Effect of single-point sequence alterations on the aggregation propensity of a model protein

Protein Association in Solution: Statistical Mechanical Modeling

Protein molecules associate in solution, often in clusters beyond pairwise, leading to liquid phase separations and high viscosities. It is often impractical to study these multi-protein systems by atomistic computer simulations, particularly in multi-component solvents. Instead, their forces and states can be studied by liquid state statistical mechanics. However, past such approaches, such as the Derjaguin-Landau-Verwey-Overbeek (DLVO) theory, were limited to modeling proteins as spheres, and contained no microscopic structure-property relations. Recently, this limitation has been partly overcome by bringing the powerful Wertheim theory of associating molecules to bear on protein association equilibria. Here, we review these developments.

Immunogenicity of therapeutic proteins: influence of aggregation

The elicitation of anti-drug antibodies (ADA) against biotherapeutics can have detrimental effects on drug safety, efficacy, and pharmacokinetics. The immunogenicity of biotherapeutics is, therefore, an important issue. There is evidence that protein aggregation can result in enhanced immunogenicity; however, the precise immunological and biochemical mechanisms responsible are poorly defined. In the context of biotherapeutic drug development and safety assessment, understanding the mechanisms underlying aggregate immunogenicity is of considerable interest. This review provides an overview of the phenomenon of protein aggregation, the production of unwanted aggregates during bioprocessing, and how the immune response to aggregated protein differs from that provoked by non-aggregated protein. Of particular interest is the nature of the interaction of aggregates with the immune system and how subsequent ADA responses are induced. Pathways considered here include 'classical' activation of the immune system involving antigen presenting cells and, alternatively, the breakdown of B-cell tolerance. Additionally, methods available to screen for aggregation and immunogenicity will be described. With an increased understanding of aggregation-enhanced immune responses, it may be possible to develop improved manufacturing and screening processes to avoid, or at least reduce, the problems associated with ADA.

Coarse-grained simulations of protein aggregation

Protein aggregation is believed to be responsible for a number of human diseases and limits the yields of pharmaceutical proteins during production. Computer simulations can be used to develop novel experimentally testable hypotheses pertaining to aggregation. While all-atom simulations with explicit solvent are too computationally intensive to address the multitude of relevant time scales, coarse-grained models make it possible to observe the transition of monomers to an equilibrium containing aggregates. Here, we provide the reader with background information and a list of steps for setting up, performing, and analyzing computer simulations of aggregating coarse-grained (CG) proteins.

Simulations of nucleation and elongation of amyloid fibrils

We present a coarse-grained model for the growth kinetics of amyloid fibrils from solutions of peptides and address the fundamental mechanism of nucleation and elongation by using a lattice Monte Carlo procedure. We reproduce the three main characteristics of nucleation of amyloid fibrils: (1) existence of lag time, (2) occurrence of a critical concentration, and (3) seeding. We find the nucleation of amyloid fibrils to require a quasi-two-dimensional configuration, where a second layer of beta sheet must be formed adjunct to a first layer, which in turn leads to a highly cooperative nucleation barrier. The elongation stage is found to involve the Ostwald ripening (evaporation-condensation) mechanism, whereby bigger fibrils grow at the expense of smaller ones. This new mechanism reconciles the debate as to whether protofibrils are precursors or monomer reservoirs. We have systematically investigated the roles of time, peptide concentration, temperature, and seed size. In general, we find that there are two kinds of lag time arising from two different mechanisms. For higher temperatures or low enough concentrations close to the disassembly boundary, the fibrillization follows the nucleation mechanism. However, for low temperatures, where the nucleation time is sufficiently short, there still exists an apparent lag time due to slow Ostwald ripening mechanism. Consequently, the lag time is nonmonotonic with temperature, with the shortest lag time occurring at intermediate temperatures, which in turn depend on the peptide concentration. While the nucleation dominated regime can be controlled by seeding, the Ostwald ripening regime is insensitive to seeding. Simulation results from our coarse-grained model on the fibril size, lag time, elongation rate, and solubility are consistent with available experimental observations on many specific amyloid systems.

Oscillatory molecular driving force for protein folding at high concentration: a molecular simulation

This paper presents a Langevin dynamics simulation that suggests a novel way to fold protein at high concentration, a fundamental issue in neurodegenerative diseases in vivo and the production of recombinant proteins in vitro. The simulation indicates that the folding of a coarse-grained beta-barrel protein at high concentration follows the "collapse-rearrangement" mechanism but it yields products of various forms, including single proteins in the native, misfolded, and uncollapsed forms and protein aggregates. Misfolded and uncollapased proteins are the "nucleus" of the aggregates that also encapsulate some correctly folded proteins (native proteins). An optimum hydrophobic interaction strength (epsilon*(p)) between the hydrophobic beads of the model protein, which results from a compromise between the kinetics of collapse and rearrangement, is identified for use in increasing the rate of folding over aggregating. Increased protein concentration hinders the structural transitions in both collapse and rearrangement and thus favors aggregation. A new method for protein folding at high concentration is proposed, which uses an oscillatory molecular driving force (epsilon*(p)) to promote the dissociation of aggregates in the low epsilon*(p) regime while promoting folding at a high epsilon*(p). The advantage of this method in enhancing protein folding while depressing aggregation is illustrated by a comparison with the methods based on direct dilution or applying a denaturant gradient.

Dynamic Control of Protein Folding Pathway with a Polymer of Tunable Hydrophobicity

While the knowledge of protein folding in a dilute solution is now well-advanced, little is known of the influence of surrounding conditions on the folding kinetics, in particular when the protein is in a dynamically responsive environment. Here we report a new procedure to control the pathways of protein folding by using a thermally responsive polymer that varies its hydrophobicity concomitant with the protein structural changes. The advantages of folding in a dynamic environment have been demonstrated first by Langevin dynamics simulations on the basis of coarse-grained models for both the protein and polymer and then by experiments for lysozyme refolding in the presence of poly(N-isopropylacrylamide-co-N-tert-butylacrylamide), a thermal responsive polymer that varies its hydrophobicity in response to temperature. The simulation suggests that decreasing the polymer hydrophobicity during the folding process may result in an optimized free-energy landscape that enhances both the folding yield and kinetics. The experiments affirm that an optimal folding condition can be identified when structural transitions of the protein collaborate with the polymer hydrophobicity tuned by variation of temperature.

Protein aggregation in silico

Protein aggregation is a challenge to the successful manufacture of protein therapeutics; it can impose severe limitations on purification yields and compromise formulation stability. Advances in computer power, and the wealth of computational studies pertaining to protein folding, have facilitated the development of molecular simulation as a tool to investigate protein misfolding and aggregation. Here, we highlight the successes of protein aggregation studies carried out in silico, with a particular emphasis on studies related to biotechnology. To conclude, we discuss future prospects for the field, and identify several biotechnology-related problems that would benefit from molecular simulation.

Molecular simulation of protein aggregation

Computer simulation offers unique possibilities for investigating molecular-level phenomena difficult to probe experimentally. Drawing from a wealth of studies concerning protein folding, computational studies of protein aggregation are emerging. These studies have been successful in capturing aspects of aggregation known from experiment and are being used to refine experimental methods aimed at abating aggregation. Here we review molecular-simulation studies of protein aggregation conducted in our laboratory. Specific attention is devoted to issues with implications for biotechnology.