The Facilitation of Protein-DNA Search and Recognition by Multiple Modes of Binding

Abstract

The studies discussed in this thesis unify experimental and theoretical techniques, both established and novel, in investigating the problem of how a protein that binds specific sites on DNA translocates to, recognizes, and stably binds to its target site or sites. The thesis is organized into two parts. Part I outlines the history of the problem and the theory and experiments that have addressed the problem and presents an apparent incompatibility between efficient search and stable, specific binding. To address this problem, we elaborate a model of protein-DNA interaction in which the protein may bind DNA in either a search (S) mode or a recognition (R) mode. The former is characterized by zero or weak sequence-dependence in the binding energy, while the latter is highly sequence-dependent. The protein undergoes a random walk along the DNA in the S mode, and if it encounters its target site, must undergo a conformational transition into the R mode. The model resolves the apparent paradox, and accounts for the observed speed, specificity, and stability in protein-DNA interactions. The model shows internal agreement as regards theoretical and simulated results, as well as external agreement with experimental measurements. Part II reports on research that has tested the applicability of the two-mode model to the tumor suppressor transcription factor p53. It describes in greater depth the experimental techniques and findings up to the present work, and introduces the techniques and biological system used in our research. We employ single-molecule optical microscopy in two projects to study the diffusional kinetics of p53 on DNA. The first project measures the diffusion coefficient of p53 and determines that the protein satisfies a number of requirements for the validity of the two-mode model and for efficient target localization. The second project examines the sequence-dependence in p53's sliding kinetics, and explicitly models the energy landscape it experiences on DNA and relates features of the landscape to observed local variation in diffusion coefficient. The thesis closes with proposed extensions and complements to the projects, and a discussion of the implications of our work and its relation to recent developments in the field.