Literature DB >> 16150969

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

K V Brinda1, Saraswathi Vishveshwara.   

Abstract

This study views each protein structure as a network of noncovalent connections between amino acid side chains. Each amino acid in a protein structure is a node, and the strength of the noncovalent interactions between two amino acids is evaluated for edge determination. The protein structure graphs (PSGs) for 232 proteins have been constructed as a function of the cutoff of the amino acid interaction strength at a few carefully chosen values. Analysis of such PSGs constructed on the basis of edge weights has shown the following: 1), The PSGs exhibit a complex topological network behavior, which is dependent on the interaction cutoff chosen for PSG construction. 2), A transition is observed at a critical interaction cutoff, in all the proteins, as monitored by the size of the largest cluster (giant component) in the graph. Amazingly, this transition occurs within a narrow range of interaction cutoff for all the proteins, irrespective of the size or the fold topology. And 3), the amino acid preferences to be highly connected (hub frequency) have been evaluated as a function of the interaction cutoff. We observe that the aromatic residues along with arginine, histidine, and methionine act as strong hubs at high interaction cutoffs, whereas the hydrophobic leucine and isoleucine residues get added to these hubs at low interaction cutoffs, forming weak hubs. The hubs identified are found to play a role in bringing together different secondary structural elements in the tertiary structure of the proteins. They are also found to contribute to the additional stability of the thermophilic proteins when compared to their mesophilic counterparts and hence could be crucial for the folding and stability of the unique three-dimensional structure of proteins. Based on these results, we also predict a few residues in the thermophilic and mesophilic proteins that can be mutated to alter their thermal stability.

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Year:  2005        PMID: 16150969      PMCID: PMC1366981          DOI: 10.1529/biophysj.105.064485

Source DB:  PubMed          Journal:  Biophys J        ISSN: 0006-3495            Impact factor:   4.033


  25 in total

1.  Identification of side-chain clusters in protein structures by a graph spectral method.

Authors:  N Kannan; S Vishveshwara
Journal:  J Mol Biol       Date:  1999-09-17       Impact factor: 5.469

2.  The Protein Data Bank.

Authors:  H M Berman; J Westbrook; Z Feng; G Gilliland; T N Bhat; H Weissig; I N Shindyalov; P E Bourne
Journal:  Nucleic Acids Res       Date:  2000-01-01       Impact factor: 16.971

3.  Structural differences between mesophilic, moderately thermophilic and extremely thermophilic protein subunits: results of a comprehensive survey.

Authors:  A Szilágyi; P Závodszky
Journal:  Structure       Date:  2000-05-15       Impact factor: 5.006

4.  Three key residues form a critical contact network in a protein folding transition state.

Authors:  M Vendruscolo; E Paci; C M Dobson; M Karplus
Journal:  Nature       Date:  2001-02-01       Impact factor: 49.962

5.  Aromatic clusters: a determinant of thermal stability of thermophilic proteins.

Authors:  N Kannan; S Vishveshwara
Journal:  Protein Eng       Date:  2000-11

6.  Classes of small-world networks.

Authors:  L A Amaral; A Scala; M Barthelemy; H E Stanley
Journal:  Proc Natl Acad Sci U S A       Date:  2000-10-10       Impact factor: 11.205

7.  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

8.  Network analysis of protein structures identifies functional residues.

Authors:  Gil Amitai; Arye Shemesh; Einat Sitbon; Maxim Shklar; Dvir Netanely; Ilya Venger; Shmuel Pietrokovski
Journal:  J Mol Biol       Date:  2004-12-03       Impact factor: 5.469

9.  HOMSTRAD: a database of protein structure alignments for homologous families.

Authors:  K Mizuguchi; C M Deane; T L Blundell; J P Overington
Journal:  Protein Sci       Date:  1998-11       Impact factor: 6.725

10.  Stabilizing interactions in the dimer interface of alpha-subunit in Escherichia coli RNA polymerase: a graph spectral and point mutation study.

Authors:  N Kannan; P Chander; P Ghosh; S Vishveshwara; D Chatterji
Journal:  Protein Sci       Date:  2001-01       Impact factor: 6.725

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  117 in total

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Authors:  M S Vijayabaskar; Saraswathi Vishveshwara
Journal:  Biophys J       Date:  2010-12-01       Impact factor: 4.033

2.  Analysis of core-periphery organization in protein contact networks reveals groups of structurally and functionally critical residues.

Authors:  Arnold Emerson Isaac; Sitabhra Sinha
Journal:  J Biosci       Date:  2015-10       Impact factor: 1.826

Review 3.  Protein Allostery and Conformational Dynamics.

Authors:  Jingjing Guo; Huan-Xiang Zhou
Journal:  Chem Rev       Date:  2016-02-15       Impact factor: 60.622

4.  Hydrophobic, hydrophilic, and charged amino acid networks within protein.

Authors:  Md Aftabuddin; S Kundu
Journal:  Biophys J       Date:  2006-12-15       Impact factor: 4.033

5.  Dynamics of lysozyme structure network: probing the process of unfolding.

Authors:  Amit Ghosh; K V Brinda; Saraswathi Vishveshwara
Journal:  Biophys J       Date:  2007-01-05       Impact factor: 4.033

6.  A study of communication pathways in methionyl- tRNA synthetase by molecular dynamics simulations and structure network analysis.

Authors:  Amit Ghosh; Saraswathi Vishveshwara
Journal:  Proc Natl Acad Sci U S A       Date:  2007-09-26       Impact factor: 11.205

7.  NAPS update: network analysis of molecular dynamics data and protein-nucleic acid complexes.

Authors:  Broto Chakrabarty; Varun Naganathan; Kanak Garg; Yash Agarwal; Nita Parekh
Journal:  Nucleic Acids Res       Date:  2019-07-02       Impact factor: 16.971

8.  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

9.  Molecular dynamics study of HIV-1 RT-DNA-nevirapine complexes explains NNRTI inhibition and resistance by connection mutations.

Authors:  R S K Vijayan; Eddy Arnold; Kalyan Das
Journal:  Proteins       Date:  2013-11-22

10.  Dancing through Life: Molecular Dynamics Simulations and Network-Centric Modeling of Allosteric Mechanisms in Hsp70 and Hsp110 Chaperone Proteins.

Authors:  Gabrielle Stetz; Gennady M Verkhivker
Journal:  PLoS One       Date:  2015-11-30       Impact factor: 3.240

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