Reduction−Alkylation Strategies for the Modification of Specific Monoclonal Antibody Disulfides

Michael Sun(Seagen (United States)), Kevin S. Beam(Seagen (United States)), Charles G. Cerveny(Seagen (United States)), Kevin J. Hamblett(Seagen (United States)), Richard S. Blackmore(Seagen (United States)), Michael Torgov(Seagen (United States)), Felicia G. M. Handley(Seagen (United States)), Nathan C. Ihle(Seagen (United States)), Peter D. Senter(Seagen (United States)), Stephen C. Alley(Seagen (United States))
Bioconjugate Chemistry
September 1, 2005
Cited by 364Open Access
Full Text

Abstract

Site-specific conjugation of small molecules and enzymes to monoclonal antibodies has broad utility in the formation of conjugates for therapeutic, diagnostic, or structural applications. Precise control over the location of conjugation would yield highly homogeneous materials that could have improved biological properties. We describe for the first time chemical reduction and oxidation methods that lead to preferential cleavage of particular monoclonal antibody interchain disulfides using the anti-CD30 IgG1 monoclonal antibody cAC10. Alkylation of the resulting cAC10 cysteine thiols with the potent antimitotic agent monomethyl auristatin E (MMAE) enabled the assignment of drug conjugation location by purification with hydrophobic interaction chromatography followed by analysis using reversed-phase HPLC and capillary electrophoresis. These analytical methods demonstrated that treating cAC10 with reducing agents such as DTT caused preferential reduction of heavy-light chain disulfides, while reoxidation of fully reduced cAC10 interchain disulfides caused preferential reformation of heavy-light chain disulfides. Following MMAE conjugation, the resulting conjugates had isomeric homogeneity as high as 60-90%, allowing for control of the distribution of molecular species. The resulting conjugates are highly active both in vitro and in vivo and are well tolerated at efficacious doses.


Related Papers

No related papers found

Powered by citation graph analysis