Drug delivery in a safe manner is a major challenge in the drug development process. Growth factor receptors (GFRs) are known to have profound roles in the growth and progression of cancerous cells making these receptors a therapeutic target in the effective treatment of cancer. This work focused on exploring bioactive compounds that can target GFRs using in silico method. In this study, 50 bioactive compounds from different plant sources were screened as anticancer agent against GFRs using drug likeness parameters of Lipinski’s rule of five. The molecular docking was performed between phytochemicals and GFRs. Ligands with acceptable drug likeness and binding energy comparable to the standard drugs were further screened to determine their pharmacokinetic activities. This study showed phytochemicals with the binding energy comparable with the standard drugs (Dovitinib and Gefitinib), while ADME, bioactivity score, and bioavailability radar analysis gave further insight on these compounds as potent anticancer agents.
Drug delivery in a safe manner is a major challenge in the drug development process. Growth factor receptors (GFRs) are known to have profound roles in the growth and progression of cancerous cells making these receptors a therapeutic target in the effective treatment of cancer. This work focused on exploring bioactive compounds that can target GFRs usingin-silico method. In this study, 50 bioactive compounds from different plant sources were screened as anticancer agent against GFRs using drug likeness parameters of Lipinski’s rule of five. The molecular docking was performed between phytochemicals and GFRs. Ligands with acceptable drug likeness and binding energy comparable to the standard drugs were further screened to determine their pharmacokinetic activities. This study showed phytochemicals with the binding energy comparable with the standard drugs (Dovitinb and Geftinib), while ADME, bioactivity score and bioavailability radar analysis gave further insight on these compounds as potent anticancer agents.
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