通过整合药理和预训练模型,提高药物向相互作用识别的概括性和性能
Zuolong Zhang1, Xin He1,2, Dazhi Long3
1School of Software, Henan University, Kaifeng, Henan Province 475000, China.
Bioinformatics (Oxford, England)
|June 28, 2024
概括
HeteroDTA通过整合化合物药理和蛋白质结构来增强药物标结合亲和力 (DTA) 的预测. 这种新的深度学习方法提高了药物发现的准确性和概括性.
科学领域:
- 计算化学和化学信息学
- 生物信息学和计算生物学
- 人工智能在药物发现中的作用
背景情况:
- 准确的药物标结合亲和力 (DTA) 预测对于有效的药物发现至关重要.
- 传统的分子对接对于大规模的虚拟选是计算密集的.
- 目前用于DTA预测的深度学习方法在特征表示和概括方面存在局限性.
研究的目的:
- 开发一种新的深度学习方法,HeteroDTA,用于准确高效的DTA预测.
- 通过结合多视图化合物特征和蛋白质信息来解决现有方法的局限性.
- 增强概括能力,减少对大型标记数据集的依赖.
主要方法:
- 开发了一个多视图化合物特征提取模块,模拟原子键和药图.
- 使用了残留合图和蛋白质序列,用于全面的蛋白质建模.
- 采用预先训练的模型来初始化原子和序列嵌入,以及一个上下文感知的非线性特征融合方法.
主要成果:
- 在公开基准数据集上,HeteroDTA显著超过了现有的方法.
- 在冷启动实验中表现出极好的概括性能.
- 对于药物标对来说,展示了卓越的代表性学习能力,并在现实世界药物发现研究中得到验证.
结论:
- 在药物发现中,HeteroDTA为DTA预测提供了一种强大而有效的方法.
- 该方法能够整合多种特征并利用预先训练的模型,从而提高预测准确性和概括性.
- 在加快虚拟查和识别新药候选药物方面,HeteroDTA显示出前景.
相关概念视频
Protein-protein Interfaces
12.5K
Many proteins form complexes to carry out their functions, making protein-protein interactions (PPIs) essential for an organism's survival. Most PPIs are stabilized by numerous weak noncovalent chemical forces. The physical shape of the interfaces determines the way two proteins interact. Many globular proteins have closely-matching shapes on their surfaces, which form a large number of weak bonds. Additionally, many PPIs occur between two helices or between a surface cleft and a...
12.5K
Drug Discovery: Overview
7.8K
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...
7.8K
Pharmacokinetic Models: Overview
647
Pharmacokinetic models utilize mathematical analysis to achieve a detailed quantitative understanding of a drug's life cycle within the body. They are instrumental in simulating a drug's pharmacokinetic parameters, predicting drug concentrations over time, optimizing dosage regimens, linking concentrations with pharmacologic activity, and estimating potential toxicity.
There are three primary types of models: empirical, compartment, and physiological. Empirical models, with minimal...
There are three primary types of models: empirical, compartment, and physiological. Empirical models, with minimal...
647
Physiological Pharmacokinetic Models: Incorporating Hepatic Transporter-Mediated Clearance
38
Drug transporters are critical in drug absorption, distribution, and excretion processes. They should be included in physiological-based pharmacokinetic (PBPK) models, which help predict human drug disposition. However, predicting this is challenging during drug development, especially when liver transport is involved. However, with a realistic representation of body transport processes, an accurate model may be possible.
A recent model describes pravastatin's hepatobiliary excretion,...
A recent model describes pravastatin's hepatobiliary excretion,...
38
Drug-Receptor Interactions
5.1K
Drug-receptor interaction describes the binding of receptors by drugs, but not all drug-receptor interactions result in activation and tissue response. For instance, the binding of agonists activates the receptor to generate a cellular reaction, while antagonists bind to receptors without causing their activation.
Several parameters, such as the drug's affinity for its receptor and its efficacy, which is its ability to activate the receptor, determine the drug's effect on the tissue....
Several parameters, such as the drug's affinity for its receptor and its efficacy, which is its ability to activate the receptor, determine the drug's effect on the tissue....
5.1K
Structure-Activity Relationships and Drug Design
697
Drug design is a dynamic field that involves discovering and developing new medications based on specific biological targets. This process heavily relies on structure-activity relationships (SAR) and quantitative structure-activity relationships (QSAR) to guide the design and optimization of efficient drugs.
SAR studies the intricate relationship between a drug's chemical structure and biological activity. It focuses on understanding how modifications to a drug's structure can influence...
SAR studies the intricate relationship between a drug's chemical structure and biological activity. It focuses on understanding how modifications to a drug's structure can influence...
697


