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Updated: Feb 2, 2026

Quantitative Structure-Activity Relationship, Activity Prediction, and Molecular Dynamics of Non-nucleotide Reverse Transcriptase Inhibitors
Published on: May 9, 2025
Complementary Quantitative Structure⁻Activity Relationship Models for the Antitrypanosomal Activity of Sesquiterpene
Njogu M Kimani1, Josphat C Matasyoh2, Marcel Kaiser3,4
1Institute of Pharmaceutical Biology and Phytochemistry (IPBP), University of Muenster, PharmaCampus Corrensstrasse 48, D-48149 Muenster, Germany. m_kima01@uni-muenster.de.
Quantitative structure-activity relationship (QSAR) models were developed for sesquiterpene lactones (STLs) against Trypanosoma brucei rhodesiense. These models predict antitrypanosomal activity based on molecular structure, aiding drug discovery.
Area of Science:
- Medicinal Chemistry
- Computational Chemistry
- Parasitology
Background:
- Human African trypanosomiasis remains a significant health concern, necessitating novel therapeutic agents.
- Sesquiterpene lactones (STLs) are natural products with demonstrated antitrypanosomal activity.
- Previous quantitative structure-activity relationship (QSAR) studies have explored STL activity, but larger, more diverse datasets are needed.
Purpose of the Study:
- To develop robust QSAR models for predicting the antitrypanosomal activity of a large and diverse set of STLs against Trypanosoma brucei rhodesiense (Tbr).
- To identify key molecular descriptors and structural features that govern the antitrypanosomal efficacy of STLs.
- To enhance the understanding of structure-activity relationships for the development of new anti-trypanosomal drugs.
Main Methods:
- Employed three complementary QSAR methodologies: regression modeling using classical molecular descriptors, 3D pharmacophore features, and 2D molecular holograms (HQSAR).
- Developed models for an extended dataset of 130 STLs, including newly isolated compounds and literature data tested under identical conditions.
- Validated the QSAR models using internal (leave-one-out) and external prediction metrics.
Main Results:
- Achieved good predictive ability for all developed QSAR models, with coefficients of determination (R²) ranging from 0.71 to 0.85.
- Demonstrated strong internal validation (Q² values from 0.62 to 0.72) and external validation (P² values from 0.54 to 0.73) across the diverse STL dataset.
- Confirmed that antitrypanosomal activity is significantly influenced by the presence and position of reactive enone groups, as well as hydrophilic/hydrophobic properties and molecular shape.
Conclusions:
- The developed QSAR models provide reliable tools for predicting the antitrypanosomal activity of STLs.
- The findings reinforce the importance of specific structural features, particularly reactive enone groups, for Tbr activity.
- This study contributes to the rational design of novel STL-based compounds for treating human African trypanosomiasis.
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