CAREER: Structure Prediction of Proteins on Solid Surfaces

Johns Hopkins University, Baltimore MD

Investigators

Abstract

0846324 Gray Intellectual Merit: The long-term goal of this project is to create computational tools which can accurately predict the structure of proteins when they interact with interfaces. The specific goals are (1) to develop and apply techniques for sampling protein conformations in the presence of a solid, (2) to develop and apply techniques for exploring the relevant structural variations in the solid substrate in the presence of protein, and (3) to elucidate the nature of molecular recognition for proteins on solid surfaces relative to other biomolecular interactions. The PI will apply the developed techniques to natural mineralization proteins which have been well studied and offer some structural data for validating the PI?s approaches. Successful creation of predictive tools for determining protein structure on surfaces will be invaluable to the progressive growth and evolution of devices at the interfaces of biology and solid-state (nano)technology. Broader Impact: In addition to the broad impact of these scientific studies on interfacial chemistry, biotechnology, biomaterials, and bionanotechnology, the PI proposes an accompanying educational program which includes new courses, computational modules for broad distribution, and outreach to young scientists within Baltimore. The PI will create a new course on computational design of biomolecules and continue to redesign the undergraduate modeling and control course, contributing to the transformation of the chemical engineering field as it incorporates biology in the curriculum. Computational modules will teach structure prediction tools from basic energetic calculations and structural manipulations to prediction of complex structures and design of custom biomolecules. Software developed from this research will be distributed freely via the Rosetta Commons consortium. Outreach in Baltimore will have a direct impact on minority and low-income populations through the Ingenuity Project which targets exceptional high-school and middle-school students from at-risk populations for advanced curricula and research mentorship.