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Updated: Jul 17, 2026
Biosensor-based High Throughput Biopanning and Bioinformatics Analysis Strategy for the Global Validation of Drug-protein Interactions
Published on: December 1, 2020
3D-QSAR study of 20 (S)-camptothecin analogs
Ai-jun Lu1, Zhen-shan Zhang, Ming-yue Zheng
1Jiangsu Simcere Pharmaceutical Research Company Ltd, Nanjing 210042, China.
Aim:
To build up a quantitative structure-activity relationship (QSAR) model of 20 (S)-camptothecin (CPT) analogs for the prediction of the activity of new CPT analogs for drug design.
Methods:
A training set of 43 structurally diverse CPT analogs which were inhibitors of topoisomerase I were used to construct a quantitative structure-activity relationship model with a comparative molecular field analysis (CoMFA). The QSAR model was optimized using partial least squares (PLS) analysis. A test set of 10 compounds was evaluated using the model.
Results:
The CoMFA model was constructed successfully, and a good cross-validated correlation was obtained in which q(2) was 0.495. Then, the analysis of the non-cross-validated PLS model in which r(2) was 0.935 was built and permitted demonstrations of high predictability for the activities of the 10 CPT analogs in the test set selected in random.
Conclusion:
The CoMFA model indicated that bulky negative-charged group at position 9, 10 and 11 of CPT would increase activity, but excessively increasing bulky group at position 10 is adverse to inhibitory activity; substituents that occupy position 7 with the bulky positive group will enhance the inhibitive activity. The model can be used to design new CPT analogs and understand the mechanism of action.
