Interactions between Dihydroorotate Dehydrogenase and a Series of Inhibitors of Pyrrole Derivatives for Malaria Treatment: A Study Using Molecular Docking

Abstract

Despite the efforts and resources devoted to the fight against malaria, also the knowledge acquired on the various species of plasmodium, of which Plasmodium faciparum is the most common in humans, malaria remains the world's leading parasitic endemic. Malaria, although a curable disease, continues to be the most important infectious disease in terms of incidence and mortality worldwide. It is a potentially fatal disease caused by parasites transmitted to people through the bites of infected female Anopheles mosquitoes. This disease affects more than 216 million people and kills a million, mainly children and pregnant women. Anti-malaria therapy finds itself confronted with drug-resistant strains, hence the urgency of finding new targets and new anti-infectious agents. Dihydroorotate dehydrogenase (DHODH) is an essential enzyme for the design of new antimalarial drugs. Using a Computer Aided Molecular Design (CAMD) reaction approach, a series of 17 molecules from the pyrrole family, inhibitors of (DHODH) was designed within the protein (PDB code: 6VTN). These molecules with known IC₅₀ were selected to build an RQSAR model presenting a linear correlation between the Gibbs energy (\(\Delta\)\(\Delta\)G), the complexes formed and the experimental inhibition potential (\(pIC^{exp}_{50}\)) : \(pIC^{exp}_{50}\)= - 0.2909 × \(\Delta\)\(\Delta\)G + 7.7715 ; R² = 0,97. we subsequently carried out a study on the catalytic residues (interaction by residue)  in order to exploit the different interactions (enzyme: inhibitor). The predictive power of the QSAR model was validated by the generation of 3D-QSAR pharmacophores (PH4): \(pIC^{exp}_{50}\) = 0.9939 X \(pIC^{est}_{50}\) + 0.0421 ; R² = 0.92. The different methods used, namely molecular docking, interaction energy per residue and the pharmacophore model, allowed us to establish the correlation between biological activity and a set of real numbers called descriptors, to predict the mode of binding of the ligands, the free energies of formation of the different complexes.