| Literature DB >> 29424691 |
Robert McCoy Vernon1, Paul Andrew Chong1, Brian Tsang1,2, Tae Hun Kim1, Alaji Bah1, Patrick Farber1, Hong Lin1, Julie Deborah Forman-Kay1,2.
Abstract
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.Entities:
Keywords: bioinformatics; computational biology; human; molecular biophysics; pi interactions; prediction; protein interactions; protein phase separation; protein structure; structural biology; systems biology
Mesh:
Substances:
Year: 2018 PMID: 29424691 PMCID: PMC5847340 DOI: 10.7554/eLife.31486
Source DB: PubMed Journal: Elife ISSN: 2050-084X Impact factor: 8.140