Protein structure and interaction under environmental stress : from quality control recognition to evolution of collective behavior

• Main Author: Brock, Kelly Paige
• Other Authors: Jeremy England.
• Format: Others
• Language: English
• Published: Massachusetts Institute of Technology 2016
• Subjects: Computational and Systems Biology Program.
• Online Access: http://hdl.handle.net/1721.1/104575

Thesis: Ph. D., Massachusetts Institute of Technology, Computational and Systems Biology Program, 2016. === Cataloged from PDF version of thesis. === Includes bibliographical references. === A protein's function in the cell depends on its structure, which in turn depends on the intracellular environment. Stress like heat shock or nutrient starvation can alter intracellular conditions, leading to protein misfolding - i.e. the inability of a protein to reach or maintain its native conformation. Since many proteins interact with each other, protein misfolding and cellular stress response must be examined both on the scale of individual protein conformational changes and on a more global level, where interaction patterns can reveal larger-scale protein responses to cellular stress. On the individual scale, one example of a protein particularly susceptible to misfolding is the human von Hippel-Lindau (VHL) tumor suppressor. When expressed in the absence of its cofactors, VHL cannot fold correctly and is quickly degraded by the cell's quality control machinery. Here, I present a biophysical characterization of a VHL mutation that confers increased resistance to misfolding. Mathematical modeling provides an explanation for this mutant's increased stability in the cell by predicting how its cofactor and chaperone interaction sites are buried or exposed in the protein's predicted conformation. On a more global level, a budding yeast cell undergoing glucose deprivation both acidifies its cytosol and exhibits widespread protein clustering. By employing a proteome-wide computational assay, I examine how this drop in pH could lead to the formation of higher order protein structures. This modeling framework also provides a rationale for why these two related phenotypes might be beneficial, since protein clustering can help regulate relevant metabolic pathways and provide protection from protein misfolding and/or degradation. === by Kelly Paige Brock. === Ph. D.