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Aromatic and arginine content drives multiphasic condensation of protein-RNA mixtures.

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Peer-reviewed

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Article

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Authors

Joseph, Jerelle A 
Collepardo-Guevara, Rosana 
Reinhardt, Aleks 

Abstract

Multiphasic architectures are found ubiquitously in biomolecular condensates and are thought to have important implications for the organization of multiple chemical reactions within the same compartment. Many of these multiphasic condensates contain RNA in addition to proteins. Here, we investigate the importance of different interactions in multiphasic condensates comprising two different proteins and RNA using computer simulations with a residue-resolution coarse-grained model of proteins and RNA. We find that in multilayered condensates containing RNA in both phases, protein-RNA interactions dominate, with aromatic residues and arginine forming the key stabilizing interactions. The total aromatic and arginine content of the two proteins must be appreciably different for distinct phases to form, and we show that this difference increases as the system is driven toward greater multiphasicity. Using the trends observed in the different interaction energies of this system, we demonstrate that we can also construct multilayered condensates with RNA preferentially concentrated in one phase. The "rules" identified can thus enable the design of synthetic multiphasic condensates to facilitate further study of their organization and function.

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Keywords

Arginine, RNA, Proteins, Molecular Dynamics Simulation, Biomolecular Condensates, Models, Molecular

Journal Title

Biophys J

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Journal ISSN

0006-3495
1542-0086

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Publisher

Elsevier BV
Sponsorship
European Research Council (803326)
Engineering and Physical Sciences Research Council (EP/P020259/1)
We acknowledge funding from the University of Cambridge Ernest Oppenheimer Fund [PYC], the Winton Programme for the Physics of Sustainability [PYC, RC-G], the European Research Council under the European Union's Horizon 2020 research and innovation programme [grant 803326; RC-G]. JAJ was a Junior Research Fellow at King's College when this work was undertaken. This work was performed using resources provided by the Cambridge Tier-2 system operated by the University of Cambridge Research Computing Service funded by EPSRC Tier-2 capital grant EP/P020259/1 [RC-G, JAJ, AR], and the ARCHER2 UK National Supercomputing Service via the UK High-End Computing Consortium for Biomolecular Simulation (HEC BioSim) supported by EPSRC grant EP/R029407/1.
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2023-08-31 13:40:27
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2023-07-03 23:31:54
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