Pi-Pi contacts are an overlooked protein feature relevant to phase separation

Protein phase separation is implicated in formation of membraneless organelles, signaling puncta and the nuclear pore. Multivalent interactions of modular binding domains and their target motifs can drive phase separation. However, forces promoting the more common phase separation of intrinsically d...

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Bibliographic Details
Published ineLife Vol. 7
Main Authors Vernon, Robert McCoy, Chong, Paul Andrew, Tsang, Brian, Kim, Tae Hun, Bah, Alaji, Farber, Patrick, Lin, Hong, Forman-Kay, Julie Deborah
Format Journal Article
LanguageEnglish
Published England eLife Science Publications, Ltd 09.02.2018
eLife Sciences Publications Ltd
eLife Sciences Publications, Ltd
Subjects
Algorithms
Analysis
bioinformatics
Biological products
Biomaterials
Chemical plants
Computational and Systems Biology
Extinction
Hydrophobicity
Mutation
Organelles
Peptides
Phase transitions
pi interactions
prediction
protein interactions
protein phase separation
Protein structure
Proteins
RNA
RNA processing
Secondary structure
Structural Biology and Molecular Biophysics
Canada
computational biology
protein interactions
protein structure
systems biology
bioinformatics
prediction
protein phase separation
structural biology
molecular biophysics
human
pi interactions
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Summary:Protein phase separation is implicated in formation of membraneless organelles, signaling puncta and the nuclear pore. Multivalent interactions of modular binding domains and their target motifs can drive phase separation. However, forces promoting the more common phase separation of intrinsically disordered regions are less understood, with suggested roles for multivalent cation-pi, pi-pi, and charge interactions and the hydrophobic effect. Known phase-separating proteins are enriched in pi-orbital containing residues and thus we analyzed pi-interactions in folded proteins. We found that pi-pi interactions involving non-aromatic groups are widespread, underestimated by force-fields used in structure calculations and correlated with solvation and lack of regular secondary structure, properties associated with disordered regions. We present a phase separation predictive algorithm based on pi interaction frequency, highlighting proteins involved in biomaterials and RNA processing.
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content type line 23
Zymeworks, Vancouver, Canada.
Department of Biochemistry and Molecular Biology, SUNY Upstate Medical University, New York, United States.
ISSN:2050-084X
2050-084X
DOI:10.7554/elife.31486