Machine Learning Models of Antibody-Excipient Preferential Interactions for Use in Computational Formulation Design.

Preferential interactions of formulation excipients govern their impact on the stability properties of proteins in solution. The ability to predict these interactions without the need to perform experiments would enable formulation design to begin early in the development of a new antibody therapeutic. With that in mind, we developed a feature set to numerically describe local regions of an antibody's surface for use in machine learning applications. Then, we used these features to train machine learning models for local antibody-excipient preferential interactions for the excipients sorbitol, sucrose, trehalose, proline, arginine·HCl, and NaCl. Our models had accuracies of up to about 85%. We also used linear (elastic net) models to quantify the contribution of antibody surface features to the preferential interaction coefficients, finding that the carbohydrates and proline tend to have similar important features, while the interactions of arginine·HCl and NaCl are governed by charge features. We present several case studies demonstrating how these machine learning models could be used to predict experimental aggregation and viscosity behavior in solution. Finally, we propose an approach to computational formulation design wherein a panel of excipients may be considered while designing an antibody sequence.

Molecular Computations of Preferential Interaction Coefficients of IgG1 Monoclonal Antibodies with Sorbitol, Sucrose, and Trehalose and the Impact of These Excipients on Aggregation and Viscosity.

Preferential interactions of formulation excipients govern their overall interactions with protein molecules, and molecular dynamics simulations allow for the examination of the interactions at the molecular level. We used molecular dynamics simulations to examine the interactions of sorbitol, sucrose, and trehalose with three different IgG1 antibodies to gain insight into how these excipients impact aggregation and viscosity. We found that sucrose and trehalose reduce aggregation more than sorbitol because of their larger size and their stronger interactions with high-spatial aggregation propensity residues compared to sorbitol. Two of the antibodies had high viscosity in sodium acetate buffer, and for these, we found that sucrose and trehalose tended to have opposite effects on viscosity. The data presented here provide further insight into the mechanisms of interactions of these three carbohydrate excipients with the antibody surface and thus their impact on excipient stabilization of antibody formulations.

Understanding the Role of Preferential Exclusion of Sugars and Polyols from Native State IgG1 Monoclonal Antibodies and its Effect on Aggregation and Reversible Self-Association.

PURPOSE: To investigate differences in the preferential exclusion of trehalose, sucrose, sorbitol and mannitol from the surface of three IgG1 monoclonal antibodies (mAbs) and understand its effect on the aggregation and reversible self-association of mAbs at high-concentrations. METHODS: Preferential exclusion was measured using vapor pressure osmometry. Effect of excipient addition on accelerated aggregation kinetics was quantified using size exclusion chromatography and on reversible self-association was quantified using dynamic light scattering. RESULTS: The doubling of excipient concentration in the 0 to 0.5 m range resulted in a doubling of the mAb transfer free energy for all excipients and antibodies tested in this study. Solution pH and choice of buffering agent did not significantly affect the magnitude of preferential exclusion. We find that aggregation suppression for trehalose, sucrose and sorbitol (but not mannitol) correlates with the magnitude of their preferential exclusion from the native state of the three IgG1 mAbs. We also find that addition of sugars and polyols reduced the tendency for reversible self-association in two mAbs that had weakly repulsive or neutral self-interactions in the presence of buffer alone. CONCLUSIONS: The magnitude of preferential exclusion for trehalose, sucrose and sorbitol correlates well with their partial molar volumes in solution. Mannitol is excluded to a greater extent than that expected from its partial molar volume, suggesting specific interactions of mannitol that might be different than the other sugars and polyols tested in this study. Local interactions play a role in the effect of excipient addition on the reversible self-association of mAbs. These results provide further insights into the stabilization of high-concentration mAb formulations by sugars and polyols.

Review of emerging concepts in nanotoxicology: opportunities and challenges for safer nanomaterial design.

Nanotoxicology and nanosafety has been a topic of intensive research for about more than 20 years. Nearly 10 000 research papers have been published on the topic, yet there exists a gap in terms of understanding and ways to harmonize nanorisk assessment. In this review, we revisit critically ignored parameters of nanoscale materials (e.g. band gap factor, phase instability and silver leaching problem, defect and instability plasmonic versus inorganic particles) versus their biological counterparts (cell batch-to-batch heterogeneity, biological barrier model design, cellular functional characteristics) which yield variability and nonuniformity in results. We also emphasize system biology approaches to integrate the high throughput screening methods coupled with in vivo and in silico modeling to ensure quality in nanosafety research. We emphasize and highlight the recommendation regarding bridging the mechanistic gaps in fundamental research and predictive biological response in nanotoxicology. The research community has to develop visions to predict the unforeseen problems that do not exist yet in context with nanotoxicity and public health hazards due to the burgeoning use of nanomaterial in consumer's product.

A universal strategy for regulating mRNA translation in prokaryotic and eukaryotic cells.

We describe a simple strategy to control mRNA translation in both prokaryotic and eukaryotic cells which relies on a unique protein-RNA interaction. Specifically, we used the Pumilio/FBF (PUF) protein to repress translation by binding in between the ribosome binding site (RBS) and the start codon (in Escherichia coli), or by binding to the 5' untranslated region of target mRNAs (in mammalian cells). The design principle is straightforward, the extent of translational repression can be tuned and the regulator is genetically encoded, enabling the construction of artificial signal cascades. We demonstrate that this approach can also be used to regulate polycistronic mRNAs; such regulation has rarely been achieved in previous reports. Since the regulator used in this study is a modular RNA-binding protein, which can be engineered to target different 8-nucleotide RNA sequences, our strategy could be used in the future to target endogenous mRNAs for regulating metabolic flows and signaling pathways in both prokaryotic and eukaryotic cells.

Bidirectional regulation of mRNA translation in mammalian cells by using PUF domains.

The regulation of gene expression is crucial in diverse areas of biological science, engineering, and medicine. A genetically encoded system based on the RNA binding domain of the Pumilio and FBF (PUF) proteins was developed for the bidirectional regulation (i.e., either upregulation or downregulation) of the translation of a target mRNA. PUF domains serve as designable scaffolds for the recognition of specific RNA elements and the specificity can be easily altered to target any 8-nucleotide RNA sequence. The expression of a reporter could be varied by over 17-fold when using PUF-based activators and repressors. The specificity of the method was established by using wild-type and mutant PUF domains. Furthermore, this method could be used to activate the translation of target mRNA downstream of PUF binding sites in a light-dependent manner. Such specific bidirectional control of mRNA translation could be particularly useful in the fields of synthetic biology, developmental biology, and metabolic engineering.

Molecular computations of preferential interactions of proline, arginine.HCl, and NaCl with IgG1 antibodies and their impact on aggregation and viscosity.

Preferential interactions of excipients with the antibody surface govern their effect on the stability of antibodies in solution. We probed the preferential interactions of proline, arginine.HCl (Arg.HCl), and NaCl with three therapeutically relevant IgG1 antibodies via experiment and simulation. With simulations, we examined how excipients interacted with different types of surface patches in the variable region (Fv). For example, proline interacted most strongly with aromatic surfaces, Arg.HCl was included near negative residues, and NaCl was excluded from negative residues and certain hydrophobic regions. The differences in interaction of different excipients with the same surface patch on an antibody may be responsible for variations in the antibody's aggregation, viscosity, and self-association behaviors in each excipient. Proline reduced self-association for all three antibodies and reduced aggregation for the antibody with an association-limited aggregation mechanism. The effects of Arg.HCl and NaCl on aggregation and viscosity were highly dependent on the surface charge distribution and the extent of exclusion from highly hydrophobic patches. At pH 5.5, both tended to increase the aggregation of an antibody with a strongly positive charge on the Fv, while only NaCl reduced the aggregation of the antibody with a large negative charge patch on the Fv. Arg.HCl reduced the viscosities of antibodies with either a hydrophobicity-driven mechanism or a charge-driven mechanism. Analysis of this data presents a framework for understanding how amino acid and ionic excipients interact with different protein surfaces, and how these interactions translate to the observed stability behavior.

CL6mN: Rationally Designed Optogenetic Photoswitches with Tunable Dissociation Dynamics.

The field of optogenetics uses genetically encoded photoswitches to modulate biological phenomena with high spatiotemporal resolution. We report a set of rationally designed optogenetic photoswitches that use the photolyase homology region of A. thaliana cryptochrome 2 (Cry2PHR) as a building block and exhibit highly efficient and tunable clustering in a blue-light dependent manner. CL6mN (Cry2-mCherry-LRP6c with N mutated PPPAP motifs) proteins were designed by mutating and/or truncating five crucial PPP(S/T)P motifs near the C-terminus of the optogenetic Wnt activator Cry2-mCherry-LRP6c, thus eliminating its Wnt activity. Light-induced CL6mN clusters have significantly greater dissociation half-lives than clusters of wild-type Cry2PHR. Moreover, the dissociation half-lives can be tuned by varying the number of PPPAP motifs, with the half-life increasing as much as 6-fold for a variant with five motifs (CL6m5) relative to Cry2PHR. Finally, we demonstrate the compatibility of CL6mN with previously reported Cry2-based photoswitches by optogenetically activating RhoA in mammalian cells.

Kirkwood-Buff-Derived Alcohol Parameters for Aqueous Carbohydrates and Their Application to Preferential Interaction Coefficient Calculations of Proteins.

The CHARMM36 carbohydrate parameter set did not adequately reproduce experimental thermodynamic data of carbohydrate interactions with water or proteins or carbohydrate self-association; thus, a new nonbonded parameter set for carbohydrates was developed. The parameters were developed to reproduce experimental Kirkwood-Buff integral values, defined by the Kirkwood-Buff theory of solutions, and applied to simulations of glycerol, sorbitol, glucose, sucrose, and trehalose. Compared to the CHARMM36 carbohydrate parameters, these new Kirkwood-Buff-based parameters reproduced accurately carbohydrate self-association and the trend of activity coefficient derivative changes with concentration. When using these parameters, preferential interaction coefficients calculated from simulations of these carbohydrates and the proteins lysozyme, bovine serum albumin, α-chymotrypsinogen A, and RNase A agreed well with the experimental data, whereas use of the CHARMM36 parameters indicated preferential inclusion of carbohydrates, in disagreement with the experiment. Thus, calculating preferential interaction coefficients from simulations requires using a force field that accurately reproduces trends in the thermodynamic properties of binary excipient-water solutions, and in particular the trend in the activity coefficient derivative. Finally, the carbohydrate-protein simulations using the new parameters indicated that the carbohydrate size was a major factor in the distribution of different carbohydrates around a protein surface.

Preferential interactions of trehalose, L-arginine.HCl and sodium chloride with therapeutically relevant IgG1 monoclonal antibodies.

Preferential interactions of weakly interacting formulation excipients govern their effect on the equilibrium and kinetics of several reactions of protein molecules in solution. Using vapor pressure osmometry, we characterized the preferential interactions of commonly used excipients trehalose, L-arginine.HCl and NaCl with three therapeutically-relevant, IgG1 monoclonal antibodies that have similar size and shape, but differ in their surface hydrophobicity and net charge. We further characterized the effect of these excipients on the reversible self-association, aggregation and viscosity behavior of these antibody molecules. We report that trehalose, L-arginine.HCl and NaCl are all excluded from the surface of the three IgG1 monoclonal antibodies, and that the exclusion behavior is linearly related to the excipient molality in the case of trehalose and NaCl, whereas a non-linear behavior is observed for L-arginine.HCl. Interestingly, we find that the magnitude of trehalose exclusion depends upon the nature of the protein surface. Such behavior is not observed in case of NaCl and L-arginine.HCl as they are excluded to the same extent from the surface of all three antibody molecules tested in this study. Analysis of data presented in this study provides further insight into the mechanisms governing excipient-mediated stabilization of mAb formulations.

Translational repression using BIV Tat peptide-TAR RNA interaction in mammalian cells.

We developed a strategy to create novel genetically encoded switches based on translational repression. We illustrated its efficacy by incorporating two copies of an RNA hairpin in the 5'-untranslated region (UTR) of a target mRNA and demonstrating 7-fold translational repression upon expression of a ligand - the BIV Tat peptide.

Light-inducible activation of target mRNA translation in mammalian cells.

A genetically encoded optogenetic system was constructed that activates mRNA translation in mammalian cells in response to light. Blue light induces the reconstitution of an RNA binding domain and a translation initiation domain, thereby activating target mRNA translation downstream of the binding sites.