Efficient Design of Affilin(®) Protein Binders for HER3.

Engineered scaffold-based proteins that bind to concrete targets with high affinity offer significant advantages over traditional antibodies in theranostic applications. Their development often relies on display methods, where large libraries of variants are physically contacted with the desired target protein and pools of binding variants can be selected. Herein, we use a novel combined artificial intelligence/physics-based computational framework and phage display approach to obtain ubiquitin based Affilin(®) proteins targeting the human epidermal growth factor receptor 3 (HER3) extracellular domain, a relevant tumor target. As traditional antibodies against the receptor have failed so far, we sought to provide molecules in a smaller more versatile format to cover the medical need in HER3 related diseases. We demonstrate that the developed in silico pipeline can generate de novo Affilin(®) proteins binding the biochemical HER3 target using a small training set of <1000 sequences. The classical phage display yielded primary candidates with low nanomolar affinities to the biochemical target and HER3-expressing cells. The latter could be further optimized by phage display and computational maturation alike. These combined efforts resulted in four HER3 ligands with high affinity, cell binding, and serum stability with theranostic potential.