Reversible self-association of therapeutic antibodies is a key factor in high protein solution viscosities. In the present work, a coarse-grained computational model accounting for electrostatic, dispersion, and long-ranged hydrodynamic interactions of two model monoclonal antibodies is applied to understand the nature of self-association, predicting the solution microstructure and resulting transport properties of the solution. For the proteins investigated, the structure factor across a range of solution conditions shows quantitative agreement with neutron-scattering experiments. We observe a homogeneous, dynamical association of the antibodies with no evidence of phase separation. Calculations of self-diffusivity and viscosity from coarse-grained dynamic simulations show the appropriate trends with concentration but, respectively, over- and under-predict the experimentally measured values. By adding constraints to the self-associated clusters that rigidify them under flow, prediction of the transport properties is significantly improved with respect to experimental measurements. We hypothesize that these rigidity constraints are associated with missing degrees of freedom in the coarse-grained model resulting from patchy and heterogeneous interactions among coarse-grained domains. These results demonstrate how structural anisotropy and anisotropy of interactions generated by features at the 2-5 nm length scale in antibodies are sufficient to recover the dynamics and rheological properties of these important macromolecular solutions.

Attractive colloidal dispersions, suspensions of fine particles which aggregate and frequently form a space spanning elastic gel are ubiquitous materials in society with a wide range of applications. The colloidal networks in these materials can exist in a mode of free settling when the network weight exceeds its compressive yield stress. An equivalent state occurs when the network is held fixed in place and used as a filter through which the suspending fluid is pumped. In either scenario, hydrodynamic instabilities leading to loss of network integrity occur. Experimental observations have shown that the loss of integrity is associated with the formation of eroded channels, so-called streamers, through which the fluid flows rapidly. However, the dynamics of growth and subsequent mechanism of collapse remain poorly understood. Here, a phenomenological model is presented that describes dynamically the radial growth of a streamer due to erosion of the network by rapid fluid back flow. The model exhibits a finite-time blowup -the onset of catastrophic failure in the gel -due to activated breaking of the inter-colloid bonds. Brownian dynamics simulations of hydrodynamically interacting and settling colloids in dilute gels are employed to examine the initiation and propagation of this instability, which is in good agreement with the theory. The model dynamics are also shown to accurately replicate measurements of streamer growth in two different experimental systems. The predictive capabilities and future improvements of the model are discussed and a stability-state diagram is presented providing insight into engineering strategies for avoiding settling instabilities in networks meant to have long shelf lives.

Research on protein-protein interaction (PPIs) tends to focus on high affinity interactions. Weaker interactions (Kd > 1 µM) recently understood as contributing to intracellular phase separation suggest that even-weaker PPIs might also matter in as-yet unknown ways. However, ultra-weak PPIs (Kd > 1 mM) are not readily accessible by in vivo techniques. Here we use protein electrostatics to estimate PPI strengths and spatially-resolved dynamic simulations to investigate the potential impacts of ultra-weak PPIs within dense protein suspensions. We find that ultra-weak PPIs can drive formation of transient clusters that last long enough to enable enzyme-catalyzed reactions and accelerate the sampling of protein associations. We apply our method to Mycoplasma genitalium , finding that ultra-weak PPIs should be ubiquitous among cytoplasmic proteins. We also predict that the proteome-wide interactome can be shifted to favor 'binding-dominant' ultra-weak PPIs via the introduction of a few charged protein complexes. We speculate that ultra-weak PPIs could contribute to cellular fitness by facilitating sampling and colloidal-scale transport of proteins involved in biological processes, including protein synthesis.

The rate of translation elongation inEscherichia coliis limited by diffusive transport of matching aminoacyl-tRNAs (aa-tRNAs) to ribosomes. Our previous work revealed that, as cell growth quickens, stoichiometric crowding speeds this diffusive search by optimizing encounters between cognate translation molecules, inclusive of chemical kinetics taken fromin vitroexperiments. However, we predicted absolute elongation rates three-fold slower thanin vivomeasurements. We hypothesized that 'pre-loading' of EF-Tu:GTP:aa-tRNA ternary complexes onto ribosomal L7/L12 subunits -- suggested experimentally but not included in our initial model -- might further speed elongation and close this gap. Here, we develop a first-principles physico-chemical model of theE. colicytoplasm including explicit EF-Tu:L7/L12 interactions and elongation reaction kinetics, which quantitatively predictsin vivobinding and rheology. Our model reveals that transient co-localization of the translation machinery by EF-Tu:L7/L12 interactions shortens wait times at the ribosomal A-site, doubling elongation speed and improving prediction of the absolute elongation rate. We posit pre-loading efficiency as a competition between durable binding and frequent sampling of new ternary complexes, and show that the naturally-observedE. colicopy number of four L7/L12 subunits optimizes this tradeoff. Paired with literature data supporting a correlation between lower L7/L12 copy number and faster bacterial growth rate, we suggest a colloidal-scale evolutionary and functional advantage of having fewer L7/L12 per ribosome: frequent ternary complex sampling in dense, fast-growing cytoplasm.

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