Abstract:Chemokines are small and approximately ~8-12 kDa in weight. They are classified into 4 main types with respect to the spacing of the first two cysteine residues at N-terminal region: a) CXC or alpha, b) CC or β, c) C or gamma, and d) CX3C or delta chemokines. The major function of chemokines is considered to be the ability to mediate the migration of leukocytes. However, it is interesting to note that each chemokine tends to mediate various cell types. A known fact is that similar functional proteins tend to have similar structures and intern similar sequences. Chemokines are varying in their sequence identity between 20 and 99 despite that they have similar structure and function. The variation in sequence identity gives a clue about their sub functional variation under the major function, i.e. chemokines mediate various leukocytes under. However, how chemokines manage to maintain the 2D and 3D structural similarity in proteins. It brings an interest to study the sequence-structure-function relationship in terms of their amino acid preference. Hence, the objective of this study is to anal
yze the structurally similar chemokine proteins to understand the amino acid preference at their secondary structures.
In this study, the chemokines which are having 3D structures are aligned and the structure guided sequence alignment is extracted. Structural properties such as, solvent accessibility, hydrophobicity, retention coefficient, multiple contact index and dihedral angle for each residue in the secondary structures are calculated and their patterns are plotted.
Results of this study reveal that it is possible to explain how different residues tend to form similar secondary structures. The residues that are involved in forming the b-strand at the core region are different from the residues that are forming b-strand at the surface. These results indicate that the preference of amino acid is varying even in the same secondary structural elements depends on the location of the secondary structure present, i.e. whether they present in the core or surface of the protein. This is a novel algorithm, which may be applied to predict the existing or novel protein fold.