A number of factors have been elucidated as responsible for the thermal stability of thermophilic proteins. However, the contribution of aromatic interactions to thermal stability has not been systematically studied. In the present investigation we used a graph spectral method to identify aromatic clusters in a dataset of 24 protein families for which the crystal structures of both the thermophilic and their mesophilic homologues are known. Our analysis shows a presence of additional aromatic clusters or enlarged aromatic networks in 17 different thermophilic protein families, which are absent in the corresponding mesophilic homologue. The additional aromatic clusters identified in the thermophiles are smaller in size and are largely found on the protein surface. The aromatic clusters are found to be relatively rigid regions of the surface and often the additional aromatic cluster is located close to the active site of the thermophilic enzyme. The residues in the additional aromatic clusters are preferably mutated to Leu, Ser or Ile in the mesophilic homologue. An analysis of the packing geometry of the pairwise aromatic interaction in the additional aromatic clusters shows a preference for a T-shaped orthogonal packing geometry. The present study also provides new insights for protein engineers to design thermostable and thermophilic proteins.
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.
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.
Every two years groups worldwide participate in the Critical Assessment of Protein Structure Prediction (CASP) experiment to blindly test the strengths and weaknesses of their computational methods. CASP has significantly advanced the field but many hurdles still remain, which may require new ideas and collaborations. In 2012 a web-based effort called WeFold, was initiated to promote collaboration within the CASP community and attract researchers from other fields to contribute new ideas to CASP. Members of the WeFold coopetition (cooperation and competition) participated in CASP as individual teams, but also shared components of their methods to create hybrid pipelines and actively contributed to this effort. We assert that the scale and diversity of integrative prediction pipelines could not have been achieved by any individual lab or even by any collaboration among a few partners. The models contributed by the participating groups and generated by the pipelines are publicly available at the WeFold website providing a wealth of data that remains to be tapped. Here, we analyze the results of the 2014 and 2016 pipelines showing improvements according to the CASP assessment as well as areas that require further adjustments and research.
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