The binding affinity prediction of PI3K / Akt / mTOR signaling pathway proteins with drugs based on deep learning method
Dayan Liu, Xun Wang, Zhenzhen Du, Jiali Liu, Yue Zhong, Qingyu Tian · 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · 2021
Human papillomavirus (HPV) infection is linked to several diseases, the most prominent of which are cervical cancer and genital condyloma acuminatum. PI3K-Akt-mTOR signaling pathway is one of the most important signaling pathway in the regulation of proliferation, differentiation and apoptosis of human cervical cancer cells, and this pathway has the potential to become a novel target for the development of cervical cancer therapeutics. Previous studies have suggested that drug therapy can modulate PI3K-AKT-mTOR pathway to reduce HPV viral load effectively through autophagy and apoptosis. Therefore, in our study, in order to find drugs that can regulate this pathway, we collected more than 20 proteins related to this pathway and used deep learning models to predict protein-ligand binding affinity, finally listed the drug molecules with the highest predicted affinity score for each protein molecule.