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Broske, B.* ; McEnroe, B.A.* ; Frechen, S.C.* ; Kempchen, T.N.* ; Fandrey, C.I.* ; Tan, E.* ; Ferber, D.* ; Yong, M.C.R.* ; Kleinert, M.* ; Messmer, J.M.* ; Konopka, P.* ; Hoch, A.* ; Blumenstock, K.* ; Tödtmann, J.M.P.* ; Oldenburg, J.* ; Rühl, H.* ; Semaan, A.* ; Toma, M.I.* ; Markova, K.* ; Kobold, S. ; Rollenske, T.* ; Geyer, M.* ; Menzel, S.* ; Bald, T.* ; Schmid-Burgk, J.L.* ; Hagelueken, G.* ; Hölzel, M.*

AI-enabled discovery and biochemical optimization of minibinders targeting cancer cell-surface proteins.

Nat. Commun. 17:8736 (2026)
Publ. Version/Full Text Research data DOI PMC
Open Access Gold
Creative Commons Lizenzvertrag
Experimental validation and functional optimization remain bottlenecks in AI-based protein design. We present a scalable workflow for developing AI-designed minibinders against cancer-associated surface proteins. Screening thousands of designs using mammalian cell-surface display identifies several high-affinity PD-L1 minibinders but far fewer for CD276 (B7-H3) and VTCN1 (B7-H4), highlighting substantial target dependence. Interface predicted template modeling (ipTM) scores generated by Chai-1 with ESM embeddings correlate with binding success and capture deleterious effects of interface mutations. Fluorophore-labeled AI-minibinders enable flow-cytometric staining comparable to conventional antibodies. However, when incorporated into chimeric antigen receptors (CAR), some show poor cell-surface trafficking and limited functionality. Redesign through a genetic algorithm-based diversification strategy that preserves the binding interface while changing non-binding surfaces experimentally reveals an isoelectric point (pI) window that improves CAR expression and enhances target-selective tumor cell killing. Our findings identify biochemical optimization beyond the binding interface as a critical requirement for translating AI-minibinders into functional applications.
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Publication type Article: Journal article
Document type Scientific Article
Keywords Prediction
ISSN (print) / ISBN 2041-1723
e-ISSN 2041-1723
Journal Nature Communications
Quellenangaben Volume: 17, Issue: 1, Pages: , Article Number: 8736 Supplement: ,
Publisher Springer
Publishing Place London
Reviewing status Peer reviewed
Institute(s) Unit for Clinical Pharmacology (KKG-EKLiP)
Grants Deutsche Forschungsgemeinschaft (German Research Foundation)
Melanoma Research Alliance (MRA)