bioRxivBiophysicsPreprint
Protein condensate fusion mapping using Hippopede curve
Abstract
Protein and nucleic acid condensation in cells has been a major focus of biophysical studies in recent years. Such droplets, condensates, or membraneless cellular organelles that form by condensation have been shown to behave like liquid or viscoelastic fluids. In vitro reconstitution of condensates of purified protein and nucleic acid have been used to better understand the phenomena, specifically to quantify the material properties of these condensates. One of the signature properties of a liquid-like condensate is the fusion of two round droplets into a larger droplet. Quantitative imaging and analysis of the fusion process can report the biophysical properties of the condensates, such as surface tension and viscosity in a non-invasive way. Here we take advantage of a model in soft matter physics, hippopede curves, to the condensate fusion problem to estimate these biophysical properties directly and compare the results with existing models in the field. In addition, this method approximates additional parameters such as the surface area and surface curvatures during the fusion process over time.
- assay: proteomics
- research focus: protein folding & dynamics
- approach: deep learning
- approach: statistical model
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