Related Experiment Video
Updated: May 20, 2026

Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors
Published on: May 9, 2025
Quantitative structure-activity relationship prediction of blood-to-brain partitioning behavior using support vector
Hassan Golmohammadi1, Zahra Dashtbozorgi, William E Acree
1Department of Chemistry, Shahr-e-Rey Branch, Islamic Azad University, Tehran, Iran.
Abstract:
In the present study a quantitative structure-activity relationship (QSAR) technique was developed to investigate the blood-to-brain barrier partitioning behavior (log BB) for various drugs and organic compounds. Important descriptors were selected by genetic algorithm-partial least square (GA-PLS) methods. Partial least squares (PLS) and support vector machine (SVM) methods were employed to construct linear and non-linear models, respectively. The results showed that, the log BB values calculated by SVM were in good agreement with the experimental data, and the performance of the SVM model was superior to the PLS model. The study provided a novel and effective method for predicting blood-to-brain barrier penetration of drugs, and disclosed that SVM can be used as a powerful chemometrics tool for QSAR studies.
Related Concept Videos
Structure-Activity Relationships and Drug Design
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 its...
Model-Independent Approaches for Pharmacokinetic Data: Noncompartmental Analysis
One important characteristic of noncompartmental analyses is that drug exposure increases proportionally with increasing doses. This relationship...
Quantitative Aspects of Drug-Receptor Interaction
Physiological Pharmacokinetic Models: Assumption with Protein Binding
Mechanistic Models: Compartment Models in Individual and Population Analysis
Measurement of Bioavailability: Pharmacodynamic Methods
