Combining Scattering Experiments and Colloid Theory to Characterize Charge Effects in Concentrated Antibody Solutions.

Charges and their contribution to protein-protein interactions are essential for the key structural and dynamic properties of monoclonal antibody (mAb) solutions. In fact, they influence the apparent molecular weight, the static structure factor, the collective diffusion coefficient, or the relative viscosity, and their concentration dependence. Further, charges play an important role in the colloidal stability of mAbs.

A multi-scale numerical approach to study monoclonal antibodies in solution.

Developing efficient and robust computational models is essential to improve our understanding of protein solution behavior. This becomes particularly important to tackle the high-concentration regime. In this context, the main challenge is to put forward coarse-grained descriptions able to reduce the level of detail, while retaining key features and relevant information.

Chemometrics in Protein Formulation: Stability Governed by Repulsion and Protein Unfolding.

Therapeutic proteins can be challenging to develop due to their complexity and the requirement of an acceptable formulation to ensure patient safety and efficacy. To date, there is no universal formulation development strategy that can identify optimal formulation conditions for all types of proteins in a fast and reliable manner. In this work, high-throughput characterization, employing a toolbox of five techniques, was performed on 14 structurally different proteins formulated in 6 different buffer conditions and in the presence of 4 different excipients.

Anisotropic protein-protein interactions in dilute and concentrated solutions.

Interactions between biomolecules are ubiquitous in nature and crucial to many applications including vaccine development; environmentally friendly textile detergents; and food formulation. Using small angle X-ray scattering and structure-based molecular simulations, we explore protein-protein interactions in dilute to semi-concentrated protein solutions. We address the pertinent question, whether interaction models developed at infinite dilution can be extrapolated to concentrated regimes? Our analysis is based on measured and simulated osmotic second virial coefficients and solution structure factors at varying protein concentration and for different variants of the protein Thermomyces Lanuginosus Lipase (TLL).

Self-Interactions of Two Monoclonal Antibodies: Small-Angle X-ray Scattering, Light Scattering, and Coarse-Grained Modeling.

Using light scattering (LS), small-angle X-ray scattering (SAXS), and coarse-grained Monte Carlo (MC) simulations, we studied the self-interactions of two monoclonal antibodies (mAbs), PPI03 and PPI13. With LS measurements, we obtained the osmotic second virial coefficient, , and the molecular weight, , of the two mAbs, while with SAXS measurements, we studied the mAbs' self-interaction behavior in the high protein concentration regime up to 125 g/L. Through SAXS-derived coarse-grained representations of the mAbs, we performed MC simulations with either a one-protein or a two-protein model to predict .

Electrostatics Drive Oligomerization and Aggregation of Human Interferon Alpha-2a.

Aggregation is a common phenomenon in the field of protein therapeutics and can lead to function loss or immunogenic patient responses. Two strategies are currently used to reduce aggregation: (1) finding a suitable formulation, which is labor-intensive and requires large protein quantities, or (2) engineering the protein, which requires extensive knowledge about the protein aggregation pathway. We present a biophysical characterization of the oligomerization and aggregation processes by Interferon alpha-2a (IFNα-2a), a protein drug with antiviral and immunomodulatory properties.

Virtual cell model for osmotic pressure calculation of charged biomolecules.

The osmotic pressure of dilute electrolyte solutions containing charged macro-ions as well as counterions can be computed directly from the particle distribution via the well-known cell model. Originally derived within the Poisson-Boltzmann mean-field approximation, the cell model considers a single macro-ion centered into a cell, together with counterions needed to neutralize the total cell charge, while it neglects the phenomena due to macro-ion correlations. While extensively applied in coarse-grained Monte Carlo (MC) simulations of continuum solvent systems, the cell model, in its original formulation, neglects the macro-ion shape anisotropy and details of the surface charge distribution.

Integrating All-Atom and Coarse-Grained Simulations-Toward Understanding of IDPs at Surfaces.

We present a scheme for transferring conformational degrees of freedom from all-atom (AA) simulations of an intrinsically disordered protein (IDP) to coarse-grained (CG) Monte Carlo (MC) simulations using conformational swap moves. AA simulations of a single histatin 5 peptide in water were used to obtain a structural ensemble, which is reweighted in a CGMC simulation in the presence of a negatively charged surface. For efficient sampling, the AA trajectory was condensed using two approaches: RMSD clustering (based on the root-mean-square difference in atom positions) and a "naı̈ve" truncation, where only every 100th frame of the trajectory was included in the library.

Dynamics at a Peptide-TiO Anatase (101) Interface.

The interface between biological matter and inorganic materials is a widely investigated research topic due to possible applications in biomedicine and nanotechnology. In this context, the molecular level adsorption mechanism that drives specific recognition between small peptide sequences and inorganic surfaces represents an important topic likely to provide much information useful for designing bioderived materials. Here, we investigate the dynamics at the interface between a Ti-binding peptide sequence (AMRKLPDAPGMHC) and a TiO anatase surface by using molecular dynamics (MD) simulations.