Variability of the cyclin-dependent kinase 2 flexibility without significant change in the initial conformation of the protein or its environment; a computational study

Background: Protein flexibility, which has been referred as a dynamic behavior has various roles in proteins' functions. Furthermore, for some developed tools in bioinformatics, such as protein-protein docking software, considering the protein flexibility, causes a higher degree of accuracy. Through undertaking the present work, we have accomplished the quantification plus analysis of the variations in the human Cyclin Dependent Kinase 2 [hCDK2] protein flexibility without affecting a significant change in its initial environment or the protein per se

Objectives: The main goal of the present research was to calculate variations in the flexibility for each residue of the hCDK2, analysis of their flexibility variations through clustering, and to investigate the functional aspects of the residues with high flexibility variations

Materials and Methods: Using Gromacs package [version 4.5.4], three independent molecular dynamics [MD] simulations of the hCDK2 protein [PDB ID: 1HCL] was accomplished with no significant changes in their initial environments, structures, or conformations, followed by Root Mean Square Fluctuations [RMSF] calculation of these MD trajectories. The amount of variations in these three curves of RMSF was calculated using two formulas

Results: More than 50% of the variation in the flexibility [the distance between the maximum and the minimum amount of the RMSF] was found at the region of Val-154. As well, there are other major flexibility fluctuations in other residues. These residues were mostly positioned in the vicinity of the functional residues. The subsequent works were done, as followed by clustering all hCDK2 residues into four groups considering the amount of their variability with respect to flexibility and their position in the RMSF curves

Conclusions: This work has introduced a new class of flexibility aspect of the proteins' residues. It could also help designing and engineering proteins, with introducing a new dynamic aspect of hCDK2, and accordingly, for the other similar globular proteins. In addition, it could provide a better computational calculation of the protein flexibility, which is, especially important in the comparative studies of the proteins' flexibility

Protein-protein interaction networks [PPI] and complex diseases

The physical interaction of proteins which lead to compiling them into large densely connected networks is a noticeable subject to investigation. Protein interaction networks are useful because of making basic scientific abstraction and improving biological and biomedical applications. Based on principle roles of proteins in biological function, their interactions determine molecular and cellular mechanisms, which control healthy and diseased states in organisms. Therefore, such networks facilitate the understanding of pathogenic [and physiologic] mechanisms that trigger the onset and progression of diseases. Consequently, this knowledge can be translated into effective diagnostic and therapeutic strategies. Furthermore, the results of several studies have proved that the structure and dynamics of protein networks are disturbed in complex diseases such as cancer and autoimmune disorders. Based on such relationship, a novel paradigm is suggested in order to confirm that the protein interaction networks can be the target of therapy for treatment of complex multi-genic diseases rather than individual molecules with disrespect the network