Computational Protein Design of Robust and Scalable Recombinant HRP and Poly-HRP Reagents

About This Grant

Project Summary: Horseradish peroxidase (HRP) is a critical reporter enzyme widely used in diagnostics, and research tools due to its ability to amplify signal in assays like ELISAs, Western blots, and immunohistochemistry. However, current HRP reagents are largely derived from horseradish root, which results in heterogeneous mixtures of isoenzymes with varying glycosylation patterns, activity, and stability. This variability compromises reproducibility, complicates regulatory compliance, and presents significant manufacturing challenges. Moreover, recombinant HRP production has been historically hindered by its complex structural requirements, including the incorporation of a heme cofactor, multiple disulfide bonds, calcium ions, and glycosylation, which are difficult to replicate in microbial hosts. As a result, efforts to create a consistent, recombinant HRP alternative have proven unsuccessful, with current solutions like poly-HRP showing significant limitations in batch-to-batch consistency which is critical in high sensitivity assays. This SBIR Phase I project aims to overcome these challenges by using state-of-the-art computational protein design to develop a novel recombinant HRP mimetic that exhibits high stability, catalytically active properties, and scalability. Our approach involves two primary innovations: the design of a stable, de novo HRP enzyme that can be expressed efficiently in microbial systems, and the development of a self-assembling HRP nanoparticle that enables precise control of enzyme stoichiometry and enhances performance consistency. The proposed HRP mimetic will not only ensure high-quality production of HRP reagents but also enable genetic fusions with other functional domains, opening the door to more consistent and reliable diagnostic development. Our team has developed promising preliminary data indicating a highly de-risked application that will have a big impact. Our preliminary data demonstrate the feasibility of using computational protein design to create a de novo HRP that is easy to manufacture, and with this grant, we intend to transform it into a high-impact product with broad applications.