CAREER: Modeling Missense Mutation

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This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5). This is a CAREER award to support the research of Dr. Rachel Karchin, who holds appointments in the Department of Biomedical Engineering, Department of Computer Science, Institute for Computational Medicine, Whiting School of Engineering, Johns Hopkins University and Institute of Genetic Medicine, Johns Hopkins School of Medicine. She is a third-year, tenure-track Assistant Professor. High-throughput genome sequencing has resulted in vast amounts of data on amino acid residue sequence variation (i.e. missense mutations). This has presented the opportunity to increase our understanding of how protein sequence, structure, and function are inter-related. Further in order to understand the role of the interactions between individual mutations, accurate modeling methods are needed. This will bring the field closer towards understanding the genetic basis of natural protein evolution and to improve efforts to evolve proteins in the laboratory. This project is developing computational methods for missense mutant function prediction. These models are resulting in the ability to explore the importance of biological context in protein response to missense mutation (such as loss or gain of activity), the generalizability of such responses among different proteins, and the relative importance of biophysics and phylogeny at these predictions. Further, an experimental verification of these model predictions is being tested in a directed evolution system in Escherichia coli. The work will contribute to computational research in public health (genetic components of disease), agriculture, and ecology (plant and animal susceptibility to pathogens and parasites, resistance to herbicides and insecticides, response to fertilizers). As part of her CAREER plan Dr. Karchin will introduce high school students from groups underrepresented in science, particularly disadvantaged young women, to computational biology. A unique approach to this activity is a molecular evolution computer game designed by the PI for high school students in which an agent-based model is employed to evolve a highly fit population of toy proteins in a virtual environment. Further information on the products of this award and how to access them will be found at the PI's lab web site at http://karchinlab.org/.