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LASSI: A lattice model for simulating phase transitions of multivalent proteins

Many biomolecular condensates form via spontaneous phase transitions that are driven by multivalent proteins. These molecules are biological instantiations of associative polymers that conform to a so-called stickers-and-spacers architecture. The stickers are protein-protein or protein-RNA interacti...

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Autores principales: Choi, Jeong-Mo, Dar, Furqan, Pappu, Rohit V.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6822780/
https://www.ncbi.nlm.nih.gov/pubmed/31634364
http://dx.doi.org/10.1371/journal.pcbi.1007028
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author Choi, Jeong-Mo
Dar, Furqan
Pappu, Rohit V.
author_facet Choi, Jeong-Mo
Dar, Furqan
Pappu, Rohit V.
author_sort Choi, Jeong-Mo
collection PubMed
description Many biomolecular condensates form via spontaneous phase transitions that are driven by multivalent proteins. These molecules are biological instantiations of associative polymers that conform to a so-called stickers-and-spacers architecture. The stickers are protein-protein or protein-RNA interaction motifs and / or domains that can form reversible, non-covalent crosslinks with one another. Spacers are interspersed between stickers and their preferential interactions with solvent molecules determine the cooperativity of phase transitions. Here, we report the development of an open source computational engine known as LASSI (LAttice simulation engine for Sticker and Spacer Interactions) that enables the calculation of full phase diagrams for multicomponent systems comprising of coarse-grained representations of multivalent proteins. LASSI is designed to enable computationally efficient phenomenological modeling of spontaneous phase transitions of multicomponent mixtures comprising of multivalent proteins and RNA molecules. We demonstrate the application of LASSI using simulations of linear and branched multivalent proteins. We show that dense phases are best described as droplet-spanning networks that are characterized by reversible physical crosslinks among multivalent proteins. We connect recent observations regarding correlations between apparent stoichiometry and dwell times of condensates to being proxies for the internal structural organization, specifically the convolution of internal density and extent of networking, within condensates. Finally, we demonstrate that the concept of saturation concentration thresholds does not apply to multicomponent systems where obligate heterotypic interactions drive phase transitions. This emerges from the ellipsoidal structures of phase diagrams for multicomponent systems and it has direct implications for the regulation of biomolecular condensates in vivo.
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spelling pubmed-68227802019-11-12 LASSI: A lattice model for simulating phase transitions of multivalent proteins Choi, Jeong-Mo Dar, Furqan Pappu, Rohit V. PLoS Comput Biol Research Article Many biomolecular condensates form via spontaneous phase transitions that are driven by multivalent proteins. These molecules are biological instantiations of associative polymers that conform to a so-called stickers-and-spacers architecture. The stickers are protein-protein or protein-RNA interaction motifs and / or domains that can form reversible, non-covalent crosslinks with one another. Spacers are interspersed between stickers and their preferential interactions with solvent molecules determine the cooperativity of phase transitions. Here, we report the development of an open source computational engine known as LASSI (LAttice simulation engine for Sticker and Spacer Interactions) that enables the calculation of full phase diagrams for multicomponent systems comprising of coarse-grained representations of multivalent proteins. LASSI is designed to enable computationally efficient phenomenological modeling of spontaneous phase transitions of multicomponent mixtures comprising of multivalent proteins and RNA molecules. We demonstrate the application of LASSI using simulations of linear and branched multivalent proteins. We show that dense phases are best described as droplet-spanning networks that are characterized by reversible physical crosslinks among multivalent proteins. We connect recent observations regarding correlations between apparent stoichiometry and dwell times of condensates to being proxies for the internal structural organization, specifically the convolution of internal density and extent of networking, within condensates. Finally, we demonstrate that the concept of saturation concentration thresholds does not apply to multicomponent systems where obligate heterotypic interactions drive phase transitions. This emerges from the ellipsoidal structures of phase diagrams for multicomponent systems and it has direct implications for the regulation of biomolecular condensates in vivo. Public Library of Science 2019-10-21 /pmc/articles/PMC6822780/ /pubmed/31634364 http://dx.doi.org/10.1371/journal.pcbi.1007028 Text en © 2019 Choi et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Choi, Jeong-Mo
Dar, Furqan
Pappu, Rohit V.
LASSI: A lattice model for simulating phase transitions of multivalent proteins
title LASSI: A lattice model for simulating phase transitions of multivalent proteins
title_full LASSI: A lattice model for simulating phase transitions of multivalent proteins
title_fullStr LASSI: A lattice model for simulating phase transitions of multivalent proteins
title_full_unstemmed LASSI: A lattice model for simulating phase transitions of multivalent proteins
title_short LASSI: A lattice model for simulating phase transitions of multivalent proteins
title_sort lassi: a lattice model for simulating phase transitions of multivalent proteins
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6822780/
https://www.ncbi.nlm.nih.gov/pubmed/31634364
http://dx.doi.org/10.1371/journal.pcbi.1007028
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