On interaction patterns in proteins

Official URL: http://risc01.sabanciuniv.edu/record=b1615027 (Table of Contents)

Proteins act like molecular machines that perform various functions in cellular activities. The physical laws determine the rules of atomic arrangements, however the organization of amino acids in proteins inherit evolutionary information. Understanding the three-dimensional structures of proteins are crucial for the exploration of the strong relationship between structure and functionality. This provides motivation to inspect how the network structure a ects communication in global scale. In this thesis, we study the interaction patterns in proteins to explore what kind of local mechanisms and global properties they inherit. Using the spatial information of amino acids, simpli ed models of complex molecular systems are built. We generate synthetic structures that resemble proteins in terms of network properties such as degree distribution and clustering characteristics. The di erences between synthetic structures and proteins are traced to distinguish proteins from non-protein structures. Such a di erentiation points out patterns that are peculiar to proteins and reveal the randomness within the proteins. We introduce the Mutation-Minimization (MuMi) method which mimics single point alanine mutation scan to investigate how proteins respond to naturally occurring random perturbations. Our approach enables us to unravel motifs that are common in protein structures and point out amino acids that have signi cant functional roles in biological activities.