Analysis of homodimeric protein interfaces by graph-spectral methods

• Published in: Protein engineering 2002-04, Vol.15 (4), p.265-277
• Main Authors: Brinda, K.V., Kannan, N., Vishveshwara, S.
• Format: Article
• Language: English
• Subjects: Algorithms; Amino Acid Sequence; Animals; Binding Sites; Computer Simulation; Dimerization; dimerization sites; eigen vectors; expanded clusters; Humans; interface clusters; interface hot spots; Models, Molecular; Molecular Sequence Data; Protein Binding; Sequence Homology, Amino Acid
• ISSN: 0269-2139; 1741-0126; 1460-213X; 1741-0134
• DOI: 10.1093/protein/15.4.265

The quaternary structures impart structural and functional credibility to proteins. In a multi-subunit protein, it is important to understand the factors that drive the association or dissociation of the subunits. It is a well known fact that both hydrophobic and charged interactions contribute to the stability of the protein interface. The interface residues are also known to be highly conserved. Though they are buried in the oligomer, these residues are either exposed or partially exposed in the monomer. It is felt that a systematic and objective method of identifying interface clusters and their analysis can significantly contribute to the identification of a residue or a collection of residues important for oligomerization. Recently, we have applied the techniques of graph-spectral methods to a variety of problems related to protein structure and folding. A major advantage of this methodology is that the problem is viewed from a global protein topology point of view rather than localized regions of the protein structure. In the present investigation, we have applied the methods of graph-spectral analysis to identify side chain clusters at the interface and the centers of these clusters in a set of homodimeric proteins. These clusters are analyzed in terms of properties such as amino acid composition, accessibility to solvent and conservation of residues. Interesting results such as participation of charged and aromatic residues like arginine, glutamic acid, histidine, phenylalanine and tyrosine, consistent with earlier investigations, have emerged from these analyses. Important additional information is that the residues involved are a part of a cluster(s) and that they are sequentially distant residues which have come closer to each other in the three-dimensional structure of the protein. These residues can easily be detected using our graph-spectral algorithm. This method has also been used to identify important residues (`hot spots') in dimerization and also to detect dimerization sites on the monomer. The residues predicted using the present algorithm have correlated well with the experiments indicating the efficacy of this method in predicting residues involved in dimer stability.