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Statistical mechanics of biomolecular condensates via cavity methods

Physical mechanisms of phase separation in living systems play key physiological roles and have recently been the focus of intensive studies. The strongly heterogeneous nature of such phenomena poses difficult modeling challenges that require going beyond mean-field approaches based on postulating a...

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Detalles Bibliográficos
Autores principales: Lauber, Nino, Tichacek, Ondrej, Bose, Rudrarup, Flamm, Christoph, Leuzzi, Luca, Tang, T-Y Dora, Ruiz-Mirazo, Kepa, De Martino, Daniele
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10040705/
https://www.ncbi.nlm.nih.gov/pubmed/36994084
http://dx.doi.org/10.1016/j.isci.2023.106300
Descripción
Sumario:Physical mechanisms of phase separation in living systems play key physiological roles and have recently been the focus of intensive studies. The strongly heterogeneous nature of such phenomena poses difficult modeling challenges that require going beyond mean-field approaches based on postulating a free energy landscape. The pathway we take here is to calculate the partition function starting from microscopic interactions by means of cavity methods, based on a tree approximation for the interaction graph. We illustrate them on the binary case and then apply them successfully to ternary systems, in which simpler one-factor approximations are proved inadequate. We demonstrate the agreement with lattice simulations and contrast our theory with coacervation experiments of associative de-mixing of nucleotides and poly-lysine. Different types of evidence are provided to support cavity methods as ideal tools for modeling biomolecular condensation, giving an optimal balance between the consideration of spatial aspects and fast computational results.