Ue kind has the maximum typical perimeter values. Next, we expressed the count of every clique form in terms of relative percentage i.e. in the event the count of BBB cliques having highest typical perimeter value is 153 (out of total 495 proteins), its relative percentage is 30.90 . The relative percentage of each and every clique form is calculated and shown in Figure three. As expected, BBB residues cliques cover maximum Madrasin perimeters in 31 of proteins. Interestingly, the perimeters of all charged residues’ cliques (CCC) are maximum in around 21 of the proteins. In 11 proteins, hydrophilic loops (III) seem to cover maximum perimeter. Rest of the cliques which have non-similar residues vertices (BCC, BCI, BBC etc), do not show substantial preference of any a single more than the others.Sengupta and Kundu BMC Bioinformatics 2012, 13:142 http:www.biomedcentral.com1471-210513Page 10 ofFigure 3 The percentage of proteins for each and every clique variety that covers maximum perimeter at 0 and 2 Imin cutoffs. The average values of your perimeters for every single clique kind ARN-ANs and LRN-ANs are calculated. The amount of times a clique form seems to possess the maximum typical perimeter worth is expressed when it comes to relative percentage of proteins for each and every clique form. The sum of all relative values of various clique sorts at each and every Imin cutoff is 100.The occurrences and perimeters covered by cliques tends to make two clear observations. The initial a single confirms the well known facts concerning the role of hydrophobic residues in tertiary structure formation. However the novel facts which is coming out applying the network evaluation is that charged residue cliques have a larger strength of interaction amongst themselves, and that although fewer in quantity, the charged cliques certainly bring the distantly placed amino acid residues along a polypeptide chain closer within the 3D space; hence helping in protein’s structural organization. Comparing the transition of largest cluster size of real proteins with random model, Vishveshwara et al have concluded that the bond percolation resembles with random model (the probability of connection among two amino acids depends only on a precise Imin); however clique percolation can’t be accomplished by random like behaviour [39,40]. Hence, the presence of cliques and their properties PubMed ID:http://www.ncbi.nlm.nih.gov/pubmed/21331607 are not random; rather they are associated to the protein’s structural want. Nonetheless, they have not addressed no matter whether there is certainly any preference of clique of precise amino acid residues. So far our understanding, no prior study has addressed to evaluate the perimeter of the cliques. The outcomes based around the perimeters of cliques clearly indicate the importance of charged residues (additionally to hydrophobic) in forming triad of distantly placed segments of principal structures in 3D space.ConclusionsThe facts relating to the tertiary structure of a protein is imprinted in the linear arrangement of its constituent amino acids and the said structure has evolved through interactions of amino acids in 3D space. Here, we’ve got analyzed a big variety of protein structures having a simple but strong framework of protein contact network. Our results show that the technique can extractseveral known properties of protein structure too as can unravel several new characteristics. The existence of comparatively larger size of LRN-LCC at higher interaction strength cut-off in thermophiles than mesophiles indicate that the higher interaction strengths among the amino acid nodes of these thermophilic long-r.
