In silico off-target profiling for enhanced drug safety assessment

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外文摘要：Ensuring drug safety in the early stages of drug development is crucial to avoid costly fail-ures in subsequent phases.However,the economic burden associated with detecting drug off-targets and potential side effects through in vitro safety screening and animal testing is substantial.Drug off-target interactions,along with the adverse drug reactions they induce,are significant factors affecting drug safety.To assess the liability of candidate drugs,we developed an artificial intelligence model for the pre-cise prediction of compound off-target interactions,leveraging multi-task graph neural networks.The outcomes of off-target predictions can serve as representations for compounds,enabling the differentia-tion of drugs under various ATC codes and the classification of compound toxicity.Furthermore,the pre-dicted off-target profiles are employed in adverse drug reaction(ADR)enrichment analysis,facilitating the inference of potential ADRs for a drug.Using the withdrawn drug Pergolide as an example,we eluci-date the mechanisms underlying ADRs at the target level,contributing to the exploration of the potential clinical relevance of newly predicted off-target interactions.Overall,our work facilitates the early assess-ment of compound safety/toxicity based on off-target identification,deduces potential ADRs of drugs,and ultimately promotes the secure development of drugs.

外文关键词：

Drug safetyOff-target predictionAdverse drug reactionsToxicityMolecular representationArtificial intelligence

作者：

Jin Liu、Yike Gui、Jingxin Rao、Jingjing Sun、Gang Wang、Qun Ren、Ning Qu、Buying Niu、Zhiyi Chen、Xia Sheng、Yitian Wang、Mingyue Zheng、Xutong Li

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作者单位：

College of Pharmaceutical Sciences,Zhejiang University,Hangzhou 310058,China

Drug Discovery and Design Center State Key Laboratory of Drug Research,Shanghai Institute of Materia Medica Chinese Academy of Sciences,Shanghai 201203,China

Nanjing University of Chinese Medicine,Nanjing 210023,China

University of Chinese Academy of Sciences,Beijing 100049,China

School of Pharmaceutical Science and Technology,Hangzhou Institute for Advanced Study,Hangzhou 330106,China

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基金：

National Key Research and Development Program of ChinaNational Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaLingang LaboratorySIMM-SHUTCM Traditional Chinese Medicine Innovation Joint Research ProgramShanghai Municipal Science and Technology Major Project

项目编号：

2022YFC3400504T22250028227385582204278LG202102-01-02E2G805H

出版年：

2024

DOI：

10.1016/j.apsb.2024.03.002

药学学报(英文版)

CSTPCD

ISSN：

年,卷(期)：2024.14(7)