Coarse-Grained Model for Colloidal Protein Interactions, B₂₂, and Protein Cluster Formation

Abstract

Reversible protein cluster formation is an important initial step in the processes of native and non-native protein aggregation, but involves relatively long time and length scales for detailed atomistic simulations and extensive mapping of free energy landscapes. A coarse-grained (CG) model is presented to semi-quantitatively characterize the thermodynamics and key configurations involved in the landscape for protein oligomerization, as well as experimental measures of interactions such as the osmotic second virial coefficient (B22). Based on earlier work, this CG model treats proteins as rigid bodies composed of one bead per amino acid, with each amino acid having specific parameters for its size, hydrophobicity, and charge. The net interactions are a combination of steric repulsions, short-range attractions, and screened long-range charge-charge interactions. Model parametrization was done by fitting simulation results against experimental values of the B22 as a function of solution ionic strength for α-chymotrypsinogen A and γD-crystallin (gD-Crys). The CG model is applied to characterize the pairwise interactions and dimerization of gD-Crys and the dependance on temperature, protein concentration, and ionic strength. The results illustrate that at experimentally relevant conditions where stable dimers do not form, the entropic contributions are predominant in the free-energy of protein cluster formation and colloidal protein interactions, arguing against interpretations that treat B22 primarily from energetic considerations alone. Additionally, the results suggest that electrostatic interactions help to modulate the population of the different stable configurations for protein nearest-neighbor pairs, while short-range attractions determine the relative orientations of proteins within these configurations. Finally, simulation results are combined with Principal Component Analysis to identify those amino-acids / surface patches that form inter-protein contacts at conditions that favor dimerization of gD-Crys. The resulting regions agree with previously found aggregation-prone sites, as well as suggesting new ones that may be important.

Role of Anisotropic Interactions for Proteins and Patchy Nanoparticles

“…11−15 In some cases, this involves interactions between partially or fully unfolded proteins, and the resulting self-assembled or aggregated states are often effectively irreversible under the solution conditions that they form. 16,17 For interactions between native or folded proteins, assembly processes are more easily reversible, and one of two limiting behaviors is typically observed.…”

Predicting unfolding thermodynamics and stable intermediates for alanine-rich helical peptides with the aid of coarse-grained molecular simulation

“…It was a modified version of the 4bAA force field proposed by Bereau and Deserno [16] that was extended previously to include long-ranged screened electrostatic interactions [7,20]. Each amino acid is represented as the conjunction of four spherical beads as follows: one for the amide group (N), one for the alpha carbon (C α ), one for the carbonyl group (C’) and one for the side chain group (C β ) as shown in Scheme 1.…”

“…Previously, the interaction parameters (other than electrostatics) were parametrized against NMR and crystallographic data in order to capture the secondary and tertiary structures of different polypeptides in their folded state(s) [16]. The electrostatic interactions were parameterized based on experimental light scattering data to give accurate values of osmotic second virial coefficients for globular proteins as a function of ionic strength [20]. This extended Bereau Deserno (EBD) coarse-grained model treats solvent (water + buffer + salts/solutes) implicitly in order to make the computations tractable for the range of different sequences and solution conditions of interest here and for future work.…”

“…Atomistic force fields provide the most accurate method available to identify amino-acid-specific interactions, while coarse-grained (CG) molecular models provide faster computations at the expense of molecular definition [18,19]. Therefore, CG models can potentially be well-suited as a computational framework to speed up experimental searches in order to optimize time and resources, provided the force-field can accurately predict the experimental behavior of interest [18,20,21]. …”

A multiscale view of therapeutic protein aggregation: A colloid science perspective

“…This limitation makes the approach not suitable to describe aggregation kinetics of complex therapeutic proteins on a time scale relevant for accelerated studies and storage conditions. Consequently, coarse-grained models at the amino acid or at the monomer level may offer a compromise between structure resolution and computational time [29][30][31]. For a more comprehensive summary of the computational tools used to study therapeutic protein aggregation, we refer the reader to specific reviews on this topic [23,32].…”