SSR-DTA: Substructure-aware multi-layer graph neural networks for drug-target binding affinity prediction

Yuansheng Liu, Xinyan Xia, Yongshun Gong, Bosheng Song, Xiangxiang Zeng

Abstract: Highlights•We propose a new DTA prediction model that facilitates drug discovery research.•We resolve issues from incomplete substructure learning and overlooked atoms.•We solve insufficient sequence info and errors in predicted spatial features.•We present a feature fusion tech, capturing their intricate interrelationships.