在过去五年中,关于药物向相互作用的研究进展
1School of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi, 214000, China.
Analytical biochemistry
|October 25, 2024
概括
计算方法提供了一种经济有效的方法来识别药物向相互作用 (DTI),这对于药物发现和重新定位至关重要. 本综述综合了DTI预测的当前方法和未来方向.
科学领域:
- 计算化学是一种计算化学.
- 生物信息学是一种生物信息学.
- 药物发现 药物发现
背景情况:
- 药物向相互作用 (DTI) 的识别对于药物发现和重新定位至关重要.
- 对DTI的实验验证是昂贵和耗时的.
- 计算方法提供了一个经济和高效的替代方案.
研究的目的:
- 审查和综合现有的化学基因组方法用于DTI预测.
- 提供流行DTI预测数据库和特征编码的全面摘要.
- 讨论DTI预测方法的最新进展和未来方向.
主要方法:
- 关于化学基因组方法的文献综述.
- 用于DTI预测的特征编码的分类.
- 概述和比较流行的DTI预测方法 (2020-2024),包括网络表示学习和图形神经网络.
主要成果:
- 综合当前的DTI预测数据库和特征编码策略.
- 详细讨论最近的DTI预测方法的优缺点.
- 在各种数据集中评估方法性能.
结论:
- 计算DTI预测是一个快速发展的领域,具有巨大的潜力.
- 像图形神经网络这样的新兴方法显示出提高准确性和效率的前景.
- 未来的研究应该专注于整合大数据和先进的计算技术,以提高DTI预测.
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