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TISBE:一个公共网络平台,用于基于共识的可解释的发展毒性预测

Fabrizio Mastrolorito¹, Maria Vittoria Togo¹, Nicola Gambacorta¹

¹Dipartimento di Farmacia-Scienze del Farmaco, Università degli Studi di Bari Aldo Moro, 70125 Bari, Italy.

Chemical research in toxicology

|January 10, 2024

概括

一个新的平台,TISBE,通过使用可解释的AI和更大的数据集,增强了发育性毒性 (Dev Tox) 预测. 它可以识别有毒的分子碎片,以更高的精度帮助产前和新生儿健康保护.

科学领域:

计算毒理学计算毒理学
化学信息学化学信息学
预测性毒理学预测性毒理学

背景情况:

发育性毒性 (Dev Tox) 对产前和新生儿健康至关重要,但在分子层面上尚不清楚.
有限的高质量数据和缺乏强大的非测试方法阻碍了Dev Tox研究.
在监管毒理学中,Dev Tox是动物试验的一个重要领域,需要使用替代方法.

研究的目的:

推出TISBE (TIRESIA 基于结构的可解释性改进),这是一个用于 in silico 发育毒性分析的新型网络平台.
为了解化学毒性提供一个可解释的人工智能 (XAI) 框架.
提供可靠的工具来预测发育性毒性和识别负责任的分子碎片.

主要方法:

开发TISBE,包括一个更大的数据集 (1008种化学品),一个基于片段的XAI框架,一个共识分类器 (5ML模型) 和一种新的适用性域 (AD) 方法.
使用五重交叉验证方法进行培训和验证.
将TISBE应用于生物活性化合物 (ChEMBL) 和儿科药物 (TEDDY) 的外部数据集.

主要成果:

TISBE的中位数达到了0.410.10的马修斯相关系数.
在交叉验证过程中观察到高中位灵敏度 (0.984) 和特异性 (0.274).
该平台成功识别了与测试化合物中毒性或安全性相关的分子碎片.

结论:

TISBE 代表了 in silico 发育性毒性评估的重大进步,提供了可解释性和更高可靠性.
该平台能够精确识别有毒分子碎片的能力有助于理解化学风险.
TISBE是免费提供的,支持监管毒理学和药物开发,以提高儿童安全.

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