Theoretically Predicted Descriptors Based Quantitative Structure Activity Relationship Study of the Activity of Acridines Against B-16 Melanoma
Bahjat A. Saeed1, Rita S. Elias2, Sadiq M-H. Ismael1 & Kawkab A. Hussain1 Show affiliations
- Department of Chemistry, College of Education, Iraq
- Department of Pharmaceutical Chemistry, College of Pharmacy, University of Basrah, Iraq
American Journal of Applied Sciences, Volume 8, Issue 8, pp. 773–776 · doi.org/10.3844/ajassp.2011.773.776
Abstract
Problem statement: The probability of success and reducing time and coast in drug discovery process could be increased on the basis of QSAR techniques. The study involves the QSAR investigation of 20 bioactive acridines that have activity against Approach: Molecular descriptors, total energy, van der Waals volume, molecular volume, HOMO energy, HOMO-LUMO energy gap, polarizability, refractivity, bond angle of C8-N9-C2 and bond length of C14-N6 were calculated. Initial geometry optimizations were carried out with RM1 Hamiltonian. Lowest energy conformers were subjected to single point calculations by DFT method. Several models for the prediction of biological activity have been drawn up by using the multiple regression technique. Results: Four models with R2 ranges from 0.88-0.93 were predicted. A model with hepta-parametric equation with R2 0.93 was used to predict the biological activities, the agreement between the observed and the predicted values was up to 93%. Conclusion: The biological activity of the studied acridines can be modeled with quantum chemical molecular descriptors.
Licence and reuse
Free to read. This article carries the publisher’s copyright, as printed on it: © 2011 Science Publications. It is free to read; ask us before reusing it.
How to reuse this articleResponses (0)
About this article
Saeed, B. A., Elias, R. S., Ismael, S. M. & Hussain, K. A. (2011). Theoretically Predicted Descriptors Based Quantitative Structure Activity Relationship Study of the Activity of Acridines Against B-16 Melanoma. American Journal of Applied Sciences, 8(8), 773–776. https://doi.org/10.3844/ajassp.2011.773.776
- Licence
- © Science Publications
- Issue
- Volume 8, Issue 8
- Policies
- Editorial independenceUse of generative AIData availabilityAppeals and complaints
- Version
- Version of record
