2022
DOI: 10.1101/2022.05.21.492916
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Condensates of disordered proteins have small-world network structures and interfaces defined by expanded conformations

Abstract: The formation of membraneless biomolecular condensates is driven by macromolecules with sticker- and-spacer architectures that undergo phase separation coupled to percolation (PSCP). Driving forces for PSCP are governed by the interplay between reversible inter-sticker crosslinks and solvation preferences of spacers. Here, we introduce molecular and mesoscale descriptions of structures within, outside, and at the interfaces of condensates that are formed by prion-like low complexity domains (PLCDs). These syst… Show more

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Cited by 13 publications
(49 citation statements)
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“…have recently shown that LCD molecules of hnRNPA1 are organized in different topologies inside the condensates 59 . Specifically, proteins are more expanded at the interface compared to both the interior of the condensate and the dilute phase 59 . Moreover, molecules prefer to be oriented perpendicularly to the condensate interface 59 .…”
Section: Discussionmentioning
confidence: 99%
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“…have recently shown that LCD molecules of hnRNPA1 are organized in different topologies inside the condensates 59 . Specifically, proteins are more expanded at the interface compared to both the interior of the condensate and the dilute phase 59 . Moreover, molecules prefer to be oriented perpendicularly to the condensate interface 59 .…”
Section: Discussionmentioning
confidence: 99%
“…In addition to conformational changes inside and outside the condensate, Farag et al have recently shown that LCD molecules of hnRNPA1 are organized in different topologies inside the condensates 59 . Specifically, proteins are more expanded at the interface compared to both the interior of the condensate and the dilute phase 59 . Moreover, molecules prefer to be oriented perpendicularly to the condensate interface 59 .…”
Section: Discussionmentioning
confidence: 99%
See 2 more Smart Citations
“…This has been achieved by leveraging (i) experimental data on single-chain properties, (ii) statistical analyses of protein structures, and (iii) residue-residue free energy profiles calculated from all-atom simulations [26][27][28][29][30][31]. In particular, we and others have proposed an automated procedure to optimize the "stickiness" parameters so as to maximize the agreement with experimental data small-angle X-ray scattering (SAXS) and paramagnetic relaxation enhancement (PRE) NMR data for a large set of IDPs [26,28,29,32]. To ensure the transferability of the model across sequence space, we employed a Bayesian regularization approach [32,33].…”
Section: Introductionmentioning
confidence: 99%