Following Protein Dynamics in Real Time during Crystallization

Abstract

The process of protein crystallization from aqueous protein solutions is still insufficiently understood. During macroscopic crystal formation, occurring often on time scales from a few hours to several days, protein dynamics evolves on the molecular level. Here, we present a proof of concept and a framework to observe this evolving diffusive dynamics on the pico- to nanosecond time scale, associated with cluster or precursor formation that ultimately results in emerging crystals. We investigated the model system of the protein β-lactoglobulin in D2O in the presence of ZnCl2, which induces crystallization by electrostatic bridges. First, the structural changes occurring during crystallization were followed by small-angle neutron scattering. Furthermore, we employed neutron backscattering and spin–echo spectroscopy to measure the ensemble-averaged self- and collective diffusion on nanosecond time scales of protein solutions with a kinetic time resolution on the order of 15 min. The experiments provide information on the increasing number fraction of immobilized proteins as well as on the diffusive motion of unbound proteins in an increasingly depleted phase. Simultaneously, information on the internal dynamics of the proteins is obtained.

Evolution of the structure and dynamics of bovine serum albumin induced by thermal denaturation

“…While this study mixes these approaches by real-time monitoring the dynamical evolution driven by a temperature scan, EFWS and IFWS are particularly promising for future studies focusing, e.g., purely on the evolution of dynamics during assembly and nucleation. 50,51 The conventional analysis of EFWS is based on the Gaussian approximation valid in the limit of low q and yielding an apparent mean squared displacement hu 2 i, 52 which characterizes the dynamical confinement of motions within the resolution time of the instrument (for IN16B: B10 ns). Different extensions have been suggested [53][54][55] to introduce effects of dynamical heterogeneity, and allow data fitting beyond the immediate low q limit, mainly targeted at hydrated protein powders.…”

Notes on Fitting and Analysis Frameworks for QENS Spectra of (Soft) Colloid Suspensions

“…Since the signal is typically dominated by incoherent scattering, the q-dependence mainly influences the different dynamic features. While this approach includes the separation of the (apparent) global diffusion from internal diffusive processes [8], the same procedure can be applied to separate the scattering signal of the crowders from the one of the protein of interest [23], the contributions of monomers and crystals [30], the contributions of two different proteins [31], or to distinguish the scattering signal of proteins from the one coming from the detergent used for purification [32].…”

“…albumin (BSA) at concentrations between c p = 100 − 200 mg/ml are shown which are measured at the temperatures T =280 K and T =295 K. A direct comparison of the spectra is not possible due to the temperature dependence [22,34] and the volume fraction scaling [34]. A model using two Lorentzian functions L to describe the apparent global center-of-mass diffusion coefficient and to summarize the internal diffusive processes of the proteins, which is established for different proteins in the small energy transfer range [8,23,25,30,35], and one Lorentzian function for the solvent contribution is convoluted with the resolution function to obtain the final fit model…”

Reverse-engineering method for XPCS studies of non-equilibrium dynamics

“…For example, understanding the dynamics of proteins in solutions is extremely important for their complex phase transitions including liquid-liquid phase separation (LLPS) (Wang et al, 2013), protein crystallization (Durbin & Feher, 1996), glass transition (Cardinaux et al, 2007), bio-materialization (Gunton et al, 2007), and in the food and pharmaceutical industry. The dynamic behavior of these nonequilibrium process covers length scales ranging from singleprotein size to micrometre phase domains and time scales from microseconds to hundreds of seconds (Da Vela et al, 2016;Beck et al, 2019;Banc et al, 2019). To date, a theory describing these dynamics does not exist.…”