(310i) Sequence-Encoded Spatial and Temporal Dependence of Viscoelasticity of Protein Condensates Using Computational Microrheology

Many biomolecular condensates exist as phase-separated viscoelastic protein assemblies within cells. Characterizing the viscoelasticity of condensates is essential for gaining insights into their spatiotemporal organization and physiological functions. Despite the significant interest in the dynamics and rheology of condensates, the quantification of their time-dependent viscoelastic properties is limited and mostly done through experimental rheological methods. Here, we demonstrate that a computational passive probe microrheology technique, coupled with continuum mechanics, can accurately quantify the linear viscoelasticity of condensates formed by intrinsically disordered proteins (IDPs) and is superior to other conventional computational rheology techniques. Using a transferable coarse-grained protein model, we first provide a physical basis for choosing optimal values that define the attributes of the probe particle, namely its size and interaction strength with the model IDPs. We show that the technique reveals the sequence-dependent elastic and viscous modulus, terminal viscosity, and relaxation time of heteropolymeric IDPs that differ either in sequence charge patterning in model IDPs or sequence hydrophobicity in naturally occurring IDPs. Further, we accurately quantify the spatial dependence of viscoelasticity in heterogeneous condensates formed by a pair of IDPs through spatially controlled probe motion in the microrheology technique. The computational passive rheology technique has important implications for investigating the time-dependent rheology of complex biomolecular architectures, resulting in the sequence-rheology-function relationship for condensates.