Computational Bioprospecting of Natural Compounds Targeting PfLDH for Malaria

This dataset contains the results of a computational bioprospecting study aimed at discovering novel inhibitors for Plasmodium falciparum lactate dehydrogenase (PfLDH), a key target in malaria treatment. The data includes molecular docking results, molecular dynamics simulations, and in silico mutagenesis analyses of 24,316 natural product compounds retrieved from Traditional Chinese Medicine (TCM) databases. The study used advanced computational techniques such as molecular docking, molecular dynamics (MD) simulations, and in silico mutagenesis to identify potential antimalarial compounds that can inhibit PfLDH, especially in the presence of enzyme mutations associated with drug resistance. This dataset is valuable for researchers in the field of drug discovery and malaria treatment, as it provides computational insights into the efficacy of natural compounds as potential inhibitors of PfLDH, which could offer a novel approach to counteract the growing problem of drug resistance in malaria.