bioRxivBiophysics
Network Theory Reveals Principles of Spliceosome Structure and Dynamics
Abstract
Cryo-EM has revolutionized structural biology of the spliceosome and dozens of distinct spliceosome structures representing much of the splicing cycle have now been determined. However, comparison of these structures is challenging due to extreme compositional and conformational dynamics of the splicing machinery and the thousands of intermolecular interactions created or dismantled as splicing progresses. We have used network theory to quantitatively analyze the dynamic interactions of splicing factors throughout the splicing cycle by constructing structure-based networks from every protein-protein, protein-RNA, and RNA-RNA interaction found in eight different spliceosome structures. Our networks reveal that structural modules comprising the spliceosome are highly dynamic with factors oscillating between modules during each stage along with large changes in the algebraic connectivities of the networks. Overall, the spliceosomes connectivity is focused on the active site in part due to contributions from non-globular proteins and components of the NTC. Many key components of the spliceosome including Prp8 and the U2 snRNA exhibit large shifts in both eigenvector and betweenness centralities during splicing. Other factors show transiently high betweenness centralities only at certain stages thereby suggesting mechanisms for regulating splicing by briefly bridging otherwise poorly connected network nodes. These observations provide insights into the organizing principles of spliceosome architecture and provide a framework for comparative network analysis of similarly complex and dynamic macromolecular machines.
- assay: cryo-EM
- research focus: protein folding & dynamics
- approach: deep learning
- approach: statistical model
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