In Silico Identification and Molecular Dynamics Analysis of PfLysRS Inhibitors for Malaria Treatment
Abstract
ABSTRACT Plasmodium falciparum lysyl‐tRNA synthetase (PfLysRS) is an essential enzyme involved in parasite protein biosynthesis. In this study, we aimed to identify and prioritize potential PfLysRS inhibitors. Virtual screening was used for initial screening, followed by density functional theory (DFT) optimization to refine ligand geometries and electronic properties, including HOMO–LUMO characteristics. Redocking analyses confirmed the retention of favorable binding poses with predicted binding affinities ranging from −12.4 to −11.8 kcal/mol relative to the native reference ligand. The top‐ranked compounds were further evaluated using long‐timescale molecular dynamics simulations (500 ns), which demonstrated stable protein–ligand complexes with limited RMSD and RMSF fluctuations and persistent interaction patterns. MM/GBSA binding free energy calculations indicated favorable predicted binding affinities, with Compound 22401385 showing the most favorable ΔG _total among the evaluated candidates. Principal component analysis (PCA) and free energy landscape (FEL) analyses revealed that the top complexes predominantly occupied stable conformational basins during simulation. Structural convergence analysis of low‐energy conformers showed minimal RMSD variation (<2 Å), while QM/MM calculations supported favorable electronic environments within the PfLysRS binding pocket. This study identifies compound 22401385 as a promising antimalarial candidate. The presented computational…
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Evidence Hub reads this as a simulation / modelling, done in computer models (in silico), not in people. Its evidence level is 5 of 5 (Very low · case / narrative / animal / in vitro / in silico). Case reports, narrative reviews, and animal, cell or computer-model studies give the weakest evidence for human health.
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