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Dynamics of Lysozyme Structure Network: Probing the Process of Unfolding

Molecular Biophysics Unit, Indian Institute of Science, Bangalore, India

Correspondence: Address reprint requests to Saraswathi Vishveshwara, Molecular Biophysics Unit, Indian Institute of Science, Bangalore 560012, India. Tel.: 91-80-22932611; Fax: 91-80-23600535; E-mail: sv{at}mbu.iisc.ernet.in.

Recently we showed that the three-dimensional structure of proteins can be investigated from a network perspective, where the amino acid residues represent the nodes in the network and the noncovalent interactions between them are considered for the edge formation. In this study, the dynamical behavior of such networks is examined by considering the example of T4 lysozyme. The equilibrium dynamics and the process of unfolding are followed by simulating the protein at 300 K and at higher temperatures (400 K and 500 K), respectively. The snapshots of the protein structure from the simulations are represented as protein structure networks in which the strength of the noncovalent interactions is considered an important criterion in the construction of edges. The profiles of the network parameters, such as the degree distribution and the size of the largest cluster (giant component), were examined as a function of interaction strength at different temperatures. Similar profiles are seen at all the temperatures. However, the critical strength of interaction (I_critical) and the size of the largest cluster at all interaction strengths shift to lower values at 500 K. Further, the folding/unfolding transition is correlated with contacts evaluated at I_critical and with the composition of the top large clusters obtained at interaction strengths greater than I_critical. Finally, the results are compared with experiments, and predictions are made about the residues, which are important for stability and folding. To summarize, the network analysis presented in this work provides insights into the details of the changes occurring in the protein tertiary structure at the level of amino acid side-chain interactions, in both the equilibrium and the unfolding simulations. The method can also be employed as a valuable tool in the analysis of molecular dynamics simulation data, since it captures the details at a global level, which may elude conventional pairwise interaction analysis.