Computational Approach Towards Exploring Potential Anti-Chikungunya Activity of Selected Flavonoids

Abstract

Chikungunya virus (CHIKV) is a mosquito-borne alphavirus that causes chikungunya infection in humans. Despite the widespread distribution of CHIKV, no antiviral medication or vaccine is available against this virus. Therefore, it is crucial to find an effective compound to combat CHIKV. We aimed to predict the possible interactions between non-structural protein 3 (nsP) of CHIKV as one of the most important viral elements in CHIKV intracellular replication and 3 potential flavonoids using a computational approach. The 3-dimensional structure of nsP3 was retrieved from the Protein Data Bank, prepared and, using AutoDock Vina, docked with baicalin, naringenin and quercetagetin as ligands. The first-rated ligand with the strongest binding affinity towards the targeted protein was determined based on the minimum binding energy. Further analysis was conducted to identify both the active site of the protein that reacts with the tested ligands and all of the existing intermolecular bonds. Compared to the other ligands, baicalin was identified as the most potential inhibitor of viral activity by showing the best binding affinity (-9.8 kcal/mol). Baicalin can be considered a good candidate for further evaluation as a potentially efficient antiviral against CHIKV.