A wide variety of processes in the cell depend on the function of large complexes. Our lab focuses on using computational modeling to understand how macromolecular structures assemble from their component parts. Our work is aimed at providing fundamental insights into assembly mechanisms with the ultimate goal of developing strategies that could disrupt or enhance the assembly of medically relevant complexes. The results of our work also provide general rules that can be applied in the design and construction of synthetic complexes that will self-assembly efficiently.
In one set of projects, we are considering the assembly dynamics of macromolecular structures that contain rings. Many important complexes, such as the proteasome, the chaperone GroEL, and the apoptosome involved in programmed cell death, consist either of single rings or of multiple rings stacked on top of one another. We have characterized some of the challenges that face simple ring-like structures as they assemble, and have discovered mechanisms that complexes could employ to assemble with optimal efficiency. We are currently extending this work to the study of stacked rings, with a particular focus on complexes for which there is experimental evidence of self-assembly. The predictions of our models are tested through detailed analysis of the solved structures of complexes containing rings or stacked rings.
In a second set of projects, we are taking a more systems-wide view and are characterizing assembly challenges that arise in the context of large Protein-Protein Interaction (PPI) networks. Over the past decade, high-throughput techniques such as yeast 2-hybrid screens and affinity purification-mass spec have revealed that the PPI networks inside cells are very large and complex. Assembly processes thus do not occur in isolation, but rather in the context of a large network in which each of the components of a complex may interact with many potential binding partners. By applying rule- and agent-based modeling techniques, we have recently conducted the first dynamical simulations of complex formation in the context of a large PPI network. We have found that large complexes do not reliably assemble in these simulations, indicating that specific mechanisms have evolved to deal with assembly challenges that arise in large PPI networks. We are currently extending this work to understand how cells have evolved to overcome these problems.
- Deeds, E. J.*, Bachman, J.* and Fontana, W. “Optimizing ring assembly: the strength of weak bonds” (manuscript in preparation)
- Deeds, E. J., Krivine, J., Feret, J., Danos, V. and Fontana, W. “Combinatorial complexity and compositional drift in protein-protein interaction networks”. (manuscript in submission)
- Kolokotrones, T., Savage, V., Deeds, E. J. and Fontana, W. “Curvature in metabolic scaling” Nature 464, 753 (2010)
- Savage, V. M.*, Deeds, E. J.* and Fontana, W. “Sizing up allometric scaling theory” PLoS Comput Biol 4, e1000171 (2008)
- Deeds, E. J., Ashenberg, O., Gerardin, J. and Shakhnovich, E. I. “Robust protein-protein interactions in crowded cellular environments” Proc Natl Acad Sci 104, 14952 (2007)
- Deeds, E. J., Ashenberg, O. and Shakhnovich, E. I. “A simple physical model for scaling in protein-protein interaction networks” Proc Natl Acad Sci 103, 311 (2006)
- * Indicates equal contribution of authors