Literature DB >> 16173917

Insights into the quaternary association of proteins through structure graphs: a case study of lectins.

K V Brinda1, Avadhesha Surolia, Sarawathi Vishveshwara.   

Abstract

The unique three-dimensional structure of both monomeric and oligomeric proteins is encoded in their sequence. The biological functions of proteins are dependent on their tertiary and quaternary structures, and hence it is important to understand the determinants of quaternary association in proteins. Although a large number of investigations have been carried out in this direction, the underlying principles of protein oligomerization are yet to be completely understood. Recently, new insights into this problem have been gained from the analysis of structure graphs of proteins belonging to the legume lectin family. The legume lectins are an interesting family of proteins with very similar tertiary structures but varied quaternary structures. Hence they have become a very good model with which to analyse the role of primary structures in determining the modes of quaternary association. The present review summarizes the results of a legume lectin study as well as those obtained from a similar analysis carried out here on the animal lectins, namely galectins, pentraxins, calnexin, calreticulin and rhesus rotavirus Vp4 sialic-acid-binding domain. The lectin structure graphs have been used to obtain clusters of non-covalently interacting amino acid residues at the intersubunit interfaces. The present study, performed along with traditional sequence alignment methods, has provided the signature sequence motifs for different kinds of quaternary association seen in lectins. Furthermore, the network representation of the lectin oligomers has enabled us to detect the residues which make extensive interactions ('hubs') across the oligomeric interfaces that can be targetted for interface-destabilizing mutations. The present review also provides an overview of the methodology involved in representing oligomeric protein structures as connected networks of amino acid residues. Further, it illustrates the potential of such a representation in elucidating the structural determinants of protein-protein association in general and will be of significance to protein chemists and structural biologists.

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Year:  2005        PMID: 16173917      PMCID: PMC1237133          DOI: 10.1042/BJ20050434

Source DB:  PubMed          Journal:  Biochem J        ISSN: 0264-6021            Impact factor:   3.857


  45 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.  A graph-theoretic algorithm for comparative modeling of protein structure.

Authors:  R Samudrala; J Moult
Journal:  J Mol Biol       Date:  1998-05-29       Impact factor: 5.469

Review 3.  Lectins as chaperones in glycoprotein folding.

Authors:  E S Trombetta; A Helenius
Journal:  Curr Opin Struct Biol       Date:  1998-10       Impact factor: 6.809

4.  Handling context-sensitivity in protein structures using graph theory: bona fide prediction.

Authors:  R Samudrala; J Moult
Journal:  Proteins       Date:  1997

5.  Direct evaluation of thermal fluctuations in proteins using a single-parameter harmonic potential.

Authors:  I Bahar; A R Atilgan; B Erman
Journal:  Fold Des       Date:  1997

6.  Analysis of protein-protein interaction sites using surface patches.

Authors:  S Jones; J M Thornton
Journal:  J Mol Biol       Date:  1997-09-12       Impact factor: 5.469

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Authors:  D Xu; C J Tsai; R Nussinov
Journal:  Protein Eng       Date:  1997-09

8.  Identification of tertiary structure resemblance in proteins using a maximal common subgraph isomorphism algorithm.

Authors:  H M Grindley; P J Artymiuk; D W Rice; P Willett
Journal:  J Mol Biol       Date:  1993-02-05       Impact factor: 5.469

9.  CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice.

Authors:  J D Thompson; D G Higgins; T J Gibson
Journal:  Nucleic Acids Res       Date:  1994-11-11       Impact factor: 16.971

Review 10.  Legume lectin structure.

Authors:  R Loris; T Hamelryck; J Bouckaert; L Wyns
Journal:  Biochim Biophys Acta       Date:  1998-03-03
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  12 in total

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Journal:  J Biosci       Date:  2015-10       Impact factor: 1.826

2.  Spectroscopic and differential scanning calorimetric studies on the unfolding of Trichosanthes dioica seed lectin. Similar modes of thermal and chemical denaturation.

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Journal:  Glycoconj J       Date:  2009-11       Impact factor: 2.916

Review 3.  Network Re-Wiring During Allostery and Protein-Protein Interactions: A Graph Spectral Approach.

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Journal:  Methods Mol Biol       Date:  2021

4.  Structural analysis and unique molecular recognition properties of a Bauhinia forficata lectin that inhibits cancer cell growth.

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5.  Effect of Nigella sativa alcoholic extract and oil, as well as Phaseolus vulgaris (kidney bean) lectin on the ultrastructure of Trichomonas vaginalis trophozoites.

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Journal:  J Parasit Dis       Date:  2014-09-11

6.  Extraction and purification of a lectin from red kidney bean and preliminary immune function studies of the lectin and four Chinese herbal polysaccharides.

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7.  Elucidation of the conformational free energy landscape in H.pylori LuxS and its implications to catalysis.

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Journal:  BMC Struct Biol       Date:  2010-08-12

8.  Regulated motion of glycoproteins revealed by direct visualization of a single cargo in the endoplasmic reticulum.

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9.  Functional correlation of bacterial LuxS with their quaternary associations: interface analysis of the structure networks.

Authors:  Moitrayee Bhattacharyya; Saraswathi Vishveshwara
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10.  Structure predictions of two Bauhinia variegata lectins reveal patterns of C-terminal properties in single chain legume lectins.

Authors:  Gustavo M S G Moreira; Fabricio R Conceição; Alan J A McBride; Luciano da S Pinto
Journal:  PLoS One       Date:  2013-11-19       Impact factor: 3.240

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