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In silico screening for identification of novel anti-malarial inhibitors by molecular docking, pharmacophore modeling and virtual screening
- Source :
- Scopus-Elsevier
-
Abstract
- 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 multidrugresistant 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.
- Subjects :
- Virtual screening
biology
Drug discovery
Plasmodium falciparum
Drug Evaluation, Preclinical
Protozoan Proteins
Computational biology
AutoDock
biology.organism_classification
Molecular Docking Simulation
Combinatorial chemistry
LigandScout
Antimalarials
User-Computer Interface
Docking (molecular)
parasitic diseases
Drug Discovery
Humans
Computer Simulation
Pharmacophore
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- Scopus-Elsevier
- Accession number :
- edsair.doi.dedup.....7c28111f08a91e3444a408fc8504badc