Protein degradation studies are of interest due to the high demand for protein-based therapeutics in the pharmaceutical industry. However, formulation efficiency is limited by the degradation of the desired products during multiple points of the biomanufacturing process. While the use of additives has significantly reduced degradation, screening of additives and stabilizers is greatly limited by current understanding of the degradation mechanisms. For this purpose, computational models have been developed to quantify the properties associated with each degradation pathway. One such form of degradation is deamidation or the spontaneous conversion of net neutral Asparagine and Glutamine into their acidic counterparts. In this study, we analyzed how selectivity towards specific deamidation pathways was influenced by the interactions between functional groups in model dipeptides using quantum chemistry, statistical thermodynamics, and reaction pathway analysis. Our studies have established trends in thermodynamic and kinetic parameters as a function of each reaction. Additionally, the parameters and trends computed by our study were found to be in agreement with experimental literature.

Influence of competing pathways on non-enzymatic protein deamidation at a neutral pH

ACS Fall 2021

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