دورية أكاديمية
In silico off-target profiling for enhanced drug safety assessment.
| العنوان: | In silico off-target profiling for enhanced drug safety assessment. |
|---|---|
| المؤلفون: | Liu, Jin, Gui, Yike, Rao, Jingxin, Sun, Jingjing, Wang, Gang, Ren, Qun, Qu, Ning, Niu, Buying, Chen, Zhiyi, Sheng, Xia, Wang, Yitian, Zheng, Mingyue, Li, Xutong |
| المصدر: | Acta Pharmaceutica Sinica B; Jul2024, Vol. 14 Issue 7, p2927-2941, 15p |
| مصطلحات موضوعية: | GRAPH neural networks, DRUG side effects, MEDICATION safety, DRUG interactions, DRUG development |
| مستخلص: | Ensuring drug safety in the early stages of drug development is crucial to avoid costly failures 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 precise 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 differentiation of drugs under various ATC codes and the classification of compound toxicity. Furthermore, the predicted 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 Using the withdrawn drug Pergolide as an example, we elucidate the mechanisms underlying ADRs at the target level, contributing to the exploration of the potential clinical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 assessment of compound safety/toxicity based on off-target identification, deduces potential ADRs of drugs, and ultimately promotes the secure development of drugs. An advanced framework for drug safety assessment, encompassing precise drug off-target profile prediction and its utilization in ATC classification, toxicity prediction, and ADR enrichment analysis. [Display omitted] [ABSTRACT FROM AUTHOR] |
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| قاعدة البيانات: | Supplemental Index |
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