Quantitative structure-activity relationship study of natural and semi-synthetic anti-leukemic compounds
Leukemia is one of the most common cancers worldwide. Current treatments could be unsatisfactory because of side effects, drug resistance, or some types of cancer that remain incurable. Natural products are a promising approach to overcome these limitations. Particularly, species from the Asteraceae...
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| Natura: | bachelorThesis |
| Lingua: | eng |
| Pubblicazione: |
2022
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| Soggetti: | |
| Accesso online: | http://repositorio.yachaytech.edu.ec/handle/123456789/485 |
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Aggiungi Tag | Riassunto: | Leukemia is one of the most common cancers worldwide. Current treatments could be unsatisfactory because of side effects, drug resistance, or some types of cancer that remain incurable. Natural products are a promising approach to overcome these limitations. Particularly, species from the Asteraceae family have a high content of terpenoids, called sesquiterpene lactones (SLs). These compounds are highly interested in natural product chemistry because they exhibit potential anti-cancer effects. However, their isolation and biological activity evaluation could be expensive and time-consuming. In addition, to make more potent and selective compounds, it is necessary to conduct chemical modifications of these structures. Fortunately, combining quantum methods, high-performance computing, and experimental studies can accelerate the discovery of new compounds with better pharmacological profiles. This project presents a Quantitative Structure-Activity Relationship (QSAR) model of a set of SLs with anti-leukemic activity. The analysis showed that the α-methylene-γ-lactone group plays an essential role in the anti-leukemic activity of the SLs. The model is based on the electronic properties (molecular descriptors) of the SLs computed with the ab initio DFT method. The descriptors that best fit the model were highest occupied molecular orbital and total energy. The statistical parameters showed goodness-of-fit (R2=0.66), robustness (Q2cv=0.60), and predictability (Q2Ext=0.61). Therefore, the model has great internal and external prediction ability. Finally, this QSAR model predicted the anti-leukemic activity of a new set of SLs. Based on this project’s results, further research can be conducted to design new SLs and develop new pharmaceutical products to treat leukemia. |
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