Literature DB >> 11276080

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

N Kannan1, S Selvaraj, M M Gromiha, S Vishveshwara.   

Abstract

The alpha/beta barrel fold is adopted by most enzymes performing a variety of catalytic reactions, but with very low sequence similarity. In order to understand the stabilizing interactions important in maintaining the alpha/beta barrel fold, we have identified residue clusters in a dataset of 36 alpha/beta barrel proteins that have less than 10% sequence identity within themselves. A graph theoretical algorithm is used to identify backbone clusters. This approach uses the global information of the nonbonded interaction in the alpha/beta barrel fold for the clustering procedure. The nonbonded interactions are represented mathematically in the form of an adjacency matrix. On diagonalizing the adjacency matrix, clusters and cluster centers are obtained from the highest eigenvalue and its corresponding vector components. Residue clusters are identified in the strand regions forming the beta barrel and are topologically conserved in all 36 proteins studied. The residues forming the cluster in each of the alpha/beta protein are also conserved among the sequences belonging to the same family. The cluster centers are found to occur in the middle of the strands or in the C-terminal of the strands. In most cases, the residues forming the clusters are part of the active site or are located close to the active site. The folding nucleus of the alpha/beta fold is predicted based on hydrophobicity index evaluation of residues and identification of cluster centers. The predicted nucleation sites are found to occur mostly in the middle of the strands. Proteins 2001;43:103-112. Copyright 2001 Wiley-Liss, Inc.

Mesh:

Year:  2001        PMID: 11276080     DOI: 10.1002/1097-0134(20010501)43:2<103::aid-prot1022>3.0.co;2-x

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


  6 in total

1.  Role of hydrophobic clusters and long-range contact networks in the folding of (alpha/beta)8 barrel proteins.

Authors:  S Selvaraj; M Michael Gromiha
Journal:  Biophys J       Date:  2003-03       Impact factor: 4.033

2.  Automatic generation and evaluation of sparse protein signatures for families of protein structural domains.

Authors:  Matthew J Blades; Jon C Ison; Ranjeeva Ranasinghe; John B C Findlay
Journal:  Protein Sci       Date:  2005-01       Impact factor: 6.725

3.  Understanding protein structure from a percolation perspective.

Authors:  Dhruba Deb; Saraswathi Vishveshwara; Smitha Vishveshwara
Journal:  Biophys J       Date:  2009-09-16       Impact factor: 4.033

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

Authors:  Sumudu P Leelananda; Robert L Jernigan; Andrzej Kloczkowski
Journal:  J Comput Biol       Date:  2016-05       Impact factor: 1.479

5.  Functional clustering of yeast proteins from the protein-protein interaction network.

Authors:  Taner Z Sen; Andrzej Kloczkowski; Robert L Jernigan
Journal:  BMC Bioinformatics       Date:  2006-07-24       Impact factor: 3.169

6.  MegaMotifBase: a database of structural motifs in protein families and superfamilies.

Authors:  Ganesan Pugalenthi; P N Suganthan; R Sowdhamini; Saikat Chakrabarti
Journal:  Nucleic Acids Res       Date:  2007-10-11       Impact factor: 16.971

  6 in total

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