Abstract:
Internal dynamics of proteins can be analyzed by the help of simulation techniques, one of which is molecular dynamics (MD) simulation. Principal component analysis is commonly applied on large-sized MD simulation data to extract the functionally relevant essential modes (principal components). Recently, Alakent et al. analyzed the principal components from MD simulation data by time series models and interpreted the obtained parameters in terms of protein fluctuations. In this thesis, MD trajectories of two enzymes, dihydrofolate reductase (DHFR) and triosephosphate isomerase (TIM), are investigated by performing time series analysis on the principal components. Two independent MD trajectories of 3.2 ns duration are used for the free (apo) and ligand-bound (liganded) states of each enzyme. Model parameters extracted from two independent runs are similar for the same state of each enzyme, which indicates the reliability of the analysis, and shows the extent of the effect of different conformational substates on the protein vibrational frequency density. DHFR has been analyzed with two different ligands which differ from each other by only hydride ion. The contribution of NADPH to the collective motions of DHFR is higher compared to those of NADP+. It is also seen that the collective motions in NADPH bound DHFR are similar to the unliganded form, while the collective character of the motions in the NADP+ bound DHFR is lost. It is found that unliganded forms of both DHFR and TIM are more flexible than liganded form. For both TIM and DHFR, low frequencies shift to higher frequencies after the ligands bind. Vibrational frequencies of NADP+ bound DHFR are lower than those of NADPH bound DHFR. Briefly, it can be concluded that ligand binding affects the collectivity of fluctuations, vibrational low frequency density and anharmonic motions of proteins, and particulary vibrational frequencies of the proteins may have importance on the catalytic cycle. All these effects should be taken into consideration for examing binding affinities of proteins.
