计算方法可以识别药物诱导的结构性心脏毒性的转录指纹
Victoria P W Au Yeung1,2, Olga Obrezanova3, Jiarui Zhou4
1Safety Sciences, Clinical Pharmacology & Safety Sciences, R&D, AstraZeneca, Cambridge, UK. victoria.auyeung.publications@gmail.com.
Cell biology and toxicology
|June 28, 2024
概括
结构性心脏毒性 (SCT) 是一种主要的药物发现风险. 这项研究确定了关键的预测参数和基因表达指纹,以改善机理学理解并减轻早期药物开发中的SCT风险.
科学领域:
- 药物发现 药物发现 药物发现
- 心脏病学 心脏病学
- 毒理学 毒理学 毒理学
背景情况:
- 结构性心脏毒性 (SCT) 在药物发现中构成了重大挑战.
- 更深入地了解SCT的机制对于早期风险减轻至关重要.
研究的目的:
- 增强对结构性心脏毒性的机制性理解.
- 识别与SCT相关的预测参数和分子特征.
主要方法:
- 机器学习应用于人类诱导的多能干细胞衍生的心肌细胞中的过时测定.
- 对暴露于心脏毒素的人类心脏微组织的转录组分析.
- 不同基因表达和网络聚类分析.
主要成果:
- 确定了9个参数可以预测SCT.
- 一个52基因的转录指纹与心肌细胞,内皮细胞和纤维细胞中已知的SCT机制有关.
- 这个指纹可以与已建立的SCT路径联系起来.
结论:
- 鉴定的参数和转录指纹为SCT提供了更好的机械洞察力.
- 这些知识可以指导在早期药物发现阶段减轻SCT风险的策略.
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