Structure Based Prediction of Asparagine Deamidation Propensity in Monoclonal Antibodies

Abstract

Identification of asparagine (Asn) sites that are prone to deamidation is critical for the development of therapeutic monoclonal antibodies (mAbs). Despite a common chemical degradation pathway, the rates of Asn deamidation can vary dramatically among different sites, and prediction of the sensitive deamidation sites is still challenging. In this study, characterization of Asn deamidation for five IgG1 and five IgG4 mAbs under both normal and stressed conditions revealed dramatic differences in the Asn deamidation rates. A comprehensive analysis of the deamidation sites indicated that the deamidation rate differences could be explained by differences in the local structure conformation, structure flexibility and solvent accessibility. A decision tree was developed to predict the deamidation propensity for all Asn sites in IgG mAbs based on the analysis of these three structural parameters. This decision tree will allow potential Asn deamidation hot spots to be identified early in development.

Deamidation and isomerization liability analysis of 131 clinical-stage antibodies

“…Modification is only observed in the two exceptional cases listed earlier (anifrolumab and lirilumab, exhibiting isomerization and deamidation, respectively). It had been proposed previously that higher local flexibility, 23,30 as reflected in higher B-factor values, 58 may correlate with propensity for isomerization or deamidation. To examine the specific effect due to a presence or absence of Pro at L95, we performed an analysis of B-factors using a set of 359 crystal structures of un-complexed kappa antibodies from the PDB having L3 length of 9; n = 337 with Pro and n = 22 without Pro.…”

“…Although local structure is known to modulate deamidation and isomerization rates, 21,23,30 the ability to predict such local structural effects from sequence alone is not fully developed. For instance, 9.8% deamidation was observed at H54 upon high pH stress of rituximab.…”

“…These findings suggest that the complex global dynamics of the molecule may result in structural differences in the CDRs that likely contribute to the observed chemical stability. In light of this observation, we suspect that the sequence and structure inputs into recent predictive methods 23,30 may be too similar (as currently encoded or examined) to allow for meaningful differentiation between the modified and nonmodified instances. For example, referring to the NH example above, preliminary homology models of the three antibodies (tabalumab, patritumab and zanolimumab) followed by analysis as in Yan et al 30 leads to very similar values for the key descriptors (secondary structure, solvent accessibility and Cγ to N distance) at the NH motif, and thus no suggestion that they may differ in their deamidation propensity.…”

“…Looking forward, the field appears to be working towards a priori predictions of chemical modifications. 7,23,30 Currently, cursory ab initio analysis can be performed at the amino acid sequence level to identify potential degradation sequence liabilities based on motifs of two amino acids, such as NG or DG sequences; however, simple counting of such motifs leads to a high frequency of false positives. For example, in the most extensive study to date, 37 mAbs were stressed at pH 6.0 at 40°C for two weeks, which resulted in 67% or 21% of samples with expected-labile NG or NS motifs showing detectable levels of deamidation, respectively.…”

Prediction of methionine oxidation risk in monoclonal antibodies using a machine learning method

“…9,11 Other antibody liabilities due to chemical stress in the manufacturing process include the deamidation of asparagine (Asn), isomerization of aspartic acid (Asp) and oxidation of methionine (Met) and tryptophan (Trp) residues. To this end, studies on prediction models for Asn deamidation, 12,13 Asp isomerization 12 and Trp oxidation 9 have been reported.…”