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Tanja Kortemme, PhD
What I do
My research seeks to invent approaches to engineer new biological functions at multiple scales, ranging from atomic details to macromolecular machines to cellular processes. By building new functions through a combination of computational design and experimental engineering, I also hope to learn how molecular design principles shape systems-level properties and, ultimately, organismal fitness.
Departmental research area
My research expertise
protein engineering, model predictions and designer proteins to characterize and reengineer protein interactions controlling complex biological processes, atom-level computational methods, protein modeling methods
PhD, Biochemistry, EMBL Heidelberg/University of Hannover, 1997
MSc, Biophysics, Biochemistry, Stanford University/University of Hannover, 1993
BSc, Chemistry, Biochemistry, University of Hannover, Germany, 1989
Engineered biological systems, ranging from molecules with new functions to entire organisms, have tremendous practical importance; they can also fundamentally change how we ask questions about the biological principles of function and fitness. Our research aims to invent approaches to engineer new molecules that operate as predicted in biological contexts, and to utilize prediction and engineering to address fundamental questions on the relationship of molecular characteristics, cellular function and organismal fitness. To address the many current challenges in the field – from developing more predictive computational design methods to determining the requirements for function in cells – we combine concepts from computer science, physics, chemistry, mathematics, engineering and biology.
Our work spans three interrelated themes:
I. Develop computational methods for modeling & design of proteins, in the program Rosetta (www.rosettacommons.org).
Predicting and designing the structures of proteins with biologically useful accuracy has been a key challenge in computational structural biology and molecular engineering. We have made methodological advances that address one of the main bottlenecks: sampling the vast number of conformations accessible to proteins. We have utilized a method for moving through conformational space inspired by principles from robotics – a field with a rich history in efficient calculation of mechanically accessible states subject to constraints. We applied the same mathematics that can be used to direct the motions of a robot arm to compute the degrees of freedom of a polypeptide chain (Mandell et al., Nature Methods 2009). Our predictions generate hypotheses on protein conformations controlling biological processes – such as protein recognition, signal transduction, and enzyme active site gating – and are laying the foundation for our work reengineering and “reshaping” protein interfaces and active sites for new functions.
II. Create new proteins and devices with more advanced functions by experimental engineering.
Designer molecules with new biological functions could have many exciting uses: protein therapeutics with minimal side effects; new enzymes and biological synthesis pathways for fuel molecules or compounds that are otherwise too expensive to produce; sensor/actuator devices that can report on cell biological processes in real time; robust signaling systems that can detect specific inputs and generate a precise response; protein machines that can be controlled by specific external inputs such as light. Over the past several years, we have engineered a range of proteins with new functions, including protein-protein interactions that are specific enough to control complex biological processes in mammalian cells (Kapp et al., PNAS, 2012). We have also engineered proteins whose functions can be switched by phosphorylation or light. A recent highlight is a study describing the control of precise shape transitions of a large protein assembly with optical inputs, where we successfully exchanged the ‘engine’ of a protein-based ATP-driven molecular machine to be powered by light (Hoersch et al., Nature Nanotechnology 2013). A current focus is to apply computational protein design to create new proteins that can sense molecular signals in living cells and orchestrate desired biological responses.
III. Dissect design principles of function in cells by combining prediction and engineering approaches.
Cells must balance the cost and benefit to optimize organismal fitness. In a recent study, we used the lac operon of Escherichia coli – a classic system for regulatory mechanisms that balance cost and benefit of protein expression – to quantify the economics of protein production (Eames & Kortemme, Science 2012). A current experimental effort is directed towards determining the system-level functions of specific interactions in cells and organisms by systematically modulating protein interactions and protein abundance. In a new project, we have begun to characterize large-scale genetic interactions of engineered proteins with altered interaction patterns, using the E-MAP (epistatic mini array profile) technology, in collaboration with Nevan Krogan’s laboratory at UCSF. With Mark von Zastrow's group at UCSF, we have reengineered and characterized PDZ-domain mediated interactions in the recycling of G-protein coupled receptors to quantify the interaction specificities of protein-peptide interactions in the context of cellular processes. These investigations reveal an unexpected functional promiscuity in cellular networks, and suggest that there are biologically important differences between biochemically possible and functionally utilized interactions.
synthetic biology, Computational protein design, Molecular and cellular engineering, Biological interaction networks, systems biology, computational biology, Protein recognition, Molecular Models, Atomistic modeling and simulation, Protein Conformation, Macromolecular structure, Molecular Evolution, protein folding, Protein Interaction Mapping, Azo Compounds, software, Computer-Aided Design, Protein engineering, Protein Sequence Analysis, Protein Conformation, computational biology, Molecular Models, proteins, Polyisoprenyl Phosphates, PDZ Domains, Group II Chaperonins, Secondary Protein Structure