residues and significance for protein dynamics.

Authors:  Ali Rana Atilgan; Pelin Akan; Canan Baysal
Journal:  Biophys J       Date:  2004-01       Impact factor: 4.033

5.  A network representation of protein structures: implications for protein stability.

Authors:  K V Brinda; Saraswathi Vishveshwara
Journal:  Biophys J       Date:  2005-09-08       Impact factor: 4.033

6.  The network of sequence flow between protein structures.

Authors:  Leonid Meyerguz; Jon Kleinberg; Ron Elber
Journal:  Proc Natl Acad Sci U S A       Date:  2007-06-27       Impact factor: 11.205

Review 7.  Proteins as networks: usefulness of graph theory in protein science.

Authors:  Arun Krishnan; Joseph P Zbilut; Masaru Tomita; Alessandro Giuliani
Journal:  Curr Protein Pept Sci       Date:  2008-02       Impact factor: 3.272

8.  Comparative analysis of the packing topology of structurally important residues in helical membrane and soluble proteins.

Authors:  Vagmita Pabuwal; Zhijun Li
Journal:  Protein Eng Des Sel       Date:  2008-12-02       Impact factor: 1.650

9.  Protein design: a perspective from simple tractable models

Authors: 
Journal:  Fold Des       Date:  1998

10.  Optimized null model for protein structure networks.

Authors:  Tijana Milenković; Ioannis Filippis; Michael Lappe; Natasa Przulj
Journal:  PLoS One       Date:  2009-06-26       Impact factor: 3.240

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.