Peter M. Kasson
- MD/PhD, Stanford University
Mechanisms of cell entry by influenza; Viral glycan recognition and drug resistance; molecular dynamics simulation; distributed computing.
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. Using a combination of novel computational methods and targeted experiments, we will 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. This proposal seeks 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; in this work, we will use 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. Recent progress in high-resolution imaging and single-molecule spectroscopy have made the interface of large-scale computation and high-resolution imaging particularly exciting, as we start to approach an overlap of time and length scales between the two. Our long-term goal is to leverage this synergy between computation and biophysical experimentation for a mechanistic understanding of viral infection and design of therapeutic strategies.
- Kasson P, Lindahl E, Pande V. Water ordering at membrane interfaces controls fusion dynamics. Journal of the American Chemical Society. 2011;133(11): 3812-5. PMID: 21351772
- Kasson P, Pande V. A bundling of viral fusion mechanisms. Proceedings of the National Academy of Sciences of the United States of America. 2011;108(10): 3827-8. PMID: 21368165 | PMCID: PMC3053970
- Kasson P, Lindahl E, Pande V. Atomic-resolution simulations predict a transition state for vesicle fusion defined by contact of a few lipid tails. PLoS computational biology. 2010;6(6): e1000829. PMID: 20585620 | PMCID: PMC2891707
- Kasson P, Ensign D, Pande V. Combining molecular dynamics with bayesian analysis to predict and evaluate ligand-binding mutations in influenza hemagglutinin. Journal of the American Chemical Society. 2009;131(32): 11338-40. PMID: 19637916 | PMCID: PMC2737089
- Kasson P, Pande V. "Cross-graining": efficient multi-scale simulation via markov state models. Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing. 2009; 260-8. PMID: 19908378
- Kasson P, Pande V. Combining mutual information with structural analysis to screen for functionally important residues in influenza hemagglutinin. Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing. 2009; 492-503. PMID: 19209725 | PMCID: PMC2811693
- Kasson P, Pande V. Structural basis for influence of viral glycans on ligand binding by influenza hemagglutinin. Biophysical journal. 2008;95(7): L48-50. PMID: 18641068 | PMCID: PMC2547437
- Ensign D, Kasson P, Pande V. Heterogeneity even at the speed limit of folding: large-scale molecular dynamics study of a fast-folding variant of the villin headpiece. Journal of molecular biology. 2007;374(3): 806-16. PMID: 17950314 | PMCID: NIHMS34314
- Kasson P, Pande V. Control of membrane fusion mechanism by lipid composition: predictions from ensemble molecular dynamics. PLoS computational biology. 2007;3(11): e220. PMID: 18020701 | PMCID: PMC2077900
- Kasson P, Pande V. Predicting structure and dynamics of loosely-ordered protein complexes: influenza hemagglutinin fusion peptide. Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing. 2007; 40-50. PMID: 17992744