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A computational model for protein phase separation: hnRNPA1 as a case study

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If you have a question about this talk, please contact Lisa Masters. Meeting ID: 960 8115 6517 Passcode: 135523

First Year PhD Report: Liquid–liquid phase separation (LLPS) is an important mechanism that contributes to intracellular organization via the formation of biomolecular condensates. From a theoretical and computational perspective, the development of accurate and transferable coarse-grained models that allow us to elucidate the molecular mechanisms driving condensate formation in the cytoplasm and nucleoplasm with attainable computational cost is highly desirable. Recently, Bremer and colleagues provided an extensive set of experimental quantitative phase diagrams for the low complexity domain (LCD) of the hnRNPA1 protein (A1LCD), an RNA binding protein that has been found to be involved in neurodegenerative diseases, in particular, ALS . Our group has recently developed a multiscale coarse-grained model, termed ‘Mpipi‘ and based on atomistic potential-of-mean-force calculations, which seeks to provide a balanced parametrization of interaction strengths between different types of amino acids, accounting for the dominant role of pi-based and other select interactions. In this work, we adopt Mpipi, and compute phase diagrams for the full set of A1LCD variants. We find excellent agreement between our simulated phase diagrams and the experimental ones, both qualitatively (i.e., the relative LLPS propensities of the proteins) and quantitatively (i.estimated critical temperatures for LLPS ). During this talk, I aim to give an overview of the theoretical framework of phase separation, its importance in the functionality and pathology of the cellular environment, as well as presenting our new computational model and the insights we can learn from using the hnRNPA1 protein as a model example.

This talk is part of the Theory - Chemistry Research Interest Group series.

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