Effective Interactions, Global Dynamics and Cluster Formation in Protein Solutions

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URI: http://hdl.handle.net/10900/88070
http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-880704
http://dx.doi.org/10.15496/publikation-29455
Dokumentart: Dissertation
Date: 2019-04-25
Language: English
Faculty: 7 Mathematisch-Naturwissenschaftliche Fakultät
Department: Physik
Advisor: Schreiber, Frank (Prof. Dr.)
Day of Oral Examination: 2018-07-23
DDC Classifikation: 000 - Computer science, information and general works
500 - Natural sciences and mathematics
530 - Physics
Keywords: Proteine , Interaktion , Wechselwirkung , Isotopieeffekt , Phasendiagramm , Wasser , Deuteriumoxid , Dynamik , Diffusion , Selbstdiffusion , Cluster , Crowding , Röntgenstreuung , Lichtstreuung , Neutronenspektroskopie , Rückstreuung
Other Keywords: mehrwertige Ionen
Yttriumchlorid
Lanthanchlorid
Yttriumnitrat
Lanthannitrat
Proteinwechselwirkungen
effektive Wechselwirkungen
konkurrierende Wechselwirkungen
Phasenverhalten
Proteinphasenverhalten
H2O
D2O
Wasserstoff
Deuterium
Screened-Coulomb-Potenzial
Klebrige-Harte-Kugel-Potenzial
Two-Yukawa-Potenzial
Proteindynamik
Proteindiffusion
Selbstdiffusion
kollektive Diffusion
Clusterbildung
Kleinwinkelröntgenstreuung
Neutronenrückstreuung
Neutronen-Spin-Echo
Rinderserumalbumin
Proteinlösungen
dreiwertiges Salz
Beta-Lactoglobulin
proteins
protein solutions
bovine serum albumin
beta-lactoglobulin
trivalent salt
multivalent ions
yttrium chloride
lanthanum chloride
yttrium nitrate
lanthanum nitrate
protein interactions
effective interactions
competing interactions
phase behavior
protein phase behavior
isotope effects
hydrogen
screened coulomb potential
sticky hard sphere potential
two-yukawa potential
two yukawa potential
protein dynamics
protein diffusion
self-diffusion
collective diffusion
clusters
protein clusters
cluster formation
crowding
small angle x-ray scattering
light scattering
neutron spectroscopy
neutron backscattering
neutron spin-echo
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Abstract:

Proteins are essential for life. Both in vitro and in vivo their behavior is goverend by the interactions which they are subject to. Models from colloid theory quantitatively characterize the effective interaction potential between protein molecules in solution. This allows to better understand the mechanisms behind protein aggregation, cluster formation and crystallization. Protein aggregation is the reason for diseases such as e.g. sickle cell anemia. Protein crystals are grown in order to elucidate the structure and function of proteins. Protein clusters are possible precursors for protein crystals. Moreover, the study of protein clusters is relevant for antibody drug delivery. Clusters tend to form when there is a competition between a short-range attractive and a long-range repulsive potential. At present, cluster formation in systems with competing interactions is an active research field in experiment, simulation and theory. In our group we study cluster formation in a model protein-salt system with a rich phase behavior. The model system of interest is the globular protein bovine serum albumin (BSA) in solution with a trivalent salt (here either LaCl3 , La(NO3 )3 or YCl3 ). When the salt concentration cs in this system is increased at a fixed protein concentration cp, a reentrant condensation (RC) behavior is found which is due to charge inversion on the protein surface. The protein solutions are clear up to the lower salt concentration boundary of the RC (c∗ ) where they become turbid. Above the upper salt concentration boundary of the RC (c∗∗ ) the protein solutions turn clear again. The cs -cp phase diagram is accordingly divided into regimes I, II and III. This system further shows a liquid-liquid phase separation (LLPS) that occurs in the condensed regime when temperature is increased. This phase separation is driven by entropy. The microscopic reason for the attraction between the protein molecules is believed to be the formation of ion bridges. So far, dynamic investigations both by light and neutron scattering were limited to regime I. Part B of this thesis presents a dynamic study on a pure protein system. The method applied there can in the future also be applied to the model system of BSA and trivalent salt. In part C of the thesis the light scattering measurements are extended to regimes II and III. Dynamic methods using neutrons, as in part B of this thesis, require the usage of D2O. Therefore the effect of the solvent isotope on the phase behavior is important. Generally it is assumed in neutron scattering and nuclear magnetic resonance experiments that the solvent isotope does not change the properties of the protein studied. Part A of this thesis investigates the influence of the solvent isotope in the model system of BSA and trivalent salt. Contrary to the general assumption, it is found that the effective attraction is much stronger in D2O compared to H2 O. This is observed consistently by visual inspection of sample solutions as well as by characterizing the interaction using model fits to small-angle X-ray scattering (SAXS) data. As already shortly mentioned, part B of this thesis presents a framework that combines static and dynamic methods to study cluster formation in pure β-lactoglobulin (BLG) solutions. The effect of crowding on protein cluster formation is studied. Crowding plays an important role in the cell where proteins move in an environment with a high concentration of macromolecules. The study in this thesis addresses the question whether under (self-)crowded conditions the proteins still move as monomers or as clusters. By neutron backscattering (NBS) the self-diffusion coefficient is measured. Assuming Brownian diffusion, the hydrodynamic radius of the diffusing entity is obtained. It is found to increase with increasing protein concentration. The analysis of neutron spin-echo (NSE) and SAXS data yields the number of dimers per cluster. The combination of NBS, NSE and SAXS shows that the clusters are compact. At 300 mg/ml 3 to 4 protein dimers move together in one cluster. The NSE data further shows that the lifetime of the clustes is above 50 ns. In terms of a model potential, the Two-Yukawa model proves to be suitable to describe the effective interactions. The unique way to study cluster formation in pure protein solutions by combining statics and dynamic may in the future help to study cluster formation in more complicated systems as, for instance, in the BSA-trivalent salt model system. Part C of the thesis describes cluster formation in the model system of BSA and trivalent salt. An existing study on collective diffusion in BSA with YCl3 in regime I is extended to BSA with LaCl3 and to regime III. Solutions with BSA and LaCl3 are also measured in regime II. Cluster formation is studied by dynamic light scattering (DLS). The concentrations investigated are between 5 and 25 mg/ml. In this concentration range, the intermediate scattering function has two modes which belong to fast and slow diffusion. The fast diffusion mode can tentatively be assigned to monomers and the slow one to clusters. The lifetime of these clusters that are visible in dynamic light scattering is in the range of approximately 1 to 100 ms which is very long compared to the clusters which were observed using NBS. The observation time scale of the NBS instrument is around 4 ns. As outlined above, using NSE, the time scale was extended to ∼50 ns. The DLS results in BSA with LaCl3 show the same trends as in the system with BSA and YCl3. The collective diffusion coefficients and the contribution of clusters to the scattering signal reflect the effective interactions quantified by SAXS measurements as well as the observations made by visual inspection of the protein solutions. To further characterize the BSA-trivalent salt system, the effect of two anions on the phase behavior is investigated in part D of the thesis. The employed anions are chloride ions and nitrate ions. These two anions are very close in the Hofmeister series. Nevertheless it is found that nitrate ions strongly enhance the attraction in comparison to chloride ions. This is found both by visual inspection of the sample solutions and by quantitative analysis of SAXS data.

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