JOURNAL ARTICLE

Engineering of a lysosomal-targeted GAA enzyme.

  • Published In: PEDS: Protein Engineering, Design & Selection, 2025, v. 38. P. 1 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Marze, Nicholas; Tikh, Ilya; Benard, Susan; Cheng, Yuxing; Yu, Vincent; Cai, Waijiao; Lavallie, Edward; Lopez, Erin; Wang, Jing; Zamkovaya, Tatyana 3 of 3

Abstract

This article focuses on the rational engineering of a chimeric enzyme to improve enzyme replacement therapy (ERT) for Pompe disease, a genetic disorder caused by deficiency of the acid alpha-glucosidase (GAA) enzyme. The study describes the design of an N-terminal peptide tag (NTPT) derived from insulin-like growth factor II (IGF-II) that enhances binding to the IGF-II receptor (IGF2R) to facilitate lysosomal targeting while minimizing off-target binding to the insulin receptor (INS-R) and IGF-I receptor (IGF1R), which had previously caused adverse effects. Using computational modeling, library screening in CHO cells, and biochemical assays including surface plasmon resonance and cellular uptake tests, several NTPT-GAA variants were identified with improved specificity and preserved enzymatic activity. The lead variant, NTPTSeq44-GAA, demonstrated increased cellular uptake and selective IGF2R binding without detectable off-target receptor interactions, suggesting a promising approach to enhance lysosomal delivery of therapeutic enzymes in Pompe disease and potentially other lysosomal storage disorders.

Additional Information

  • Source:PEDS: Protein Engineering, Design & Selection. 2025/01, Vol. 38, p1
  • Document Type:Article
  • Subject Area:Health and Medicine
  • Publication Date:2025
  • ISSN:1741-0126
  • DOI:10.1093/protein/gzaf001
  • Accession Number:191816610
  • Copyright Statement:Copyright of PEDS: Protein Engineering, Design & Selection is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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