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Loretta Au
Loretta Au
William H. Kruskal Instructor

Web: http://www.stat.uchicago.edu/~lorettaau
E-mail: lorettaau@galton.uchicago.edu
Phone: 773.834.1042
Fax: 773.702.9810

University of Chicago
Department of Statistics
5747 S. Ellis Avenue
Jones 316
Chicago, IL 60637 USA

Research Interests

Many biological systems depend upon a balanced relationship between resilience and adaptivity in response to a changing environment, and the primary focus of my research is in understanding how biological systems may continue to remain stable or further evolve by developing quantitative and computational methods to understand the underlying mechanisms that are involved. In particular, I am focused on answering these questions within the context of proteins, and am continuing to address related, relevant problems from molecular and cellular perspectives.

Variation in primary structure is an important aspect of any protein family, enabling proteins from the same family to modulate a broad range of biological responses, despite sharing structural and functional motifs. Methods in comparative sequence analysis are often used to determine the extent that proteins may be related to each other, but further mutagenesis experiments are typically required to fully understand the role of sequence conservation in protein structural stability and other aspects of protein fitness, including binding interactions with ligands or other proteins, allosteric mechanisms involved in conformational changes, and molecular interactions involved in catalysis. However, limitations often exist in the size of protein sequence space that can be explored, due to the financial or temporal costs of experiments.

We have recently devised a computational protocol for performing large-scale mutagenesis that can explore protein sequence and structural spaces simultaneously, allowing us to deconvolve the contributions amino acids may have towards structural stability and binding interactions; this circumvents many obstacles of comparative sequence analysis and complementary techniques, and provides insight on how protein primary structure and 3D conformation are related. A number of statistical and analytical methods are being developed in on-going projects for use in conjunction with computational mutagenesis to understand mutational robustness of protein families, epistatic effects between co-dependent amino acids, structural stability in repeat proteins, and more.

 

 

Last update: 3/29/16