Predicting the interaction between RGR and TRPV1 using chai-1

Summary: Abstract Body: RPE-retinal G protein-coupled receptor (RGR), as an important photoreceptor protein, is involved in various physiological functions in the human body, such as the perception of light signals and the regulation of the retinaldehyde cycle. Our previous research found that RGR is also expressed in the skin and influences the proliferation and migration of keratinocytes. In recent experiments, we found that the expression of RGR in the skin also be regulated by temperature (data not show). TRPV1 (Transient Receptor Potential Vanilloid 1) is a non-selective cation channel protein and a typical heat-sensitive ion channel. In previous studies, it was found that RGR and TRPV1 appear to share common downstream factors, such as Ca2+. All these observations may indicate that the RGR and TRPV1 have certain interaction or even form complex. To investigate whether the RGR and TRPV1 interact during physiological processes, we used the Chai-1, an open-source tool, to predict the protein complex of RGR and TRPV1. By using the Chai-1 default parameters, several protein complex structures were successfully generated. Using the TRPV1 (PDB Code: 8x94) protein structure chain A aligned with the protein complex TRPV1 part, a RMSD value, 2.01, was got, which indicated that the predicted protein complex accuracy is acceptable. Further analysis was conducted for the predicted protein complex, a special loop (DTCPDPLDGDPNSRPPP) from TRPV1 was identified which shows strong interaction with RGR protein, lots of hydrogen-bonding were found between this loop and RGR protein. This exploration work suggest that the two proteins may interact. In future studies, we will continue to study the potential interaction through molecular dynamic simulation and experimentally validate their potential interaction and determine whether they jointly regulate skin physiological functions. Rui Wang¹, Renfu Lai², Wei Zhang¹, Wen Zeng¹, Hongguang Lu¹ 1. Dermatology, Guizhou Medical University, Guiyang, Guizhou, China. 2. Xiaotiaofu (Shanghai) Technology Co., Ltd, Shanghai, China. Bioinformatics, Computational Biology, and Imaging