ABT-DDI:一个带有原子键结构意识的图形变压器模型,用于药物相互作用预测
Xu Guo1, Jianbo Qiao1, Siqi Chen1
1School of Software, Shandong University, Jinan 250100, China.
ACS synthetic biology
|December 23, 2025
概括
由于多药学,预测药物相互作用 (DDI) 是至关重要的. 我们的新型ABT-DDI模型有效地使用分子结构和3D信息来提高DDI预测的准确性.
科学领域:
- 计算化学是一种计算化学.
- 药理学 药理学是指药理学的学科.
- 生物信息学是一种生物信息学.
背景情况:
- 多药制品增加了药物相互作用 (DDI) 的风险.
- 目前的DDI预测方法往往忽略了分子3D结构和原子结合关系.
研究的目的:
- 开发一个先进的DDI预测模型,ABT-DDI.
- 通过结合多模式分子信息,提高药物相互作用事件 (DDIEs) 预测的准确性.
主要方法:
- 使用图形变压器架构进行DDI预测.
- 使用多尺度注意力机制建模空间关系 (原子-原子,原子-键,键-键).
- 集成的分子指纹与3D空间描述器,用于全面的分子表示.
主要成果:
- 在基准数据集上,ABT-DDI在现有最先进的方法中表现优越.
- 该模型有效地捕获了原子和结合相互作用模式.
- 在多个绩效指标上取得了显著的改进.
结论:
- 通过利用详细的分子结构和空间信息,ABT-DDI提供了一种可靠的方法来预测DDI.
- 该模型在药物开发和多药房风险管理方面具有重要的潜在应用.
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