QSAR ANALYSIS USING SEMI-EMPIRICAL AM1 METHOD, MOLECULAR DOCKING, AND ADMET STUDIES OF CHALCONE DERIVATIVES AS ANTIMALARIAL COMPOUNDS

Abstract

Malaria is a serious caused by protozoan parasites such as Plasmodium groups and has fatal consequences for human health. The increase in the resistance of the Plasmodium parasites toward existing antimalarial drugs prompts the exploration of novel compounds. In this study, quantitative structure-activity relationship (QSAR) analysis using the semi-empirical AM1 method was conducted to identify the optimal model that relates physicochemical properties and biological activity of chalcone derivatives. In addition, ADMET prediction and molecular docking were also carried out. Multilinear regression calculations for statistical parameters of QSAR models revealed that Model 4, with 11 independent variables, provided the best predictions and exhibited a robust correlation with antimalarial activity represented by inhibitory concentration (IC50). ADMET predictions indicated favorable absorption, distribution, metabolism, excretion, and toxicity properties, particularly for B2D, showing promising antimalarial attributes. Molecular docking studies targeting 5 mutated PfDHODH proteins revealed B2D’s potential to reach therapeutic targets efficiently. It has low docking scores for mutations I (-10.5 kcal/mol), II (-8.6 kcal/mol), and V (-10.5 kcal/mol) with RMSD < 2Å, in carrying out its role for antimalarial activity. This research successfully identifies B2D as an efficient inhibitor of PfDHODH receptors. Thus, it is a highly promising novel antimalarial drug.

Keywords

• admet prediction
• antimalarial agents
• chalcone derivative
• molecular docking
• qsar