CUPID:一个免费的药物发现平台,用于对心脏毒性进行可解释的多离子通道评估
Nicola Gambacorta1, Fabrizio Mastrolorito2, Maria Vittoria Togo2
1Division of Medical Genetics, IRCCS Foundation-Casa Sollievo della Sofferenza, San Giovanni Rotondo, Foggia, Italy; Department of Pharmacy-Pharmaceutical Sciences, University of Bari "Aldo Moro", Bari, Italy.
European journal of medicinal chemistry
|April 4, 2025
概括
由于心脏毒性等安全问题,药物发现面临很高的磨损. 可解释的人工智能平台CUPID预测候选药物的心脏毒性风险,帮助设计更安全的药物.
科学领域:
- 药物发现和开发 药物发现和开发
- 计算毒理学计算毒理学
- 人工智能在医学中的应用
背景情况:
- 由于安全问题,特别是心脏毒性,药物戒断显著影响药物发现成功率.
- 心脏毒性是药物开发中的一个关键的毒理问题,特别是在瘤学药物中,导致严重的心脏疾病.
- 现有的方法在开发管道的早期难以准确预测心脏毒性.
研究的目的:
- 引入CUPID (智能药物发现心脏毒素理解平台),这是一个可解释的AI框架,用于预测药物诱导的心脏毒性.
- 评估与关键离子通道相关的心脏毒性风险:ERG,Na1.5和Ca1.2通道.
- 通过提供可解释的心脏毒性预测,提高更安全的候选药物的合理设计.
主要方法:
- 开发了一个可解释的人工智能 (XAI) 框架,名为CUPID.
- 训练模型使用来自ChEMBL (34版本) 和核心替代指纹 (CSFP) 的精选跨物种实验数据集.
- 使用SHAP值来突出与心脏毒性风险相关的化学亚结构,并提供适用性领域信息.
主要成果:
- 在5倍分层交叉验证分析中达到约80%的准确性.
- 开发了高度准确和可解释的机器学习模型,用于心脏毒性预测.
- CUPID提供了全面的早期心脏毒性风险评估,具有明确的解释性.
结论:
- 在药物发现过程中,CUPID为早期心脏毒性风险评估提供了一个强大的工具.
- 该框架的可解释性,通过SHAP值和适用性领域信息,有助于设计更安全的生物活性化合物.
- CUPID是免费访问的,促进其采用,加速开发更安全的治疗方法.
关键词:
Ca ((v) 1.21.2 其他心脏有毒性 - 心脏有毒性药物发现 药物发现在 ERG ERG 里面,有很多东西可以做.可解释的人工智能一个免费的基于Web的平台.高质量的实验数据.Na{}v) 1.5 1.5 的时间.更多相关视频
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