TropMol:一个基于云的网络工具,用于虚拟查和早期预测使用机器学习的乙胆酶抑制剂
1Department of Exact Sciences and Education (CEE), School of Technology, Exact Sciences and Education (CTE), Federal University of Santa Catarina (UFSC), Blumenau 89036-256, SC, Brazil. thiago.doring@ufsc.br.
Organic & biomolecular chemistry
|February 13, 2026
概括
这项研究开发了一种预测模型,用于识别用于阿尔茨海默病 (AD) 治疗的乙胆化酶 (AChE) 抑制剂. 随机森林模型准确地预测化合物的疗效,帮助药物发现工作.
科学领域:
- 药用化学 医学化学
- 计算化学计算化学
- 药理学 药理学是指药理学的学科.
背景情况:
- 阿尔茨海默病 (AD) 是导致痴呆的主要原因,而乙胆酶 (AChE) 抑制是关键的治疗策略.
- 开发ACHE抑制剂的预测模型对于有效的药物设计和虚拟查至关重要.
研究的目的:
- 开发一种使用随机森林 (RF) 方法的ACHE抑制剂的通用,公开可访问和免费的分子查预测模型.
- 确定与ACHE抑制活性相关的关键分子描述物 (pIC50).
主要方法:
- 利用了大约16000个化合物的大型数据集,并计算了超过2000万个描述符.
- 采用随机森林 (RF) 模型,将其性能与其他算法比较,如梯度增强,XGBoost和LightGBM.
- 使用内部测试组和独立的外部测试组严格验证模型.
主要成果:
- 射频模型实现了高预测精度,R2值为0.76 (15%的测试组) 和0.77 (外部验证组).
- Y-scrambling证实没有偶然的相关性,外部验证证明了对新型化学支架的稳定性.
- 确定了oxime组和高结构分支的负相关性,以及具有ACHE抑制的线性链的正相关性.
结论:
- 开发的RF模型是用于阿尔茨海默病的ACHE抑制剂的虚拟查和药物设计的可靠工具.
- 与电子电荷分布,表面积,疏水性以及分支和链等结构特征相关的分子描述因素是AChE抑制活性的重要预测因素.
- 该模型和相关数据是公开可用的,促进了AD治疗的进一步研究和开发.
相关概念视频
Virtual Work
1.4K
The principle of virtual work states that if a body is in static and dynamic equilibrium, then the sum of all the virtual work done by all external forces and couple moments for any given virtual displacement must be zero.
In static equilibrium, a body can experience an imaginary or virtual movement, such as displacement or rotation. The virtual work done by a force is equal to the dot product of force and virtual displacement in the direction of the force. When it comes to virtually rotating a...
In static equilibrium, a body can experience an imaginary or virtual movement, such as displacement or rotation. The virtual work done by a force is equal to the dot product of force and virtual displacement in the direction of the force. When it comes to virtually rotating a...
1.4K
Eukaryotic Transcription Inhibitors
11.1K
Certain biochemical processes, such as embryonic development and cell growth regulation, depend on the repression of specific genes. DNA binding proteins known as eukaryotic transcription inhibitors regulate the repression of gene expression in eukaryotes. The presence of these inhibitors at the required location and time in the cell is triggered by the presence of hormones and additional signals from other cells.
Eukaryotic transcription inhibitors usually contain two distinct domains, a...
Eukaryotic transcription inhibitors usually contain two distinct domains, a...
11.1K
Predicting Molecular Geometry
46.1K
VSEPR Theory for Determination of Electron Pair Geometries
46.1K
Machines
581
Machines are complex structures consisting of movable, pin-connected multi-force members that work together to transmit forces. One example of a machine is the cutting plier, which is used to cut wires by applying forces to its handles. When equal and opposite forces are exerted on the handles of the cutting plier, they cause the cutting edges to come together and apply equal and opposite reaction forces on the wire, which are greater than the applied forces.
A free-body diagram of the...
A free-body diagram of the...
581
Machines: Problem Solving II
678
Machines are complex structures consisting of movable, pin-connected multi-force members that work together to transmit forces. Consider a lifting tong carrying a 100 kg load. It comprises movable sections DAF and CBG linked together with member AB.
678
Prediction Intervals
3.4K
The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.
3.4K


