Protein evolution studies in yeast could help understanding of human disease
Wednesday, April 11, 2012
A central question in molecular evolution is what determines the rate of protein evolution. Extensive genomic studies have shown a strong negative correlation between the expression level of a protein (the concentration of the protein in the cell) and its rate of evolution, known as the E-R anticorrelation. In the April 3, 2012 issue of the Proceedings of the National Academy of Sciences, Professor Jianzhi Zhang and his colleagues propose and demonstrate that this important yet enigmatic phenomenon is at least in part caused by natural selection against protein-protein misinteraction.
Protein misinteractions are nonfunctional and typically nonspecific protein-protein interactions that occur upon random encounters between protein molecules. Protein misinteraction is frequent in cells and can be deleterious to an organism because it (1) potentially leads to a higher demand for protein synthesis that wastes energy, (2) interferes with functional interactions, and (3) initiates abnormal and potentially damaging cellular processes. Specifically, the hypothesis asserts that highly expressed proteins are under stronger selective pressures to avoid misinteraction than are proteins expressed at lower levels. This is because a misinteraction-enhancing mutation is more harmful when it occurs in a highly expressed gene due to the greater number of misinteracting molecules produced. Consequently, highly expressed proteins become less “sticky” on their surfaces and more constrained in surface-sequence evolution than do those expressed at lower levels. Thus, at least in principle, protein misinteraction avoidance can generate an E-R anticorrelation for protein surfaces.
To demonstrate the above verbal model quantitatively, Zhang and colleagues, using yeast, conducted a molecular-level evolutionary simulation using a three-dimensional, protein-lattice model. The simulation yielded multiple expected results, including an E-R anticorrelation. Furthermore, yeast functional genomic data provided unambiguous empirical evidence for their hypothesis. Nevertheless, Zhang and colleagues think that protein misinteraction avoidance is not the only cause of the E-R anticorrelation, and they are exploring other potential mechanisms. One application of the study, Zhang thinks, may be in understanding human disease. Zhang and colleagues are examining whether mutations that increase the probability of protein misinteraction tend to cause disease. Jian-Rong Yang was a visiting student in Zhang's lab at the time of this research, he is now a postdoctoral fellow in the lab. Ben-Yang Liao was an EEB student in Zhang's lab at the time of the research, he is an assistant investigator for Taiwan's National Health Research Institute.
Caption: A schematic diagram explaining the protein misinteraction avoidance hypothesis. Functional interactions between proteins are shown with lock and key matched pairs of jigsaws, whereas misinteractions are shown with unmatched jigsaw pairs that are also boxed. Credit: Jian-Rong Yang, Ben-Yang Liao, Shi-Mei Zhuang and Jianzhi Zhang.
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