Ming-Tang Chen | Principal Scientist
Merck

Ming-Tang Chen, Principal Scientist, Merck

Ming-Tang Chen is a Principal Scientist at Merck Discovery Biologics. An established subject matter expert on glycobiology, in vitro display technologies and library design and construction, Ming-Tang Leads Merck Biologics Design & Display group.

Appearances:



Festival of Biologics Day 2 @ 11:40

Merck Yeast Display and Secretion Platform for Antibody Discovery and Protein Engineering

In-vitro display technologies offer adaptable approaches to the discovery and engineering of binding proteins. Most in-vitro display platforms use small antibody fragments like scFv, but the majority of approved therapeutic antibodies are IgGs. As a result, lead molecules isolated from in vitro display must be cloned and expressed in the IgG format to confirm binding and be characterized. This reformatting process creates a bottleneck. It is thus desirable to create IgG display and co-secretion system to streamline the antibody discovery and engineering process. We created a versatile display system that enables simultaneous display and secretion of full-length mAbs on the surface of the mating competent yeast Saccharomyces cerevisiae. Dimerization of the Fc to a GPI anchored bait Fc results in tethered half-IgGs to the yeast cell. Through yeast mating of haploid heavy chain and light chain libraries, very large combinatorial full-length IgG libraries can be displayed on diploid cells, and high affinity antibody can be isolated from the library. When the bait Fc is suppressed, hit clones in full-length mAb format can be secreted and purified and used for downstream physicochemical, binding, and functional characterization. In a model experiment, we used this display platform and synthetic naïve library to generate mAbs against a soluble cytokine. We performed a fast follow up light chain shuffle of lead clones, and then structure guided affinity maturation, demonstrating the ability of this platform to generate high affinity and potent antibodies with broad sequence diversity and epitope coverage.

last published: 31/Jan/23 09:55 GMT
last published: 31/Jan/23 09:55 GMT

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