基于序和分子图的双模融合,具有双向交叉注意力,用于精确的毒性预测
Pan Li1, Shaopeng Zhang1, Ran Liu2
1School of Electronic and Information Engineering, University of Science and Technology Liaoning, Anshan 114051, China.
Journal of chemical information and modeling
|March 2, 2026
概括
一个新的双模框架,PTP-SMGCA,通过整合序列和分子图数据,准确地预测类药物毒性. 这种方法可以通过快速选潜在的有毒来促进药物开发.
科学领域:
- 药理学和化学信息学
- 计算生物学 计算生物学
- 药物发现 药物发现 药物发现
背景情况:
- 类药物具有高特异性和生物相容性,但面临毒性挑战.
- 准确的毒性评估对于将引入临床应用至关重要.
- 现有的毒性预测工具需要提高精度和可扩展性.
研究的目的:
- 开发一个高精度,可扩展的框架,用于毒性预测.
- 在类药物开发中解决毒性风险的瓶.
- 为了提高区分有毒的准确性.
主要方法:
- 提出了一个双模特功能融合框架,PTP-SMGCA.
- 通过序列路径捕获了局部动机和远程依赖关系.
- 通过分子图路径来表征原子拓和结合语义.
- 利用双向交叉注意力来动态对齐序列和图形特征,抑制噪音.
主要成果:
- 在毒性预测方面,PTP-SMGCA取得了高性能,AUROC为0.9289,AUPRC为0.9397.
- 超过了几种先进的类毒性预测工具.
- 解释性分析确定了关键的氨基酸和功能组,突出了对齐特征的作用.
结论:
- PTP-SMGCA提供了一种准确有效的方法来预测毒性.
- 该框架有助于快速选有毒,有助于治疗性药物开发.
- 双模特征融合和交叉注意力机制是模型预测能力的关键.
更多相关视频
08:31Biosensor-based High Throughput Biopanning and Bioinformatics Analysis Strategy for the Global Validation of Drug-protein Interactions
Published on: December 1, 2020
4.8K
06:50Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions
Published on: January 26, 2024
2.8K
相关概念视频
Tagging and Fusion Proteins
6.4K
Proteins are involved in several cellular processes and biochemical reactions. Analyzing a specific protein of interest requires it to be isolated from the other proteins in the cell. This is achieved by overexpressing the specific gene in a suitable host to produce large quantities of the target protein. A tag or label is recombined with the gene to produce a fusion protein containing the target protein and the tag. The tags on these fusion proteins can then be used for easy detection and...
6.4K
Peptide Identification Using Tandem Mass Spectrometry
6.2K
Tandem mass spectrometry, also known as MS/MS or MS2, is an analytical technique that employs two mass analyzers. Essentially it is a series of mass spectrometers that helps isolate a particular biomolecule and then helps study its chemical properties.
This technique helps gather information regarding the protein from which the peptide was obtained and to study the peptides’ amino acid sequence. Identifying peptides from a complex mixture is an important component of the growing field of...
This technique helps gather information regarding the protein from which the peptide was obtained and to study the peptides’ amino acid sequence. Identifying peptides from a complex mixture is an important component of the growing field of...
6.2K
