Venous thromboembolism (VTE) is multifactorial, and established hereditary risk factors explain only part of heritable risk. The protein C (PC) pathway is central to anticoagulant control, and common variants in thrombomodulin and endothelial protein C receptor genes (THBD, PROCR) have been proposed as modulators. In 73 participants, we used standardized in vivo coagulation activation with recombinant activated factor VII (15 µg/kg) and measured thrombin markers and activated protein C (APC) over 8 hours. Endothelial colony-forming cell-based ex vivo experiments were performed in 43 participants. In vivo, the APC area-under-the-curve (AUC)/thrombin-antithrombin complex (TAT) AUC ratio, reflecting the endogenous anticoagulant response relative to thrombin generation, provided the best model fit (adjusted R2=0.345). The APC response was lower in individuals with previous VTE (median 0.13 vs. 0.26; P=.009) and PROCR 655A>G carriers (0.11 vs. 0.26; P=.014), but higher in factor V Leiden (FVL) carriers (0.32 vs. 0.14; P=4.3×10-4) and THBD 1418C>T carriers (0.38 vs. 0.13; P=.032). The THBD 1418C>T effect was driven by reduced TAT AUC (30.6 vs. 82.7 pmol×h/L; P=.032), while the PROCR 655A>G effect reflected a lower APC AUC (8.6 vs. 10.7 pmol×h/L; P=0.04998). Ex vivo, the APC AUC/thrombin AUC ratio was lower with previous VTE and PROCR 655A>G, higher with FVL, and not associated with THBD 1418C>T. No in vivo or ex vivo association was observed for PROCR 4678C>G. This study provides in vivo evidence that common THBD and PROCR variants modulate PC pathway function, establishing the APC response as a sensitive endpoint for subtle genetic effects beyond FVL.
S. Reda, N. Schwarz, Sebastian Eckert et al.· Blood Advances· 0 citations
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. In this work the authors present a scalable mammalian cell-display workflow to identify AI-designed minibinders against cancer surface targets. AI-guided optimization beyond the binding interface improves their expression as chimeric antigen receptors and target-selective killing.
B. Broske, B. McEnroe, S. C. Frechen et al.· Nature Communications· 0 citations