Molecular modeling of Proteinase-Activated Receptor 1 in complex with Thrombin Receptor Activator Peptide 6.

The protease-activated receptor 1 (PAR1) and its activator thrombin re-ceptor activator peptide 6 (TRAP6) play crucial roles in various physiologi-cal and pathological processes, including hemostasis, thrombosis, and cancer progression. Although the interaction between PAR1 and TRAP6 has been heavily studied using experimental technique such as mutagenesis, structural data remains scarce due to the technical hardship of studying membrane pro-teins such as PAR1. In this study, we employed an integrative modeling approach to elucidate the structure of the PAR1-TRAP6 complex. Leveraging state-of-the-art AI-based protein modeling tools, including AlphaFold2 and ESMFOLD, we in-tegrated HADDOCK, a physics-based method to refine predictions. Overall, the predicted structures are in good agreement with the experimental data available in the literature. Our model unveiled a new T-shaped pi-stacking interaction between TRAP6s F2 and PAR1s Y360. The integrative modeling approach combining the predictions of the deep learning model with a physics-based method proves to be an interesting strat-egy for solving challenging membrane protein structures with high confidence. Our model of the PAR1-TRAP6 complex will be an interesting starting point for further investigation of the activation of PAR1 by TRAP6.