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2018| January-March | Volume 8 | Issue 1
Online since
January 15, 2018
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ORIGINAL ARTICLES
Pharmacophore Modeling and Database Mining to Identify Novel Lead Compounds Active Against the Disease Stage of Trypanosomiasis in the Central Nervous System
Kirtika Madan, Ankita N Verma, Sarvesh K Paliwal, Divya Yadav, Swapnil Sharma, Manu Sharma
January-March 2018, 8(1):16-31
DOI
:10.4103/ijnpnd.ijnpnd_53_17
Introduction:
Sleeping sickness has long been considered as a neglected disease, and very few pharmaceutical companies and research organizations are involved in the design and development of anti-trypanosomal drugs. This may be especially due to poor financial returns.
Materials and Methods:
In view of the dire need for new drugs for sleeping sickness, we have implemented
in-silico
ligand- and structure-based methods for the development of a universal pharmacophore model. The ligand-based pharmacophore models for 1,2-dihydroquinolin-6-ols and their ester derivatives were developed using Catalyst HypoGen refine algorithm. The best quantitative pharmacophore hypothesis was selected on the basis of correlation coefficient (0.92), root mean square deviation (0.97), and cost difference (76) values. The best pharmacophore model was compared with a structure-based model developed using the Protein Data Bank structure of trypanothione reductase (TR) bound to WPC inhibitor.
Results and Discussion:
High consistency between ligand- and structure-based models was observed, and both the approaches indicate that four-point interactions [three hydrophobic and one hydrogen bond acceptor (HBA)] are necessary for the anti-trypanosomal activity of 1,2-dihydroquinolin-6-ols. The pharmacophoric features obtained were in accordance with the binding requirement of TR binding site, indicating that these compounds can act as TR inhibitors. To further evaluate the model, an external test set comprising known trypanocidal agents were mapped on to a developed pharmacophoric model, which also showed four-point mapping and estimated values in close range to actual values. The screening of chemical database resulted in the identification of three druggable structurally diverse potent lead compounds.
Conclusion:
Since no pharmacophore model has been developed for this new series of compounds till date, the achieved results will allow researchers to further use this 3D pharmacophore model and hits for the design and synthesis of newer anti-trypanosomal compounds.
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Attenuation of Arsenic-Induced Dyslipidemia by Fruit Extract of
Emblica Officinalis
in Mice
Manish K Singh, Pramod K Singh, Suraj S Yadav, Uma S Singh, Pradeep Dwivedi, Rajesh S Yadav
January-March 2018, 8(1):3-9
DOI
:10.4103/ijnpnd.ijnpnd_69_17
Introduction:
In our earlier studies, we reported that arsenic-induced enhanced oxidative stress, apoptosis, immunotoxicity and inflammation in the spleen and thymus of mice and hepatotoxicity have been protected through treatment with
Emblica officinalis
(amla). The present study is focused on to the efficacy of amla in mitigation of arsenic-induced dyslipidemia and alterations in inflammatory biomarkers in the blood of mice.
Materials and Methods:
Mice were randomly divided into four groups and treated with sodium arsenite (3 mg/kg b.w.,
per os
), amla (500 mg/kg b.w.,
per os
) and simultaneously with arsenic and amla daily for 30 days.
Results:
Arsenic treatment altered the hematological and lipid profile by increasing total cholesterol (TC), triglyceride (TG), phospholipid (PL) and low-density lipoprotein (LDL) levels and decreasing high-density lipoprotein (HDL) levels as compared to controls. Treatment with arsenic also disturbed the levels of inflammatory biomarkers. Concurrent treatment with arsenic and amla significantly restored serum TC level (0.83-fold), TG level (0.92-fold), LDL level (0.72-fold), PL level (1.29-fold), and increased HDL level (1.4-fold). Inflammatory cytokine levels were also corrected significantly as serum interleukin-8 level (0.6-fold) and C-reactive protein level decreased (0.7-fold) respectively, while interleukin-10 level was increased (1.5-fold) as compared to those treated with arsenic alone. The alterations in hematological parameters were also found to be normalized by treatment of amla.
Conclusion:
The results of the present study strengthen the fact that nutritional supplement of amla in arsenic affected areas might improve the adverse effects of arsenic on lipid profile.
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The Potency of Nanoparticle of
Pinus merkusii
as Immunostimulatory on Male Wistar Albino Rat
Sri Agus Sudjarwo, Giftania Wardani, Koerniasari Eraiko, Koerniasari
January-March 2018, 8(1):10-15
DOI
:10.4103/ijnpnd.ijnpnd_72_17
Objective:
Medicinal herbs are the commonly used worldwide immunomodulators in the management of various disease conditions. The aim of this study was to evaluate the immunostimulatory activity of the nanoparticle extract of
Pinus merkusii
in Wistar albino rats.
Materials and Methods:
It was an experimental study that was conducted on various groups of animals each with six healthy adult rats. Neutrophil adhesion test, hemagglutinating antibody (HA) titer, delayed-type hypersensitivity (DTH) response, phagocytic activity, and cyclophosphamide-induced myelosuppression were determined in various groups of animals.
Results:
The nanoparticle of extract
P. merkusii
at doses 500 mg/kg BW but not at doses 125 mg/kg BW and 250 mg/kg BW induced a significant increase in percent neutrophil adhesion fibers as well as a dose-dependent increase in antibody titer values and potentiated the DTH reaction induced by sheep red blood cells. Also, it prevented myelosuppression in cyclophosphamide drug-treated rats and good response toward phagocytosis in carbon clearance assay.
Conclusion:
From these findings, it can be concluded that nanoparticle extract of
P. merkusii
possesses immunostimulatory activity and has therapeutic potential for the prevention of immune-depressed conditions.
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EDITORIAL
Primary Health Care to Conserve the Access to Health Care for the Marginalized Communities of the Developing World
Mainul Haque
January-March 2018, 8(1):1-2
DOI
:10.4103/ijnpnd.ijnpnd_80_17
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