In silico Optimization of Dihydroorotate dehydrogenase Inhibitors for Malaria viaDocking, Molecular Dynamics, and ADMET Evaluation

Plasmodium falciparum continues to be a resistant malaria-causing pathogen. Moreover, it is the causative agent of the most serious and potentially fatal infections that evade cure from the common antimalarial drugs. In drug design, targeting enzymes involved in denovo pyrimidine biosynthesis is one attractive approach due to the selectivity involved, that is, the absence of the pyrimidine salvage pathways in the parasite. In this study, structure-based pharmacophore models were generated with X-ray crystallographic structure of target protein and submitted to Pharmit webserver. Pharmacophore model with seven features was generated and utilized to screen ZINC database to identify the molecules with required features. The molecules identified with essential pharmacophoric features were submitted to standard, stable and accurate modes of docking using iGEMDOCK tool. Top ten molecules identified from accurate docking based on binding energy and interactions in comparison with standard drugs were considered for ADMET predictions. Based on the preliminary calculations, two molecules i.e., ZINC1634081 and ZINC04716501 identified. Further, these results were validated by molecular dynamics simulations and binding calculations. The overall observations indicated both molecules to form highly stable complexes with the target, with higher binding affinity compared to the standard Lefluonomide. Hence, these findings identified potential lead compounds for further experimental investigation and mechanistic studies as DHODH inhibitors.