相关实验视频

Updated: May 13, 2025

Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors

Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors

Published on: May 9, 2025

抗逆转录病毒化合物的IFPTML多输出模型,包括药物结构和向蛋白序列信息

Emilia Vásquez-Domínguez^1,2, Shan He^1,3, Carlos Santolaria¹

¹Department of Organic and Inorganic Chemistry, University of the Basque Country UPV/EHU, 48940 Leioa, Spain.

Journal of chemical information and modeling

|April 28, 2025

概括

这项研究引入了一种先进的AI模型,该模型集成了病毒蛋白序列,以改善抗逆转录病毒药物发现. 改进的模型准确地预测了对新出现的病毒突变和菌株的药物活性.

科学领域:

药物发现药物发现药物发现
计算生物学计算生物学
病毒学病毒学

背景情况:

逆转录病毒感染需要不断开发抗逆转录病毒药物 (ARV).
现有的药物发现模型难以解释病毒突变和各种生物条件.
ChEMBL数据库提供了广泛的ARV数据,但需要复杂的分析才能有效地发现药物.

研究的目的:

为加速ARV发现开发一个增强的人工智能/机器学习 (AI/ML) 模型.
将病毒蛋白序列信息集成到ARV活动的预测模型中.
解决当前模型在预测抗病毒变体和突变的药物疗效方面的局限性.

主要方法:

开发了一个增强的信息融合扰乱理论和机器学习 (IFPTML) 模型.
将从逆转录病毒蛋白质组计算的内置序列描述符纳入IFPTML模型.
在一个全面的ChEMBL ARV数据集上训练并验证了模型.

主要成果:

在培训和验证过程中,增强的IFPTML模型实现了高性能指标 (灵敏度:72.0-88.0%,特异性:72.0-88.0%,精度:72.0-88.0%).
该模型在预测针对已知的蛋白质突变的药物活性方面表现出有效性.
成功整合了各种数据,包括病毒序列,菌株,细胞系和试验生物.

结论:

增强的IFPTML模型通过系统地整合蛋白质序列数据,在ARV发现方面取得了重大进展.
这种统一的多条件多输出模型可以更好地预测抗病毒药物活性,以应对各种病毒挑战.
这种方法有助于发现有效对抗耐药突变和新兴病毒菌株的药物.

更多相关视频

Multi-target Parallel Processing Approach for Gene-to-structure Determination of the Influenza Polymerase PB2 Subunit

Multi-target Parallel Processing Approach for Gene-to-structure Determination of the Influenza Polymerase PB2 Subunit

Published on: June 28, 2013

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions

Published on: January 26, 2024

相关概念视频

Protein-protein Interfaces

Protein-protein Interfaces

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...

Physiological Pharmacokinetic Models: Incorporating Hepatic Transporter-Mediated Clearance

Physiological Pharmacokinetic Models: Incorporating Hepatic Transporter-Mediated Clearance

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,...

Protein Organization

Protein Organization

Proteins are polymers of amino acid residues. They are versatile and responsible for different cellular functions, including DNA replication, molecular transport, catalysis, and structural support. Proteins have a hierarchical structure comprising at least three levels of organization: primary, secondary, and tertiary structure. Some large proteins have a quaternary structure where individual protein subunits are linked together.
The primary structure of a protein is its amino acid sequence....