Computational Design and Evaluation of De Novo Protein Minibinders Targeting Specific Sites of STAT3

STAT3 is a transcription factor involved in the progression of many types of cancer, which makes it an attractive therapeutic target. Small-molecule STAT3 inhibitors have experienced a high failure rate in clinical trials, indicating alternative approaches may be warranted. To address these limitations, we used BindCraft, a modern AI-driven protein design tool, to create miniprotein binder candidates against several sites of STAT3. We selected seven target hotspots on the SH2, linker, DNA-binding and coiled-coil domains of STAT3. Of 139 designs that passed BindCraft's filters, 11 high-confidence binders emerged from five of the seven hotspots. These candidate binders were evaluated with AlphaFold3 (AF3). All eleven are predicted to dock with their intended domain; most within 4.5 Å of one or more of their targeted hotspot residues. Several minibinders are predicted to dock simultaneously to STAT3 without overlap. Such pairs have the potential to constitute STAT3 sandwich assays. BLASTp searches found no matches with known protein sequences for six of the binders and only very low-significance matches for the other five. We disclose herein the sequences of our top binders targeting diverse regions of the STAT3 surface with the hope that experimental validation by the broader research community will yield promising leads for preclinical drug development against this important cellular regulator.