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Recent advancements in conversational large language models (LLMs), such as ChatGPT, have demonstrated remarkable promise in various domains, including drug discovery. However, existing works mainly focus on investigating the capabilities of conversational LLMs on chemical reaction and retrosynthesis. While drug editing, a critical task in the drug discovery pipeline, remains largely unexplored. To bridge this gap, we propose ChatDrug, a framework to facilitate the systematic investigation of drug editing using LLMs. ChatDrug jointly leverages a prompt module, a retrieval and domain feedback (ReDF) module, and a conversation module to streamline effective drug editing. We empirically show that ChatDrug reaches the best performance on 33 out of 39 drug editing tasks, encompassing small molecules, peptides, and proteins. We further demonstrate, through 10 case studies, that ChatDrug can successfully identify the key substructures (e.g., the molecule functional groups, peptide motifs, and protein structures) for manipulation, generating diverse and valid suggestions for drug editing. Promisingly, we also show that ChatDrug can offer insightful explanations from a domain-specific perspective, enhancing interpretability and enabling informed decision-making. This research sheds light on the potential of ChatGPT and conversational LLMs for drug editing. It paves the way for a more efficient and collaborative drug discovery pipeline, contributing to the advancement of pharmaceutical research and development.
Author Information
Shengchao Liu (Mila, Université de Montréal)
Jiongxiao Wang (Arizona State University)
Yijin Yang (Arizona State University)
Chengpeng Wang (University of Illinois at Urbana-Champaign)
Ling Liu (Princeton University)
Hongyu Guo (National Research Council of Canada)
Hongyu GUO is a Senior Researcher Officer at the Digital Technologies Research Center of the National Research Council Canada (NRC). He is also an Adjunct Professor in the School of Electrical Engineering and Computer Science at the University of Ottawa.
Chaowei Xiao (Umich)
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