Functional selection of protease inhibitory antibodies.

Published

Journal Article

Critical for diverse biological processes, proteases represent one of the largest families of pharmaceutical targets. To inhibit pathogenic proteases with desired selectivity, monoclonal antibodies (mAbs) hold great promise as research tools and therapeutic agents. However, identification of mAbs with inhibitory functions is challenging because current antibody discovery methods rely on binding rather than inhibition. This study developed a highly efficient selection method for protease inhibitory mAbs by coexpressing 3 recombinant proteins in the periplasmic space of Escherichia coli-an antibody clone, a protease of interest, and a β-lactamase modified by insertion of a protease cleavable peptide sequence. During functional selection, inhibitory antibodies prevent the protease from cleaving the modified β-lactamase, thereby allowing the cell to survive in the presence of ampicillin. Using this method to select from synthetic human antibody libraries, we isolated panels of mAbs inhibiting 5 targets of 4 main protease classes: matrix metalloproteinases (MMP-14, a predominant target in metastasis; MMP-9, in neuropathic pain), β-secretase 1 (BACE-1, an aspartic protease in Alzheimer's disease), cathepsin B (a cysteine protease in cancer), and Alp2 (a serine protease in aspergillosis). Notably, 37 of 41 identified binders were inhibitory. Isolated mAb inhibitors exhibited nanomolar potency, exclusive selectivity, excellent proteolytic stability, and desired biological functions. Particularly, anti-Alp2 Fab A4A1 had a binding affinity of 11 nM and inhibition potency of 14 nM, anti-BACE1 IgG B2B2 reduced amyloid beta (Aβ40) production by 80% in cellular assays, and IgG L13 inhibited MMP-9 but not MMP-2/-12/-14 and significantly relieved neuropathic pain development in mice.

Full Text

Duke Authors

Cited Authors

  • Lopez, T; Mustafa, Z; Chen, C; Lee, KB; Ramirez, A; Benitez, C; Luo, X; Ji, R-R; Ge, X

Published Date

  • August 13, 2019

Published In

Volume / Issue

  • 116 / 33

Start / End Page

  • 16314 - 16319

PubMed ID

  • 31363054

Pubmed Central ID

  • 31363054

Electronic International Standard Serial Number (EISSN)

  • 1091-6490

Digital Object Identifier (DOI)

  • 10.1073/pnas.1903330116

Language

  • eng

Conference Location

  • United States