Electrostatically Mediated Attractive Self-Interactions and Reversible Self-Association of Fc-Fusion Proteins.

Attractive self-interactions and reversible self-association are implicated in many problematic solution behaviors for therapeutic proteins, such as irreversible aggregation, elevated viscosity, phase separation, and opalescence. Protein self-interactions and reversible oligomerization of two Fc-fusion proteins (monovalent and bivalent) and the corresponding fusion partner protein were characterized experimentally with static and dynamic light scattering as a function of pH (5 and 6.5) and ionic strength (10 mM to at least 300 mM). The fusion partner protein and monovalent Fc-fusion each displayed net attractive electrostatic self-interactions at pH 6.5 and net repulsive electrostatic self-interactions at pH 5. Solutions of the bivalent Fc-fusion contained higher molecular weight species that prevented quantification of typical interaction parameters (B22 and kD). All three of the proteins displayed reversible self-association at pH 6.5, where oligomers dissociated with increased ionic strength. Coarse-grained molecular simulations were used to model the self-interactions measured experimentally, assess net self-interactions for the bivalent Fc-fusion, and probe the specific electrostatic interactions between charged amino acids that were involved in attractive electrostatic self-interactions. Mayer-weighted pairwise electrostatic energies from the simulations suggested that attractive electrostatic self-interactions at pH 6.5 for the two Fc-fusion proteins were due to cross-domain interactions between the fusion partner domain(s) and the Fc domain.

Role of Domain-Domain Interactions on the Self-Association and Physical Stability of Monoclonal Antibodies: Effect of pH and Salt.

Monoclonal antibodies (mAbs) make up a major class of biotherapeutics with a wide range of clinical applications. Their physical stability can be affected by various environmental factors. For instance, an acidic pH can be encountered during different stages of the mAb manufacturing process, including purification and storage. Therefore, understanding the behavior of flexible mAb molecules in acidic solution environments will benefit the development of stable mAb products. This study used small-angle X-ray scattering (SAXS) and complementary biophysical characterization techniques to investigate the conformational flexibility and protein-protein interactions (PPI) of a model mAb molecule under near-neutral and acidic conditions. The study also characterized the interactions between Fab and Fc fragments under the same buffer conditions to identify domain-domain interactions. The results suggest that solution pH significantly influences mAb flexibility and thus could help mAbs remain physically stable by maximizing local electrostatic repulsions when mAbs become crowded in solution. Under acidic buffer conditions, both Fab and Fc contribute to the repulsive PPI observed among the full mAb at a low ionic strength. However, as ionic strength increases, hydrophobic interactions lead to the self-association of Fc fragments and, subsequently, could affect the aggregation state of the mAb.

Characterizing Experimental Monoclonal Antibody Interactions and Clustering Using a Coarse-Grained Simulation Library and a Viscosity Model.

Attractive protein-protein interactions in concentrated monoclonal antibody (mAb) solutions may lead to the formation of clusters that increase viscosity. Here, we propose an analytical model that relates mAb solution viscosity to clustering by accounting for the contributions of suboptimal mAb packing within a cluster and cluster fractal dimension. The influence of short-range, anisotropic attractions and long-range Coulombic repulsion on cluster properties is investigated by analyzing the cluster-size distributions, cluster fractal dimensions, radial distribution functions, and static structure factors from a library of coarse-grained molecular dynamics simulations. The library spans a vast range of mAb charges and attractive interactions in solutions of varying ionic strength. We present a framework for combining the viscosity model and simulation library to successfully characterize the attraction, repulsion, and clustering of an experimental mAb in three different pH and cosolute conditions by fitting the measured viscosity or structure factor from small-angle X-ray scattering. At low ionic strength, the cluster-size distribution is impacted by strong charges, and both the viscosity and net charge or structure factor and net charge must be considered to deconvolute the effects of short-range attraction and long-range repulsion.

Computational models for studying physical instabilities in high concentration biotherapeutic formulations.

Computational prediction of the behavior of concentrated protein solutions is particularly advantageous in early development stages of biotherapeutics when material availability is limited and a large set of formulation conditions needs to be explored. This review provides an overview of the different computational paradigms that have been successfully used in modeling undesirable physical behaviors of protein solutions with a particular emphasis on high-concentration drug formulations. This includes models ranging from all-atom simulations, coarse-grained representations to macro-scale mathematical descriptions used to study physical instability phenomena of protein solutions such as aggregation, elevated viscosity, and phase separation. These models are compared and summarized in the context of the physical processes and their underlying assumptions and limitations. A detailed analysis is also given for identifying protein interaction processes that are explicitly or implicitly considered in the different modeling approaches and particularly their relations to various formulation parameters. Lastly, many of the shortcomings of existing computational models are discussed, providing perspectives and possible directions toward an efficient computational framework for designing effective protein formulations.

Highland games: A benchmarking exercise in predicting biophysical and drug properties of monoclonal antibodies from amino acid sequences.

Biopharmaceutical product and process development do not yet take advantage of predictive computational modeling to nearly the degree seen in industries based on smaller molecules. To assess and advance progress in this area, spirited coopetition (mutually beneficial collaboration between competitors) was successfully used to motivate industrial scientists to develop, share, and compare data and methods which would normally have remained confidential. The first "Highland Games" competition was held in conjunction with the October 2018 Recovery of Biological Products Conference in Ashville, NC, with the goal of benchmarking and assessment of the ability to predict development-related properties of six antibodies from their amino acid sequences alone. Predictions included purification-influencing properties such as isoelectric point and protein A elution pH, and biophysical properties such as stability and viscosity at very high concentrations. Essential contributions were made by a large variety of individuals, including companies which consented to provide antibody amino acid sequences and test materials, volunteers who undertook the preparation and experimental characterization of these materials, and prediction teams who attempted to predict antibody properties from sequence alone. Best practices were identified and shared, and areas in which the community excels at making predictions were identified, as well as areas presenting opportunities for considerable improvement. Predictions of isoelectric point and protein A elution pH were especially good with all-prediction average errors of 0.2 and 1.6 pH unit, respectively, while predictions of some other properties were notably less good. This manuscript presents the events, methods, and results of the competition, and can serve as a tutorial and as a reference for in-house benchmarking by others. Organizations vary in their policies concerning disclosure of methods, but most managements were very cooperative with the Highland Games exercise, and considerable insight into common and best practices is available from the contributed methods. The accumulated data set will serve as a benchmarking tool for further development of in silico prediction tools.

Protein-Protein Interactions, Clustering, and Rheology for Bovine IgG up to High Concentrations Characterized by Small Angle X-Ray Scattering and Molecular Dynamics Simulations.

A systematic understanding of intermolecular interactions is necessary for designing concentrated monoclonal and polyclonal antibody solutions with reduced viscosity and enhanced stability. Here, we determine the effects of pH and cosolute on the strength and geometry of short-range anisotropic protein-protein attractions for a polyclonal bovine IgG by comparing intensities [I(q)] obtained from small-angle X-ray scattering to those computed in molecular dynamics simulations with 12-bead models. As our model embodies key features of the protein shape, it can describe the experimental I(q) for solutions of 10-200 mg/mL protein with only a small (<1 kBT) variation in the model's well depth. At high concentration, small changes in the interaction potential produce large increases in clustering given the close interprotein spacing. Reducing the pH below the pI or adding NaCl weakens short-range anisotropic attractions but not enough to remove large reversible oligomers that raise viscosity. In contrast, for arginine added at pH 5.5, a uniform attraction model is sufficient to describe the I(q) that plateaus at low q. With primarily monomers and dimers, the viscosity is reduced relative to the other systems that have larger clusters as described with a model that includes the cluster size distribution.

Alteración del metabolismo de glucosa y lípidos en los pacientes con virus de inmunodeficiencia humana

Introducción: El virus de inmunodeficiencia humana (VIH) es un retrovirus, de la subfamilia Lentiviridae, asociada con la dislipidemia y la resistencia a la insulina. Asimismo con el tratamiento antirretroviral de gran actividad (TARGA) se ha logrado una reducción de la morbimortalidad y como efecto secundario se ha presentado desbalance metabólico en cuanto a la glicemia y perfil lipídico. Objetivo: Relacionar los niveles de glucosa y lípidos en los pacientes con VIH con TARGA en la consulta de infectología del Servicio Autónomo del Hospital Central de Maracay (SAHCM) período mayo ­ julio 2016. Materiales y Métodos: Estudio clínico, diagnóstico, analítico, transversal, correlacional, no experimental. Se incluyeron pacientes con VIH mayores de 18 años que acudieron a la consulta de infectología en el SAHCM mayo ­ julio de 2016. Resultados: Se analizaron 30 pacientes con predominio de sexo masculino (66,7 %) y edad promedio de 41,13 años. El índice de masa corporal <25 Kg/m2 prevaleció (66,67 %), la circunferencia abdominal tuvo una media de 80,53 cm. Las personas con inhibidores de la transcriptasa reversa análogo de nucleósido más inhibidores de la transcriptasa reversa no análogo de nucleósido (ITRN/ITRNN) demostraron mayor proporción de sobrepeso (13 %). El 10 % presentaron hipercolesterolemia, la mayoría con ITRNN/ITRN; el 10 % tuvo hipertrigliceridemia y VLDL >100 mg/dL en tratamiento con ITRN/IP (Inhibidores de proteasa). El 63,3 % presentó LDL elevado asociado a ITRNN/ITRN; solo el 3,3 % presentó el HDL <50 mg/ dL y glicemias >100 mg/dL en 13,3 % de los pacientes. Conclusión: El VIH y los TARGA producen alteración metabólica.

Introduction: Human Immunodeficiency Virus (HIV) is a retrovirus, Lentiviridae subfamily, associated with dyslipidemia and insulin resistance. Antiretroviral therapy (HAART) has achieved a reduction in morbidity and mortality as a result, it has been presented metabolic imbalance related to glycemia and lipid profile. Objetive: Relate glucose and lipid levels in HIV patients on HAART in infectology's consultation the Autonomous Service of the Central Hospital of Maracay (SAHCM) period from May to July 2016. Materials and Methods: Clinical, diagnostic, analytical, transversal, co-relational, not experimental study. HIV patients over 18 years old, attended in the Infectology's consultation in May SAHCM, were included Results: 30 patients predominantly male (66.7 %) and average age of 41.13 years were analyzed. The body mass index <25 kg / m2 prevailed (66.67 %), abdominal circumference had an average of 80,53 cm. People treated with nucleotide reverse transcriptase inhibitor plus non nucleotide reverse transcriptase inhibitor (NRTIS/ ITRNA) showed higher proportion of overweight (13 %). Hypercholesterolemia was founded in 10 %, almost patients with ITRNN / ITRN; 10 % had hypertriglyceridemia and VLDL> 100 mg/dL treated with NRTIS /ITRNN / PI (protease inhibitors) with P = 0.00. The 63.3 % had elevated LDL associated with ITRNN / ITRN; only 3.3 % had HDL <50 mg/dL; the blood glucose> 100 mg/dL (13.3 %) was evident in most of HAART. Conclusion: HIV and HAART produce metabolic disorder.

Evaluating the Effects of Hinge Flexibility on the Solution Structure of Antibodies at Concentrated Conditions.

Employing 2 different coarse-grained models, we evaluated the effect of intramolecular domain-domain distances and hinge flexibility on the general solution structure of monoclonal antibodies (mAbs), within the context of protein-protein steric repulsion. These models explicitly account for the hinge region, and represent antibodies at either domain or subdomain levels (i.e., 4-bead and 7-bead representations, respectively). Additionally, different levels of mAb flexibility are also considered. When evaluating mAbs as rigid structures, analysis of small-angle scattering profiles showed that changes in the relative internal distances between Fc and Fab domains significantly alter the local arrangement of neighboring molecules, as well as the molecular packing of the concentrated mAb solutions. Likewise, enabling hinge flexibility in either of the mAb models led to qualitatively similar results, where flexibility increases the spatial molecular arrangement at elevated concentrations. This occurs because fluctuations in mAb quaternary structure are modulated by the close proximity between molecules at elevated concentrations (>50 mg mL-1), yielding an increased molecular packing and osmotic compressibility. However, our results also showed that the mechanism behind this synergy between flexibility and packing strongly depends on both the level of structural detail and the number of degrees-of-freedom considered in the coarse-grained model.

Predicting structural properties of fluids by thermodynamic extrapolation.

We describe a methodology for extrapolating the structural properties of multicomponent fluids from one thermodynamic state to another. These properties generally include features of a system that may be computed from an individual configuration such as radial distribution functions, cluster size distributions, or a polymer's radius of gyration. This approach is based on the principle of using fluctuations in a system's extensive thermodynamic variables, such as energy, to construct an appropriate Taylor series expansion for these structural properties in terms of intensive conjugate variables, such as temperature. Thus, one may extrapolate these properties from one state to another when the series is truncated to some finite order. We demonstrate this extrapolation for simple and coarse-grained fluids in both the canonical and grand canonical ensembles, in terms of both temperatures and the chemical potentials of different components. The results show that this method is able to reasonably approximate structural properties of such fluids over a broad range of conditions. Consequently, this methodology may be employed to increase the computational efficiency of molecular simulations used to measure the structural properties of certain fluid systems, especially those used in high-throughput or data-driven investigations.

A methodology to calculate small-angle scattering profiles of macromolecular solutions from molecular simulations in the grand-canonical ensemble.

The theoretical framework to evaluate small-angle scattering (SAS) profiles for multi-component macromolecular solutions is re-examined from the standpoint of molecular simulations in the grand-canonical ensemble, where the chemical potentials of all species in solution are fixed. This statistical mechanical ensemble resembles more closely scattering experiments, capturing concentration fluctuations that arise from the exchange of molecules between the scattering volume and the bulk solution. The resulting grand-canonical expression relates scattering intensities to the different intra- and intermolecular pair distribution functions, as well as to the distribution of molecular concentrations on the scattering volume. This formulation represents a generalized expression that encompasses most of the existing methods to evaluate SAS profiles from molecular simulations. The grand-canonical SAS methodology is probed for a series of different implicit-solvent, homogeneous systems at conditions ranging from dilute to concentrated. These systems consist of spherical colloids, dumbbell particles, and highly flexible polymer chains. Comparison of the resulting SAS curves against classical methodologies based on either theoretical approaches or canonical simulations (i.e., at a fixed number of molecules) shows equivalence between the different scattering intensities so long as interactions between molecules are net repulsive or weakly attractive. On the other hand, for strongly attractive interactions, grand-canonical SAS profiles deviate in the low- and intermediate-q range from those calculated in a canonical ensemble. Such differences are due to the distribution of molecules becoming asymmetric, which yields a higher contribution from configurations with molecular concentrations larger than the nominal value. Additionally, for flexible systems, explicit discrimination between intra- and inter-molecular SAS contributions permits the implementation of model-free, structural analysis such as Guinier's plots at high molecular concentrations, beyond what the traditional limits are for such analysis.

Monte Carlo simulation of cylinders with short-range attractions.

Cylindrical or rod-like particles are promising materials for the applications of fillers in nanocomposite materials and additives to control rheological properties of colloidal suspensions. Recent advances in particle synthesis allows for cylinders to be manufactured with short-ranged attractions to study the gelation as a function of packing fraction, aspect ratio and attraction strength. In order to aid in the analysis of small-angle scattering experiments of rod-like particles, computer simulation methods were used to model these particles with specialized Monte Carlo algorithms and tabular superquadric potentials. The attractive interaction between neighboring rods increases with the amount of locally-accessible surface area, thus leading to patchy-like interactions. We characterize the clustering and percolation of cylinders as the attractive interaction increases from the homogenous fluid at relatively low attraction strength, for a variety of aspect ratios and packing fractions. Comparisons with the experimental scattering results are also presented, which are in agreement.

Communication: Predicting virial coefficients and alchemical transformations by extrapolating Mayer-sampling Monte Carlo simulations.

Virial coefficients are predicted over a large range of both temperatures and model parameter values (i.e., alchemical transformation) from an individual Mayer-sampling Monte Carlo simulation by statistical mechanical extrapolation with minimal increase in computational cost. With this extrapolation method, a Mayer-sampling Monte Carlo simulation of the SPC/E (extended simple point charge) water model quantitatively predicted the second virial coefficient as a continuous function spanning over four orders of magnitude in value and over three orders of magnitude in temperature with less than a 2% deviation. In addition, the same simulation predicted the second virial coefficient if the site charges were scaled by a constant factor, from an increase of 40% down to zero charge. This method is also shown to perform well for the third virial coefficient and the exponential parameter for a Lennard-Jones fluid.

Predicting low-temperature free energy landscapes with flat-histogram Monte Carlo methods.

We present a method for predicting the free energy landscape of fluids at low temperatures from flat-histogram grand canonical Monte Carlo simulations performed at higher ones. We illustrate our approach for both pure and multicomponent systems using two different sampling methods as a demonstration. This allows us to predict the thermodynamic behavior of systems which undergo both first order and continuous phase transitions upon cooling using simulations performed only at higher temperatures. After surveying a variety of different systems, we identify a range of temperature differences over which the extrapolation of high temperature simulations tends to quantitatively predict the thermodynamic properties of fluids at lower ones. Beyond this range, extrapolation still provides a reasonably well-informed estimate of the free energy landscape; this prediction then requires less computational effort to refine with an additional simulation at the desired temperature than reconstruction of the surface without any initial estimate. In either case, this method significantly increases the computational efficiency of these flat-histogram methods when investigating thermodynamic properties of fluids over a wide range of temperatures. For example, we demonstrate how a binary fluid phase diagram may be quantitatively predicted for many temperatures using only information obtained from a single supercritical state.

Effect of the surface charge distribution on the fluid phase behavior of charged colloids and proteins.

A generic but simple model is presented to evaluate the effect of the heterogeneous surface charge distribution of proteins and zwitterionic nanoparticles on their thermodynamic phase behavior. By considering surface charges as continuous "patches," the rich set of surface patterns that is embedded in proteins and charged patchy particles can readily be described. This model is used to study the fluid phase separation of charged particles where the screening length is of the same order of magnitude as the particle size. In particular, two types of charged particles are studied: dipolar fluids and protein-like fluids. The former represents the simplest case of zwitterionic particles, whose charge distribution can be described by their dipole moment. The latter system corresponds to molecules/particles with complex surface charge arrangements such as those found in biomolecules. The results for both systems suggest a relation between the critical region, the strength of the interparticle interactions, and the arrangement of charged patches, where the critical temperature is strongly correlated to the magnitude of the dipole moment. Additionally, competition between attractive and repulsive charge-charge interactions seems to be related to the formation of fluctuating clusters in the dilute phase of dipolar fluids, as well as to the broadening of the binodal curve in protein-like fluids. Finally, a variety of self-assembled architectures are detected for dipolar fluids upon small changes to the charge distribution, providing the groundwork for studying the self-assembly of charged patchy particles.

Aggregation of poly(acrylic acid)-containing elastin-mimetic copolymers.

Polymer-peptide conjugates were produced via the copper-catalyzed azide-alkyne cycloaddition of poly(tert-butyl acrylate) (PtBA) and elastin-like peptides. An azide-functionalized polymer was produced via atom transfer radical polymerization (ATRP) followed by conversion of bromine end groups to azide groups. Subsequent reaction of the polymer with a bis-alkyne-functionalized, elastin-like peptide proceeded with high efficiency, yielding di- and tri-block conjugates, which after deprotection, yielded poly(acrylic acid) (PAA)-based diblock and triblock copolymers. These conjugates were solubilized in dimethyl formamide, and addition of phosphate buffered saline (PBS) induced aggregation. The presence of polydisperse spherical aggregates was confirmed by dynamic light scattering and transmission electron microscopy. Additionally, a coarse-grained molecular model was designed to reasonably capture inter- and intramolecular interactions for the conjugates and its precursors. This model was used to assess the effect of the different interacting molecular forces on the conformational thermodynamic stability of the copolymers. Our results indicated that the PAA's ability to hydrogen-bond with both itself and the peptide is the main interaction for stabilizing the diblocks and triblocks and driving their self-assembly, while interactions between peptides are suggested to play only a minor role on the conformational and thermodynamic stability of the conjugates.

Role of anisotropic interactions for proteins and patchy nanoparticles.

Protein-protein interactions are inherently anisotropic to some degree, with orientation-dependent interactions between repulsive and attractive or complementary regions or "patches" on adjacent proteins. In some cases it has been suggested that such patch-patch interactions dominate the thermodynamics of dilute protein solutions, as captured by the osmotic second virial coefficient (B22), but delineating when this will or will not be the case remains an open question. A series of simplified but exactly solvable models are first used to illustrate that a delicate balance exists between the strength of attractive patch-patch interactions and the patch size, and that repulsive patch-patch interactions contribute significantly to B22 for only those conditions where the repulsions are long-ranged. Finally, B22 is reformulated, without approximations, in terms of the density of states for a given interaction energy and particle-particle distance. Doing so illustrates the inherent balance of entropic and energetic contributions to B22. It highlights that simply having strong patch-patch interactions will only cause anisotropic interactions to dominate B22 solution properties if the unavoidable entropic penalties are overcome, which cannot occur if patches are too small. The results also indicate that the temperature dependence of B22 may be a simple experimental means to assess whether a small number of strongly attractive configurations dominate the dilute solution behavior.

Protein-protein interactions in dilute to concentrated solutions: α-chymotrypsinogen in acidic conditions.

Protein-protein interactions were investigated for α-chymotrypsinogen by static and dynamic light scattering (SLS and DLS, respectively), as well as small-angle neutron scattering (SANS), as a function of protein and salt concentration at acidic conditions. Net protein-protein interactions were probed via the Kirkwood-Buff integral G22 and the static structure factor S(q) from SLS and SANS data. G22 was obtained by regressing the Rayleigh ratio versus protein concentration with a local Taylor series approach, which does not require one to assume the underlying form or nature of intermolecular interactions. In addition, G22 and S(q) were further analyzed by traditional methods involving fits to effective interaction potentials. Although the fitted model parameters were not always physically realistic, the numerical values for G22 and S(q → 0) were in good agreement from SLS and SANS as a function of protein concentration. In the dilute regime, fitted G22 values agreed with those obtained via the osmotic second virial coefficient B22 and showed that electrostatic interactions are the dominant contribution for colloidal interactions in α-chymotrypsinogen solutions. However, as protein concentration increases, the strength of protein-protein interactions decreases, with a more pronounced decrease at low salt concentrations. The results are consistent with an effective "crowding" or excluded volume contribution to G22 due to the long-ranged electrostatic repulsions that are prominent even at the moderate range of protein concentrations used here (<40 g/L). These apparent crowding effects were confirmed and quantified by assessing the hydrodynamic factor H(q → 0), which is obtained by combining measurements of the collective diffusion coefficient from DLS data with measurements of S(q → 0). H(q → 0) was significantly less than that for a corresponding hard-sphere system and showed that hydrodynamic nonidealities can lead to qualitatively incorrect conclusions regarding B22, G22, and static protein-protein interactions if one uses only DLS to assess protein interactions.

Coarse-grained model for colloidal protein interactions, B(22), and protein cluster formation.

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 semiquantitatively 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 (Grüenberger et al., J. Phys. Chem. B 2013, 117, 763), 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 value of 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 dependence 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 interprotein 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.

Coarse-grained modeling of protein second osmotic virial coefficients: sterics and short-ranged attractions.

A series of coarse-grained models, with different levels of structural resolution, were tested to calculate the steric contributions to protein osmotic second virial coefficients (B(22,S)) for proteins ranging from small single-domain molecules to large multidomain molecules, using the recently developed Mayer sampling method. B(22,S) was compared for different levels of coarse-graining: four-beads-per-amino-acid (4bAA), one-bead-per-amino-acid (1bAA), one-sphere-per-domain (1sD), and one-sphere-per-protein (1sP). Values for the 1bAA and 4bAA models were quantitatively indistinguishable for both spherical and nonspherical proteins, and the agreement with values from all-atom models improved with increasing protein size, making the CG approach attractive for large proteins of biotechnological interest. Interestingly, in the absence of detailed structural information, the hydrodynamic radius (R(h)) along with a simple 1sP approximation provided reasonably accurate values for B(22,S) for both globular and highly asymmetric protein structures, while other 1sP approximations gave poorer agreement; this helps to justify the currently empirical practice of estimating B(22,S) from R(h) for large proteins such as antibodies. The results also indicate that either 1bAA or 4bAA CG models may be good starting points for incorporating short-range attractions. Comparison of gD-crystallin B(22) values including both sterics and short-range attractions shows that 1bAA and 4bAA models give equivalent results when properly scaled to account for differences in the number of surface beads in the two CG descriptions. This provides a basis for future work that will also incorporate long-ranged electrostatic attractions and repulsions.

Reexamining protein-protein and protein-solvent interactions from Kirkwood-Buff analysis of light scattering in multi-component solutions.

The classic analysis of Rayleigh light scattering (LS) is re-examined for multi-component protein solutions, within the context of Kirkwood-Buff (KB) theory as well as a more generalized canonical treatment. Significant differences arise when traditional treatments that approximate constant pressure and neglect concentration fluctuations in one or more (co)solvent/co-solute species are compared with more rigorous treatments at constant volume and with all species free to fluctuate. For dilute solutions, it is shown that LS can be used to rigorously and unambiguously obtain values for the osmotic second virial coefficient (B(22)), in contrast with recent arguments regarding protein interactions deduced from LS experiments. For more concentrated solutions, it is shown that conventional analysis over(under)-estimates the magnitude of B(22) for significantly repulsive(attractive) conditions, and that protein-protein KB integrals (G(22)) are the more relevant quantity obtainable from LS. Published data for α-chymotrypsinogen A and a series of monoclonal antibodies at different pH and salt concentrations are re-analyzed using traditional and new treatments. The results illustrate that while traditional analysis may be sufficient if one is interested in only the sign of B(22) or G(22), the quantitative values can be significantly in error. A simple approach is illustrated for determining whether protein concentration (c(2)) is sufficiently dilute for B(22) to apply, and for correcting B(22) values from traditional LS regression at higher c(2) values. The apparent molecular weight M(2, app) obtained from LS is shown to generally not be equal to the true molecular weight, with the differences arising from a combination of protein-solute and protein-cosolute interactions that may, in principle, also be determined from LS.