Assembly of Model Postsynaptic Densities Involves Interactions Auxiliary to Stoichiometric Binding
Yi-Hsuan Lin, Haowei Wu, Bowen Jia, Mingjie Zhang, Hue Sun Chan

TL;DR
This study develops a mean-field theory to understand protein phase separation in neuronal postsynaptic densities, revealing auxiliary interactions beyond known stoichiometric complexes are crucial for condensate formation.
Contribution
The paper introduces a theoretical framework that incorporates auxiliary interactions to better explain phase separation in neuronal proteins, aligning with experimental observations.
Findings
Auxiliary interactions are essential for accurate phase diagram predictions.
The 3:2 stoichiometry alone cannot explain the observed phase behavior.
Higher-order or weaker interactions likely drive condensate formation.
Abstract
The assembly of functional biomolecular condensates often involves liquid-liquid phase separation (LLPS) of proteins with multiple modular domains, which can be folded or conformationally disordered to various degrees. To understand the LLPS-driving domain-domain interactions, a fundamental question is how readily the interactions in the condensed phase can be inferred from inter-domain interactions in dilute solutions. In particular, are the interactions leading to LLPS exclusively those underlying the formation of discrete inter-domain complexes in homogeneous solutions? We address this question by developing a mean-field LLPS theory of two stoichiometrically constrained solute species. The theory is applied to the neuronal proteins SynGAP and PSD-95, whose complex coacervate serves as a rudimentary model for neuronal postsynaptic densities (PSDs). The predicted phase behaviors are…
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