Self Crowding of Globular Proteins Studied by Small-Angle X-Ray Scattering

Abstract

Small-angle x-ray scattering (SAXS) was used to study the behavior of equine metmyoglobin (Mb) and bovine pancreatic trypsin inhibitor (BPTI) at concentrations up to 0.4 and 0.15 g/mL, respectively, in solutions also containing 50% D2O and 1 M urea. For both proteins, significant effects because of interference between x-rays scattered by different molecules (interparticle interference) were observed, indicating nonideal behavior at high concentrations. The experimental data were analyzed by comparison of the observed scattering profiles with those predicted by crystal structures of the proteins and a hard-sphere fluid model used to represent steric exclusion effects. The Mb scattering data were well fit by the hard-sphere model using a sphere radius of 18 Å, only slightly smaller than that estimated from the three-dimensional structure (20 Å). In contrast, the scattering profiles for BPTI in phosphate buffer displayed substantially less pronounced interparticle interference than predicted by the hard-sphere model and the radius estimated from the known structure of the protein (15 Å). Replacing the phosphate buffer with 3-(N-morpolino)propane sulfonic acid (MOPS) led to increased interparticle interference, consistent with a larger effective radius and suggesting that phosphate ions may mediate attractive intermolecular interactions, as observed in some BPTI crystal structures, without the formation of stable oligomers. The scattering data were also used to estimate second virial coefficients for the two proteins: 2.0 ×10(-4) cm(3)mol/g(2) for Mb in phosphate buffer, 1.6 ×10(-4) cm(3)mol/g(2) for BPTI in phosphate buffer and 9.2 ×10(-4) cm(3)mol/g(2) for BPTI in MOPS. The results indicate that the behavior of Mb, which is nearly isoelectric under the conditions used, is well described by the hard-sphere model, but that of BPTI is considerably more complex and is likely influenced by both repulsive and attractive electrostatic interactions. The hard-sphere model may be a generally useful tool for the analysis of small-angle scattering data from concentrated macromolecular solutions.

Aggregation and network formation in self-assembly of protein (H3.1) by a coarse-grained Monte Carlo simulation

“…Interactions among protein chains alter the dynamics of each protein significantly from that of an isolated protein chain as discussed above ( Figure 4) due to aggregation, dispersion, and trapping depending on the temperature and concentration of the underlying protein matrix. 28,29 Apart from the global motion, local mobility of each residue is also modified dramatically (Figures 2 and 3) due to surrounding residues with a relatively moderate to high density network matrix. Thus, the specific characteristic of a protein chain in an interacting network of protein matrix is different from that of an isolated protein chain.…”

“…26 The power and pitfalls of some of the coarse-grained methods (e.g., hierarchical scaling) are relatively well understood and worth implementing in protein modeling. Goldenberg and co-workers [27][28][29] have carried out an extensive investigation of protein structure both experimentally as well as computer simulations; they have analyzed the scattering intensity, structure factor, and fractal dimensionality of the emerging structure, which is not common in many studies on protein folding. Zuckerman 30 has used a united residue model with a structure-based potential, i.e., the Go model 25 with double native structures to probe the conformational phase space of Calmodulin.…”

“…Knott and Best 31 have used a multi-state coarse-grained description, somewhat similar to the double Go model, to analyze the binding mechanism of an intrinsically disordered protein. These studies [27][28][29][30][31] involve protein structures in devising the models and are very useful in examining the structural evolutions spanning over a large time scale. It is not common to see such a detailed analysis of fractality 27 and structure factors 28, 29 that span multiple scales in protein modeling, particularly in crowded systems.…”

“…It is not common to see such a detailed analysis of fractality 27 and structure factors 28, 29 that span multiple scales in protein modeling, particularly in crowded systems. We use knowledge-based interaction potential 2, 6 in a coarsegrained approach 17,18 to investigate the structural evolution in an interacting network of proteins (an isolated chain to a crowded environment 28,29 ).…”

An Introduction and Hierarchical Organization of the Biophysical Tool in Section II

“…These areas include drug candidate and formulation selection [6] as well as in assessing the solution behavior of these drugs at very high protein concentrations in formulation development [7]. However, it may be possible to obtain somewhat similar data on small lab size SAXS units [8,9]. However, it may be possible to obtain somewhat similar data on small lab size SAXS units [8,9].…”