Abstract
Objective:Cinnamaldehyde (CM) has a molecular structure with the main reaction center of an aromatic ring which the bioactivity can be modified as an anticancer agent by substituting the groups in the ortho (o), meta (m), and para (p) position. The present study aimed to investigate the correlation of the cluster region that was substituted in CM on its activity for various anticancer receptors. Methods:The receptor types used in the test were 5FL6, 1HOV, 4GY7, 5EAM, 4XCU, 4EL9, and 4PQW. The suitability of the hydroxy (OH) and methoxy (OMe) groups, which were substituted, was studied based on the value of Ki, their interactions with metal cofactors, and the type of amino acid residues that function as cancer receptor inhibitors. The docking was conducted using AutoDock 4. Results:The study results showed that all derivative compounds (o, m, and p) –OH and –OMe CM commonly had better anticancer activities than CM. o-OH CM has the best activity against receptors 5FL6, 1HOV, 4GY7, 5EAM, and 4XCU, and m-OMe CM has better activity against the 4EL9 receptors when compared with other CM derivatives. Conclusion:Based on this study, the compound derived from CM, i.e. OHC, tends to show the best anticancer activity.
Highlights
Quantitative structure–activity relationship (QSAR) and molecular docking contribute significantly to the rationale designing of novel drug discovery (Sunyoung et al, 2019; Roberts et al, 2020)
The study results showed that all derivative compounds (o, m, and p) –OH and –OMe CM commonly had better anticancer activities than CM. o-OH CM has the best activity against receptors 5FL6, 1HOV, 4GY7, 5EAM, and 4XCU, and m-OMe CM has better activity against the 4EL9 receptors when compared with other CM derivatives
Various cancers that are used as receptors are Human Carbonic Anhydrase IX (hCA IX), matrix metalloproteinase-2 (MMP-2), and RSK2, which have general mechanisms of action in the body
Summary
Quantitative structure–activity relationship (QSAR) and molecular docking contribute significantly to the rationale designing of novel drug discovery (Sunyoung et al, 2019; Roberts et al, 2020). QSAR provides a role in modern chemistry by describing a molecular activity, with statistical analysis in silico, to simplify and reduce in vivo testing. QSAR is considered less popular, and the results are not obtained as fast as those of molecular docking (Santiago et al, 2008; Sunyoung et al, 2019; Roberts et al, 2020). Some of the applications used in molecular docking for decades include AutoDock, FlexX, Surflex, Glide, LigandFit, Autodock Vina, rDock, and UCSF Dock. Among these applications, AutoDock is one of the most popular applications and one of those having a top-ranking performance with the best score (Nataraj et al, 2007)
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