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Current Proteomics

Editor-in-Chief

ISSN (Print): 1570-1646
ISSN (Online): 1875-6247

Research Article

Novel Potent Plasmepsin-I (PMI) Inhibitors: An In-Silico Approach

Author(s): Kamal Kumar Chaudhary, Utkarsh Raj, Pritish Kumar Varadwaj and Nidhi Mishra

Volume 13, Issue 3, 2016

Page: [196 - 205] Pages: 10

DOI: 10.2174/1570164613666160722101951

Price: $65

Abstract

Background: Various taxonomic category of the genus Plasmodium are responsible for malaria, the disease induced by P. falciparum is life-threatening if left untreated. The degradation of hemoglobin is a major metabolic process required for the endurance of Plasmodium in its host. Plasmepsin-I is the most promising drug target for malaria. Plasmepsins are the other name for the aspartic proteases of Plasmodium spp., which are necessitated in the degradation of hemoglobin within the food vacuole throughout the erythrocytic stage of the parasite’s life cycle.

Objective: Identification of novel inhibitors for plasmepsins through virtual screening, docking and simulation.

Methodology: We generated diverse combinatorial library-based ligands to achieve this aim. Structures for 11826 lead and drug like molecules were downloaded from the zinc database in mol2 format for known inhibitors of plasmepsin protein, using code 3QRV, and were used for virtual screening with Openeye Scientific software. Various analysis were carried out to study the consequences of this virtual screening and docking approach, including residue interactions with key residues of the protein, Chemgauss4 scores, shape, hydrogen bonding, and binding energy.

Results/Conclusion: Our work demonstrates not just the relevancy of computer aided drug discovery, merely as well places a range of small molecules that hold the potential to serve as candidates for inhibition of P. falciparum plasmepsins. Utilizing the approach of virtual screening, Molecular Docking, Molecular dynamics simulation and ADME/T versus the malaria-causing parasite P. falciparum, we demonstrate that a computer-aided drug design infrastructure provides new models to explore battle against disease of the inadequate. The results describe a group of top-ranking compounds for further consideration.

Keywords: ADME/T, Aspartic Protease, Malaria, Molecular Docking, Molecular Dynamics Simulation, Plasmepsin, Virtual Screening.

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