Ali Bootwala1†, Hyun Hwan An2†, Meghan Whitney Franklin1, Benjamin J. Manning1, Lucy Y. Xu1, Shruti Panchal1, Joseph D. Garlick1, Reshica Baral1, Michael E. Hudson1, Gevorg Grigoryan1, Mark A. Murakami2, Kristen Hopson1* and Daniel S. Leventhal1*
What Bootwala, Hwan An, and colleagues show in their paper is a method of creating “Re-surfaced proteins”, that is variants of therapeutic proteins that retain protein function yet have significant modification to their surface so that they avoid binding to pre-existing ADAs. This was accomplished by using structure-guided, machine learning-based computational methods to generate a series of Re-surfaced proteins that mutate an unprecedented number of surface amino acid residues (up to 58) thereby disrupting ADA binding epitopes. E.coli-derived L‑Asparaginase (ASN), an enzyme that is a standard component of many treatment regimens for pediatric and adult acute lymphocytic leukemia (ALL), was Re-surfaced as a clinically relevant proof-of-concept demonstration. The resurfaced ASNs showed significantly reduced binding to ADAs from mouse, rabbit, and ALL patient samples. In addition, protein Re-surfacing ameliorated acute hypersensitivity in a mouse model which exhibits similar responses to those observed in a significant proportion of ALL patients. While applied to ASN in this study, the approach could be utilized more broadly to provide much needed alternatives or second line therapies for other lifesaving biotherapeutics.
To read the full peer-reviewed publication in Frontiers in Immunology, please click here.