Deep generative molecular design reshapes drug discovery.

TitleDeep generative molecular design reshapes drug discovery.
Publication TypeJournal Article
Year of Publication2022
AuthorsZeng X, Wang F, Luo Y, Kang S-G, Tang J, Lightstone FC, Fang EF, Cornell W, Nussinov R, Cheng F
JournalCell Rep Med
Volume3
Issue12
Pagination100794
Date Published2022 Dec 20
ISSN2666-3791
KeywordsArtificial Intelligence, Drug Discovery
Abstract

Recent advances and accomplishments of artificial intelligence (AI) and deep generative models have established their usefulness in medicinal applications, especially in drug discovery and development. To correctly apply AI, the developer and user face questions such as which protocols to consider, which factors to scrutinize, and how the deep generative models can integrate the relevant disciplines. This review summarizes classical and newly developed AI approaches, providing an updated and accessible guide to the broad computational drug discovery and development community. We introduce deep generative models from different standpoints and describe the theoretical frameworks for representing chemical and biological structures and their applications. We discuss the data and technical challenges and highlight future directions of multimodal deep generative models for accelerating drug discovery.

DOI10.1016/j.xcrm.2022.100794
Alternate JournalCell Rep Med
PubMed ID36306797
PubMed Central IDPMC9797947
Division: 
Institute of Artificial Intelligence for Digital Health
Category: 
Faculty Publication