Peter M. Kasson

Peter M. Kasson

Associate Professor of Molecular Physiology and
Biological Physics and Biomedical Engineering

Ph.D., Biophysics, Stanford University, 2005
M.D., Stanford University, 2007

P.O. Box 800886
Charlottesville, VA 22908-0376
Office: 480 Ray C Hunt Drive

Laboratory website


Research Interests

Mechanisms of influenza virus entry from simulation and experiment Our research centers on the membrane biology of virus-host cell interactions, with a focus on influenza as both a common model system and an important human pathogen. We wish to address three fundamental questions in influenza infection: how does influenza recognize cell-surface glycans on the cells it infects, how do fusion proteins catalyze membrane fusion and bring about viral entry, and how does cellular lipid metabolism permit or inhibit viral replication. We use a combination of novel computational methods and targeted experiments to generate robust quantitative and mechanistic models for these processes. This will yield important insight into the biochemistry of viral infection and should also generalize well to similar problems in vesicle trafficking and cell recognition.

Membrane fusion is a critical step in cell entry and infection by enveloped viruses such as influenza. Influenza hemagglutinin catalyzes fusion by interacting with membrane lipids, but the nature of this interaction is not well understood. Experimental mutagenesis has yielded much data on the functional requirements of the proteins that catalyze fusion, but we have no robust theory that could have predicted these results. The influence of the membrane environment is key: in some viruses, mutations that would normally block fusion can be rescued by adding exogenous lipids. We seek to develop better models of protein-lipid interplay in membrane fusion by influenza.

The development of robust predictive models for the mechanism of lipid membrane fusion will greatly aid in understanding the underlying physical process and how to effectively target it with antiviral agents. We are developing high-performance simulation methods to analyze membrane fusion; we are using these methods to predict the catalytic mechanism of influenza fusion proteins, and understand how fusion is defective in known mutants of influenza, and understand the mechanism of interaction between fusion peptide mutants and membrane perturbations. Computational predictions will be evaluated against experiments performed by collaborators.

This is an exciting time for molecular simulation, because within the past few years we have gained the ability to quantitatively predict experimental observables for small biomolecules. Our interest and expertise lies in achieving the next revolution in computational methods: addressing the more complex cellular environments required to analyze problems in cellular biophysics and infectious disease. Our long-term goal is to leverage synergy between computation and biophysical experimentation for a mechanistic understanding of viral infection and to design therapeutic strategies.

Recent Publications

Peter M. Kasson, Joshua D. Rabinowitz, Lutz Schmitt, Mark M. Davis, and Harden M. McConnell. Kinetics of Peptide Binding to the class II MHC protein I-Ek. Biochemistry, 2000 Feb 8;39(5):1048-58.

Peter M. Kasson and Vijay S. Pande. Molecular dynamics simulation of lipid reorientation at bilayer edges. Biophys J. 2004 Jun;86(6):3744-9.

Peter M. Kasson, Johannes B. Huppa, Michelle Krogsgaard, Mark M. Davis, and Axel T. Brunger. Quantitative imaging of lymphocyte membrane protein reorganization and signaling. Biophys J. 2005 Jan;88(1):579-89.

Peter M. Kasson, Nicholas W. Kelley, Nina Singhal, Marija Vrljic, Axel T. Brunger, and Vijay S. Pande. Ensemble molecular dynamics yields sub-millisecond kinetics and intermediates of membrane fusion. Proceedings of the National Academy of Sciences. 2006 Aug 8;103(32):11916-21.

Peter M. Kasson and Vijay S. Pande. Control of membrane fusion mechanism by lipid omposition: predictions from ensemble molecular dynamics. PLOS Computational Biology, 2007 3(11): e220.

Peter M. Kasson, Daniel L. Ensign, and Vijay S. Pande. Combining molecular dynamics with Bayesian analysis to predict and evaluate ligand-binding mutations in influenza hemagglutinin. J Am Chem Soc, 2009 Aug 19;131(32):11338-40.

Peter M. Kasson, Erik Lindahl, and Vijay S. Pande. Atomic-resolution simulations predict a transition state for vesicle fusion defined by contact of a few lipid tails. PLoS Computational
Biology, 2010 June; 6(6): e1000829.

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