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4D-QSAR Analyses for EGFR Inhibitors Based on CDDA-OPS-GA Method
Author(s):
1. Biying Cai: School of Pharmaceutical Science, Nanchang University,330006,China
2. Tiansheng Zhao: School of Pharmaceutical Science, Nanchang University,330006,China
3. Daogang Qin: School of Pharmaceutical Science, Nanchang University,330006,China
4. Guogang Tu: School of Pharmaceutical Science, Nanchang University,330006,China
Abstract:
Summary: Epidermal growth factor receptor (EGFR) is a preferred target for treating cancer. Compared to 3D-QSAR, 4D-QSAR has the feature of conformational flexibility and free alignment for individual ligands. In present studies, the 4D-QSAR of 131 analogs of 4-anilino quinazoline for EGFR inhibitors was built. The GROMACS package was employed to yield the conformational ensemble profile. The field descriptors of Coulomb and Lennard-Jones potentials were calculated by LQTA-QSAR (Laboratory of Theoretical and Applied Chemometrics, QSAR). The filter descriptors and variable selection is very important, which was performed by means of comparative distribution detection algorithm (CDDA), ordered predictors selection (OPS) and genetic algorithm (GA) method. Best 4D-QSAR model yielded satisfactory statistics (R2 = 0.71), good performance in internal (Q2LOO = 0.60) and external prediction (Rp2red = 0.69, k = 0.97, k' = 1.01). The 4D-QSAR was shown to be robust (Q2LMO = 0.59) and was not built by chance (R2YS = 0.17, Q2YS = -0.25). The model has a good potential for rational design new EGFR inhibitors.
Page(s): 204-212
DOI: DOI not available
Published: Journal: Journal of Chemical Society of Pakistan, Volume: 47, Issue: 3, Year: 2025
Keywords:
Genetic Algorithm GA , ordered predictors selection OPS , comparative distribution detection algorithm CDDA , 4DQSAR , EGFR Inhibitors
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