Dissecting the Molecular Mechanism of Protein-DNA Interactions

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A critical component on the regulation of gene expression is protein-DNA interactions. The Cys2-His2 zinc finger (ZF) family of transcription factors is the largest family of nucleic acid binding proteins in eukaryotes and a key participant in the regulation of most genes, being activated in response to a wide variety of stimuli. From a structural point of view, this family of transcription factors (TFs) is highly conserved, consisting in two or more ZF modular domains that work together to recognize specific DNA sequences. It is then apparent that ZFs are an ideal model system to study the fundamental principles governing non-specific and specific protein-DNA binding, and shed light into an essential step in the transcription regulation of genes. The goal of this project is to reveal the finely tuned molecular interactions responsible for the thermodynamics and dynamics of protein recognition and binding using structural-based computational approaches in combination with available selection and binding data from biochemical experiments, and high resolution crystal structures deposited in the Protein Data Bank. Specifically, the role of counter ions and side chains in protein-DNA association will be studied using molecular dynamics sampling as a guiding principle to assess and predict changes in binding free energy due to point mutations, allowing us to explore in much greater detail the molecular mechanism of their interaction. Understanding protein-DNA interactions is crucial in order to learn how proteins regulate almost every biological process. So far this problem has been studied by biochemical experiments, challenging and expensive structural determination of the complexes, and computational studies focused mostly in sequence-based motif algorithms. This project will incorporate dynamics and molecular biophysics to uncover sequence/structural relationships that might escape current methods. Any progress in this fundamental problem is bound to bring about a better understanding of how gene regulation works cooperatively in a cell. The project will involve the training of graduate students in computational/structural modeling, and efforts will be made to recruit talented students from underrepresented groups in the project. This project can also make a broad impact in the development of new agents that block or down regulate the expression of specific DNA sequences linked to a pathogenic pathway or protein.