Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/79735
Title: Redox biotransformation and delivery of anthracycline anticancer antibiotics : how interpretable structure-activity relationships of lethality using electrophilicity and the london formula for dispersion interaction work
Authors: Pang, SK 
Keywords: Anthracyclines
Electrophilicity
Dispersion interaction
Drug toxicity
Quantitative structure-activity relationship
Quantum chemical methods
Issue Date: 2018
Publisher: Bentham Science Publishers
Source: Current cancer drug targets, 2018, v. 18, no. 6, p. 600-607 How to cite?
Journal: Current cancer drug targets 
Abstract: Background: Quantum chemical methods and molecular mechanics approaches face a lot of challenges in drug metabolism study because of either insufficient accuracy, huge computational cost, or lack of clear molecular level pictures for building computational models. Low-cost QSAR methods can often be earned out, even though molecular level pictures are not well defined; however, they show difficulty in identifying the mechanisms of drug metabolism and delineating the effects of chemical structures on drug toxicity because a certain amount of molecular descriptors are difficult to be interpreted.
Objective: In order to make a breakthrough of QSAR, mechanistically interpretable molecular descriptors were used to correlate with biological activity to establish structure-activity plots. The biological activity is the lethality of anthracycline anticancer antibiotics denoted as log LD50. The mechanistically interpretable molecular descriptors include electrophilicity and the mathematical function in the London formula for dispersion interaction.
Method: The descriptors were calculated using quantum chemical methods.
Results: The plots for electrophilicity, which is interpreted as redox reactivity of anthracyclines, can describe oxidative degradation for detoxification and reductive bioactivation for toxicity induction. The plots for the dispersion interaction function, which represents the attraction between anthracyclines and biomolecules, can describe efflux from and influx into the target cells of toxicity. The plots can also identify three structural scaffolds of anthracyclines that have different metabolic pathways, resulting in their different toxicity behavior.
Conclusion: This structure-dependent toxicity behavior revealed in the plots can provide perspectives on drug design and drug metabolism study.
URI: http://hdl.handle.net/10397/79735
ISSN: 1568-0096
EISSN: 1873-5576
DOI: 10.2174/1568009617666170330145709
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