Exploring Novel Antimalarial Compounds Targeting Plasmodium falciparum Enoyl-ACP Reductase: Computational and Experimental Insights

Abstract

Malaria, caused by Plasmodium protozoa with Plasmodium falciparum as the most virulent species, continues to pose significant health challenges. Despite the availability of effective antimalarial drugs, the emergence of resistance has heightened the urgency for developing novel therapeutic compounds. In this study, we investigated the enoyl-ACP reductase enzyme of P. falciparum (PfENR) as a promising target for antimalarial drug discovery. Through a comprehensive analysis, we conducted a comparative evaluation of two lead compounds, LD1 (CID: 44405336, lead compounds 1) and LD2 (CID: 72703246, lead compounds 2), obtained from the PubChem/NCBI ligand database, to serve as reference molecules in the identification of potential derivatives using virtual screening assays. Among the newly identified candidates, Ligand 1 (LG1) and Ligand 2 (LG2) exhibited intriguing characteristics and underwent further investigation through docking and molecular dynamics simulations. Ligand 1 (LG1) demonstrated interactions similar to LD1, including hydrogen bonding with Asp218, while Ligand 2 (LG2) displayed superior binding energy comparable to LD1 and LD2, despite lacking hydrogen bonding interactions observed in the control compounds triclosan and its derivative 7-(4-chloro-2-hydroxyphenoxy)-4-methyl-2H-chromen-2-one (CHJ). Following computational validation using the MM/GBSA method to estimate binding free energy, commercially acquired LG1 and LG2 ligands were subjected to in vitro testing. Inhibition assays were performed to evaluate their potential as PfENR inhibitors alongside triclosan as a control compound. LG1 exhibited no inhibitory effects, while LG2 demonstrated inhibitory effects like triclosan. In conclusion, this study contributes valuable insights into developing novel antimalarial drugs by identifying LG2 as a potential ligand and employing a comprehensive approach integrating computational and experimental methodologies.