TIGIT: epitope-driven designed with nM affinity

Computational epitope-driven antibody designed against TIGIT with nM affinity. From trillion of un-paired scFv bank, MAbSilico designed and optimized antibodies against a predetermined epitope in 21 days with 90% success rate.

De Novo design
Tools used
Target structural modeling
Target surface characterization

Computational epitope-driven antibody design against TIGIT with nM affinity:
TIGIT is a major immune checkpoint target to develop new drugs for cancer treatment. More than 10 biotech and pharma companies are trying to design the drug for tomorrow’s breakthrough treatment. While 9 clinical trials are ongoing, more than 1000 of anti-TIGIT antibodies are described in patents. MAbSilico’s goal was to design, from a non-paired scFv naïve bank, antibodies directed against a predetermined epitope of TIGIT with nanomolar affinity.

"We discovered new drug candidates in a couple of days compared to several months"

Testimonial from Nicolas Poirier, CEO of OSE: What was impressive is the high success rate higher than 50%, compared to the usual 5%, which allows our company to accelerate, to decrease the risks and to develop new immunotherapies for the patients."

Out of trillions of possibilities, MAbSilico managed to design, in 21 days, 300 antibodies among which 90% were validated with bioassays to bind TIGIT. Computational affinity maturation was then performed on the best candidates and BLI showed that sub-nanomolar affinity was reached. During the design and optimization, MAbSilico evaluated the criteria to limit cross-reactivity and avoid liability issues, in order to get the best candidates fulfilling developability specifications and freedom-to-operate.

Highlights of computational epitope-driven antibody design against TIGIT