DeepAR: a novel deep learning-based hybrid framework for the interpretable prediction of androgen receptor antagonists.

ABSTRACT: Drug resistance represents a major obstacle to therapeutic innovations and is a prevalent feature in prostate cancer (PCa). Androgen receptors (ARs) are the hallmark therapeutic target for prostate cancer modulation and AR antagonists have achieved great success. However, rapid emergence of resistance contributing to PCa progression is the ultimate burden of their long-term usage. Hence, the discovery and development of AR antagonists with capability to combat the resistance, remains an avenue for further exploration. Therefore, this study proposes a novel deep learning (DL)-based hybrid framework, named DeepAR, to accurately and rapidly identify AR antagonists by using only the SMILES notation. Specifically, DeepAR is capable of extracting and learning the key information embedded in AR a

SUBMITTER: Schaduangrat N 

PROVIDER: S-EPMC10163717 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature