Dramatic influence of patchy attractions on short-time protein diffusion under crowded conditions

Abstract

We show that weak patchy attractions markedly slow down protein diffusion under conditions prevailing in living cells.

Slow-Down in Diffusion in Crowded Protein Solutions Correlates with Transient Cluster Formation

“…More formally, the limits of short time diffusion are generally considered as τ H ≪ t ≪ τ I , with $${\tau }_H\approx \frac{R^2\rho }{\eta \phi }\text{and}{\tau }_I\approx \frac{R^2}{D_{t,\mathit{dilute}}}$$ where R is the particle radius, ρ is the solvent density, η is the solvent viscosity, and ϕ is the volume fraction. 41 For the 32 mM villin solution, this amounts to a time range of 25 ps ≪ t ≪ 11 ns, which is well below the 2-μs simulation length of the present simulations. Therefore, villins would have enough time to diffuse out of a local cage environment and reach the long-time diffusion limit.…”

“…2.05±0.07, corresponds well to the maximum number of neighbors (2) determined from colloids interacting by the centrosymmetric potential as well as patchy colloids at the volume fraction ϕ = 0.1. 41 …”

Limiting the valence: advancements and new perspectives on patchy colloids, soft functionalized nanoparticles and biomolecules

“…126 Simple patchy models have also been helpful to describe the short-time diffusion of proteins under crowded conditions. 127 More complex situations have been recently considered, such as mixtures of different proteins 128 and non-spherical shapes. [129][130][131] It is interesting to point out that the folded structure of bovine serum albumin in solution was recently shown to change in response to variations of pH and salt concentration; 132 a similar conclusion was previously drawn from simulations on cluster formation in lysozyme solutions.…”

Molecular simulations of cellular processes

“…More complex functional forms, such as isotropic multiwell potentials, have been used to model desolvation between amino acids during protein folding, allosteric transitions, DNA supercoiling, and protein aggregation (Okazaki et al 2006;Chu and Voth 2007;Trovato and Tozzini 2008;Trovato et al 2013;Ruff et al 2014). Nonisotropic potentials have been used to describe the interactions between crystallins mediated by patches of amino acids (Staneva and Frenkel 2015;Bucciarelli et al 2016). We remark that the success of a force field depends on the choice of complex enough functional forms and the method used for its parameterization (Trovato and Tozzini 2008, 2012Trovato et al 2013;Leonarski et al 2013).…”

“…The stabilizing effect arising from the crowder excluded volume has been observed to be counteracted in several cases where weakly interacting biological crowders were employed (Zhou et al 2008;Peixoto et al 2015;Gnutt et al 2015;Smith et al 2016;Rothe et al 2016;Starzyk et al 2016). However, the largest effect of favorable interactions is experienced during diffusion (Saxton 1996;Putzel et al 2014;Peixoto et al 2015;Bucciarelli et al 2016;Smith et al 2016). Indeed, by allowing the macromolecules of a model bacterial cytoplasm to associate transiently, computer simulations have predicted a consistent motion slowdown that inert crowders were unable to explain (Trovato and Tozzini 2014).…”