Development of in silico models to predict viscosity and mouse clearance using a comprehensive analytical data set collected on 83 scaffold-consistent monoclonal antibodies.

Biologic drug discovery pipelines are designed to deliver protein therapeutics that have exquisite functional potency and selectivity while also manifesting biophysical characteristics suitable for manufacturing, storage, and convenient administration to patients. The ability to use computational methods to predict biophysical properties from protein sequence, potentially in combination with high throughput assays, could decrease timelines and increase the success rates for therapeutic developability engineering by eliminating lengthy and expensive cycles of recombinant protein production and testing. To support development of high-quality predictive models for antibody developability, we designed a sequence-diverse panel of 83 effector functionless IgG1 antibodies displaying a range of biophysical properties, produced and formulated each protein under standard platform conditions, and collected a comprehensive package of analytical data, including in vitro assays and in vivo mouse pharmacokinetics. We used this robust training data set to build machine learning classifier models that can predict complex protein behavior from these data and features derived from predicted and/or experimental structures. Our models predict with 87% accuracy whether viscosity at 150 mg/mL is above or below a threshold of 15 centipoise (cP) and with 75% accuracy whether the area under the plasma drug concentration-time curve (AUC0-672 h) in normal mouse is above or below a threshold of 3.9 × 106 h x ng/mL.

Contributions of a disulfide bond to the structure, stability, and dimerization of human IgG1 antibody CH3 domain.

Recombinant human monoclonal antibodies have become important protein-based therapeutics for the treatment of various diseases. The antibody structure is complex, consisting of beta-sheet rich domains stabilized by multiple disulfide bridges. The dimerization of the C(H)3 domain in the constant region of the heavy chain plays a pivotal role in the assembly of an antibody. This domain contains a single buried, highly conserved disulfide bond. This disulfide bond was not required for dimerization, since a recombinant human C(H)3 domain, even in the reduced state, existed as a dimer. Spectroscopic analyses showed that the secondary and tertiary structures of reduced and oxidized C(H)3 dimer were similar, but differences were observed. The reduced C(H)3 dimer was less stable than the oxidized form to denaturation by guanidinium chloride (GdmCl), pH, or heat. Equilibrium sedimentation revealed that the reduced dimer dissociated at lower GdmCl concentration than the oxidized form. This implies that the disulfide bond shifts the monomer-dimer equilibrium. Interestingly, the dimer-monomer dissociation transition occurred at lower GdmCl concentration than the unfolding transition. Thus, disulfide bond formation in the human C(H)3 domain is important for stability and dimerization. Here we show the importance of the role played by the disulfide bond and how it affects the stability and monomer-dimer equilibrium of the human C(H)3 domain. Hence, these results may have implications for the stability of the intact antibody.

Prediction of the Hydrogen Peroxide-Induced Methionine Oxidation Propensity in Monoclonal Antibodies.

Methionine oxidation in therapeutic antibodies can impact the product's stability, clinical efficacy, and safety and hence it is desirable to address the methionine oxidation liability during antibody discovery and development phase. Although the current experimental approaches can identify the oxidation-labile methionine residues, their application is limited mostly to the development phase. We demonstrate an in silico method that can be used to predict oxidation-labile residues based solely on the antibody sequence and structure information. Since antibody sequence information is available in the discovery phase, the in silico method can be applied very early on to identify the oxidation-labile methionine residues and subsequently address the oxidation liability. We believe that the in silico method for methionine oxidation liability assessment can aid in antibody discovery and development phase to address the liability in a more rational way.

Increased aggregation propensity of IgG2 subclass over IgG1: role of conformational changes and covalent character in isolated aggregates.

Aggregation of human therapeutic antibodies represents a significant hurdle to product development. In a test across multiple antibodies, it was observed that IgG1 antibodies aggregated less, on average, than IgG2 antibodies under physiological pH and mildly elevated temperature. This phenomenon was also observed for IgG1 and IgG2 subclasses of anti-streptavidin, which shared 95% sequence identity but varied in interchain disulfide connectivity. To investigate the structural and covalent changes associated with greater aggregation in IgG2 subclasses, soluble aggregates from the two forms of anti-streptavidin were isolated and characterized. Sedimentation velocity analytical ultracentrifugation (SV-AUC) measurements confirmed that the aggregates were present in solution, and revealed that the IgG1 aggregate was composed of a predominant species, whereas the IgG2 aggregate was heterogeneous. Tertiary structural changes accompanied antibody aggregation as evidenced by greater ANS (8-Anilino-1-naphthalene sulfonic acid) binding to the aggregates over monomer, and differences in disulfide character and tryptophan environments between monomer, oligomer and aggregate species, as observed by near-UV circular dichroism (CD). Differences between subclasses were observed in the secondary structural changes that accompanied aggregation, particularly in the intermolecular ß-sheet and turn structures between the monomer and aggregate species. Free thiol determination showed ∼2.4-fold lower quantity of free cysteines in the IgG1 subclass, consistent with the 2.4-fold reduction in aggregation of the IgG1 form when compared with IgG2 under these conditions. These observations suggested an important role for disulfide bond formation, as well as secondary and tertiary structural transitions, during antibody aggregation. Such degradations may be minimized using appropriate formulation conditions.