In silico Screening for Identification of Novel Anti-malarial Inhibitors by Molecular Docking, Pharmacophore Modeling and Virtual Screening.

Objective: Drug resistance from affordable drugs has increased the number of deaths from malaria globally. This problem has raised the requirement to design new drugs against multidrug-resistant Plasmodium falciparum parasite.

Methods: In the current project, we have focused on four important proteins of Plasmodium falciparum and used them as receptors against a dataset of four anti-malarial drugs. In silico analysis of these receptors and ligand dataset was carried out using Autodock 4.2. A pharmacophore model was also established using Ligandscout.

Results: Analysis of docking experiments showed that all ligands bind efficiently to four proteins of Plasmodium falciparum. We have used ligand-based pharmacophore modeling and developed a pharmacophore model that has three hydrophobic regions, two aromatic rings, one hydrogen acceptor and one hydrogen donor. Using this pharmacophore model, we have screened a library of 50,000 compounds. The compounds that shared features of our pharmacophore model and exhibited interactions with the four proteins of our receptors dataset are short-listed.

Conclusion: As there is a need of more anti-malarial drugs, therefore, this research will be helpful in identifying novel anti-malarial drugs that exhibited bindings with four important proteins of Plasmodium falciparum. The hits obtained in this study can be considered as useful leads in anti-malarial drug discovery.