Predicting the bioactivity of 2-alkoxycarbonylallyl esters as potential antiproliferative agents against pancreatic cancer (MiaPaCa-2) cell lines: GFA-based QSAR and ELM-based models with molecular docking

Predicting the bioactivity of 2-alkoxycarbonylallyl esters as potential antiproliferative agents against pancreatic cancer (MiaPaCa-2) cell lines: GFA-based QSAR and ELM-based models with molecular docking

Abstract Background The number of cancer-related deaths is on the increase, combating this deadly disease has proved difficult owing to resistance and some serious side effects associated with drugs used to combat it. Therefore, scientists continue to probe into the mechanism of action of cancer cel...

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Bibliographic Details
Main Authors: Oluwatoba Emmanuel Oyeneyin, Babatunde Samuel Obadawo, Adesoji Alani Olanrewaju, Taoreed Olakunle Owolabi, Fahidat Adedamola Gbadamosi, Nureni Ipinloju, Helen Omonipo Modamori
Format: Article
Language:English
Published: Elsevier 2021-03-01
Series:Journal of Genetic Engineering and Biotechnology
Subjects:
2-alkoxycarbonyl esters
Computer-aided drug design
Genetic function approximation
Extreme learning machine
Epidermal growth factor receptor
Molecular docking
Online Access:https://doi.org/10.1186/s43141-021-00133-2

Internet

https://doi.org/10.1186/s43141-021-00133-2

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