ICASSP 2024accepted0 citations
TD-GPT: Target Protein-Specific Drug Molecule Generation GPT
Zhengda He, Linjie Chen, Jiaying Xu, Hao Lv, Rui-ning Zhou, Jianhua Hu, Yadong Chen, Yang Gao
Abstract
Drug discovery faces challenges due to the vast chemical space and complex drug-target interactions. This paper proposes a novel deep learning framework TD-GPT for targeted drug molecule generation. TD-GPT comprises a linear Transformer for drug-target affinity prediction, an affinity-enhanced protein encoder using sequences, and a target-specific attention module in the molecular Transformer decoder. Experiments demonstrate TD-GPT’s efficiency in generating valid, novel molecules with high affinity and specificity for desired targets without target fine-tuning. The model provides a new paradigm for accelerated, cost-effective drug discovery.
BibTeX
@inproceedings{icassp2024_tdgpttargetprote,
title = {TD-GPT: Target Protein-Specific Drug Molecule Generation GPT},
author = {Zhengda He and Linjie Chen and Jiaying Xu and Hao Lv and Rui-ning Zhou and Jianhua Hu and Yadong Chen and Yang Gao},
booktitle = {ICASSP 2024},
year = {2024}
}