Software for Determining Proteoform Heterogeneity and Protein Expression Fidelity

NIH RePORTER · NIH · R44 · $643,354 · view on reporter.nih.gov ↗

Abstract

The GenNext Technologies Phase II SBIR proposal entitled “Software for Determining Proteoform Heterogeneity and Protein Expression Fidelity,” builds upon a highly successful Phase I program, and will produce a robust, easy-to-use software package, that uniquely assesses the precision of biotherapeutic protein expression. During the last thirty years, the global market for biopharmaceuticals has prospered, achieving sales of more than $176 billion in 2015. The structure and functional activity of biopharmaceuticals are dependent on various aspects of their production and environment. The presence of proteins having improper structures has been linked to adverse drug reactions (ADR), which range from patient symptomatic irritation to morbidity and death. The appearance of ADR’s has alerted the biopharmaceutical industry to the critical role that protein structure plays in the safety and function of biotherapeutics. Biopharmaceutical recombinant protein expression is inherently prone to low-level errors resulting in sequence variants caused by amino acid misincorporation. The expression system and culturing conditions can influence protein product quality attributes, such as translational fidelity and post-translational modifications. These protein variants impact product quality in a number of ways: altered function; altered activity; altered ligand/substrate binding; perturbed protein folding leading to protein aggregation; decreased serum half-life; diminished therapeutic efficacy; and undesired patient immune response. Concerns for efficacy and patient safety necessitates the need to characterize these low-level protein variants. Upon achievement of our aims, our Phase II proposal will provide biopharmaceutical researchers a valuable, new software tool that will detect unwanted biotherapeutic expression variants that can manifest as adverse drug reactions. Our software will enable researchers to discover the presence of protein expression and post-translational variants in a facile manner so that they not only understand the nature of these alterations, but also may improve the expression process to eradicate these artifacts.

Key facts

NIH application ID
10379422
Project number
5R44GM131533-03
Recipient
GENNEXT TECHNOLOGIES, INC.
Principal Investigator
Scot Randy Weinberger
Activity code
R44
Funding institute
NIH
Fiscal year
2022
Award amount
$643,354
Award type
5
Project period
2019-01-01 → 2024-03-31