序列(生物学)
残留物(化学)
肽序列
化学物理
化学
相(物质)
生物物理学
生物化学
生物
有机化学
基因
作者
Shiv Rekhi,Cristobal Garcia Garcia,Mayur Barai,Azamat Rizuan,Benjamin S. Schuster,Kristi L. Kiick,Jeetain Mittal
标识
DOI:10.1101/2023.03.02.530853
摘要
Abstract Understanding the relationship between an amino acid sequence and its phase separation has important implications for analyzing cellular function, treating disease, and designing novel biomaterials. Several sequence features have been identified as drivers for protein liquid-liquid phase separation (LLPS), leading to the development of a “molecular grammar” for LLPS. In this work, we further probed how sequence modulates phase separation and the material properties of the resulting condensates. Specifically, we used a model intrinsically disordered polypeptide composed of an 8-residue repeat unit and performed systematic sequence manipulations targeting sequence features previously overlooked in the literature. We generated sequences with no charged residues, high net charge, no glycine residues, or devoid of aromatic or arginine residues. We report that all but one of the twelve variants we designed undergo LLPS, albeit to different extents, despite significant differences in composition. These results support the hypothesis that multiple interactions between diverse residue pairs work in tandem to drive phase separation. Molecular simulations paint a picture of underlying molecular details involving various atomic interactions mediated by not just a handful of residue types, but by most residues. We characterized the changes to inter-residue contacts in all the sequence variants, thereby developing a more complete understanding of the contributions of sequence features such as net charge, hydrophobicity, and aromaticity to phase separation. Further, we find that all condensates formed behave like viscous fluids, despite large differences in their viscosities. The results presented in this study significantly advance the current sequence-phase behavior and sequence-material properties relationships to help interpret, model, and design protein assembly.
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