Study On The Characters Of Different Types Of Amino Acid Networks And Their Relations With Protein Folding

Proteins play an important role in the life system, and perform significant biological functions in all of the life activities, such as multiplication, metabolism, growth and development of life-forms. It is theoretically and practically significant to study the mechanism of protein folding. The theory of free energy surface has provided the theoretical framework to study protein folding mechanism, which has been widely used in the research of thermodynamics and kinetics of protein folding. However, there are still some troubles in constructing of the energy surface. Many experimental and theoretical studies have showed that the folding rate and mechanism of proteins are largely determined by their native structure topology, instead of the detail interactions between atoms. Therefore, it is meaningful to explore the relationship between protein structural topology and its corresponding folding mechanism, and then to obtain the information about folding dynamics through the analysis of protein topological features.In this dissertation, according to the different physicochemical properties of different residues, we have constructed amino-acid network, hydrophobic amino acid network, hydrophilic amino acid network, and hydrophobic-hydrophilic amino acid network. Then, the assortative coefficient and clustering coefficient of these networks were calculated, respectively. It is found that the assortative coefficient of all these types of amino-acid network is positive except hydrophobic-Hydrophilic amino acid network. It is also found that there is clearly a linear positive correlation between the assortative coefficient of the hydrophobic amino acid network and the folding rate of the corresponding protein, which indicates that the cooperative interactions of the hydrophobic residues can promote the process of protein folding. Moreover, the results also show that the clustering coefficient of the hydrophobic network has an obviously linear negative correlation with the folding rate, which implies that the forming of the triangle structure in the protein was unfavorable for protein folding. In addition, we also constructed long-distance-in-sequence networks to study the influence of the interactions between long-distance residues in sequence on protein folding. It is found that the forming of the contacts between distant residues in sequence will delay the process of protein folding.The above results show that the native topologic structure of proteins contains plenty of biological information, and it can be effectively obtained and analyzed by the introduction of complex network. The studies in this dissertation help us to further understand protein folding mechanisms.