DTGHAT:基于多分子图的多分子异质图形变压器,用于药物标识
Xinchen Jiang1,2, Lu Wen2,3, Wenshui Li1,2
1The National Local Joint Engineering Laboratory of Animal Peptide Drug Development, College of Life Sciences, Hunan Normal University, Changsha, China.
Frontiers in pharmacology
|May 13, 2025
概括
这项研究引入了DTGHAT,一种用于药物标识的新型模型. 通过分析复杂的药物-基因-疾病网络,DTGHAT显著提高了预测准确度,推动了药物发现.
科学领域:
- 计算生物学是一种计算生物学.
- 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:
- 药物标的识别对于开发新疗法至关重要.
- 当前的计算方法往往忽略了药物,目标和其他生物分子之间的复杂关系.
- 需要一个全面的方法来建模这些复杂的生物系统.
研究的目的:
- 提出一种新的预测模型,DTGHAT (使用异质图表注意力变压器进行药物和目标关联预测),用于识别药物目标.
- 通过结合异质生物网络数据来解决现有方法的局限性.
- 提高药物目标预测的准确性和范围.
主要方法:
- DTGHAT采用了一个图形注意力转换器架构.
- 该模型分析了15个异构的药物-基因-疾病网络,整合了化学,基因组,表型和细胞数据.
- 使用5倍交叉验证来评估模型的性能.
主要成果:
- DTGHAT实现了0.9634的接收器运行特征曲线 (AUC) 下的面积,超过了最先进的方法至少4%.
- 废弃实验证实了整合多来源生物分子数据的重要性.
- 一个关于癌症药物的案例研究表明,DTGHAT在预测新药标方面的有效性.
结论:
- DTGHAT代表了计算药物标识的重大进展.
- 该模型能够整合多样化的生物数据,从而提高了药物向相互作用的预测能力.
- DTGHAT为加速药物发现和开发提供了一个有价值的,免费可用的工具.
更多相关视频
07:40A Data Integration Workflow to Identify Drug Combinations Targeting Synthetic Lethal Interactions
Published on: May 27, 2021
3.4K
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
相关概念视频
Protein Networks
3.7K
An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
3.7K
Drug Discovery: Overview
10.3K
Drug discovery is a multifaceted process involving extensive screening, testing, and optimization of lead compounds to identify potential new drugs for therapeutic use. It combines several approaches, including screening large numbers of natural products, chemical modification of known active molecules, identification of new drug targets, and rational design based on biological mechanisms and drug-receptor structure. These approaches are carried out in both academic research laboratories and...
10.3K
Drug Biotransformation: Overview
3.7K
Pharmaceutical substances known as xenobiotics are predominantly lipophilic and nonionized. This enables them to permeate lipid bilayers, such as cell membranes, and interact with intracellular target receptors. Lipophilic drugs have an advantage in crossing biological barriers and reaching their intended sites of action. However, lipophilic drugs often have a restricted capacity for renal expulsion or elimination from the body. When these drugs enter the kidneys and undergo glomerular...
3.7K
Targets for Drug Action: Overview
9.2K
Drugs target macromolecules to modify ongoing cellular processes. Primary drug targets include receptors, ion channels, transporters, and enzymes.
Receptors are either membrane-spanning or intracellular proteins, which upon binding a ligand, get activated and transmit the signal downstream to elicit a response. Drugs bind receptors, either mimicking the action of endogenous ligands or blocking the receptor activity to bring about a modified response. Nearly 35% of approved drugs target the G...
Receptors are either membrane-spanning or intracellular proteins, which upon binding a ligand, get activated and transmit the signal downstream to elicit a response. Drugs bind receptors, either mimicking the action of endogenous ligands or blocking the receptor activity to bring about a modified response. Nearly 35% of approved drugs target the G...
9.2K
Pharmacogenomics: Identification of New Drug Targets
119
Advances in genomics have profoundly influenced drug discovery by increasing both the speed and accuracy of pharmaceutical development. Pharmacogenomics, which examines how genetic variation influences drug response, facilitates the identification of novel therapeutic targets and enables patient stratification for personalized treatment. These strategies contribute to improved drug efficacy, minimized adverse effects, and more efficient clinical trial design.Mapping genetic differences...
119
