5 years: $518,182 (with IDC)

This is a CAREER award to support the research of Dr. Rachel Karchin, who holds appointments in the Department of Biomedical Engineering, Institute for Computational Medicine, Department of Computer Science, 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 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 models for missense mutant function prediction that will be used 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 to a mutation’s functional impact. 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. To quote “the game is an agent-based model to evolve a highly fit population of toy proteins in a virtual environment.”