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Current Drug Therapy

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ISSN (Print): 1574-8855
ISSN (Online): 2212-3903

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Research Article

Network-Pharmacology and DFT Based Approach Towards Identification of Leads from Homalomena aromatica for Multi-Target In-Silico Screening on Entamoeba histolytica Proteins

Author(s): Ashis Kumar Goswami , Hemanta Kumar Sharma*, Neelutpal Gogoi and Bhaskar Jyoti Gogoi

Volume 15, Issue 3, 2020

Page: [226 - 237] Pages: 12

DOI: 10.2174/1574885514666190801102336

Price: $65

Abstract

Background: Entamoeba histolytica is the primary protozoan that causes amoebic dysentery and is prioritized as the third most prevalent protozoan causing parasitosis. Drug of choice in amoebic dysentery is metronidazole but it has unpleasant side effects with reports of development of resistance in certain cases. Homalomena aromatica Schott. is a plant which is used in different ethnomedicinal practices of South-east Asia to treat stomach ailments against intestinal parasites.

Objective: In the present study, a docking weighted network pharmacology-based approach was employed to understand the effects of a library of 71 natural molecules reported from Homalomena aromatica with reference to four proteins of Entamoeba histolytica namely thioredoxin reductase, cysteine synthase, glyceraldehyde-3-phosphate dehydrogenase, and ornithine decarboxylase.

Methods: Molecular docking of the phytoconstituents of H. aromatica was performed in Biovia Discovery Studio 2017 R2 software suite on the selected proteins of E. histolytica. A connection was established between the proteins and molecules through network pharmacology weighted docking studies with the help of Cytoscape V3.4.0 software to select three molecules namely HM 7, HM 23 and HM 24 on the basis of the generated network between the molecules and targets. Quantum mechanics based Density Functional Theory (DFT) analysis was performed on the filtered molecules to ascertain their viability with respect to LUMO-HOMO orbital energies of the filtered molecules.

Results: On the basis of the docking studies of the natural molecules on the selected protein targets, a network of molecules was built. DFT based minimum energy gap was analysed to further ascertain the most potential inhbitors. Three molecules from H. aromatica; 3,7-dimethylocta-1,6-dien-3- yl acetate, α -methyl-α-(4-methyl-3-pentenyl)-oriranemethanol, and 7-octadiene-2,6-diol-2,6- dimethyl were predicted to be potential lead molecules against amoebiasis.

Conclusion: The present study provides important evidence for the development of new drug molecules to treat amoebiasis.

Keywords: Docking, binding energy, LibDock, linalool, amoebiasis, lipinski`s rule.

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