PARAMETER OPTIMIZATION AND VIRTUAL SCREENING INDONESIAN HERBAL DATABASE AS HUMAN IMMUNODEFICIENCY VIRUS -1 INTEGRASE INHIBITOR USING AUTODOCK AND VINA

Authors

  • Arry Yanuar Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Universitas Indonesia, Depok, Indonesia.
  • Rezi Riadhi Syahdi Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Universitas Indonesia, Depok, Indonesia.
  • Widya Dwi Aryati Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Universitas Indonesia, Depok, Indonesia.

DOI:

https://doi.org/10.22159/ijap.2017.v9s1.51_57

Keywords:

Virtual Screening, Indonesian Natural Product, Human immunodeficiency virus-1 integrase, Molecular docking

Abstract

Objective: Human immunodeficiency virus (HIV-1) is a virus that causes acquired immunodeficiency syndrome, a disease considered to be one of the
most dangerous because of its high mortality, morbidity, and infectivity. The emergence of mutant HIV strains has led treatment to target protease
as reverse transcriptase and integrase enzyme become less effective. This study aims to provide knowledge about the potential of HIV-1 integrase
inhibitors for use as guiding compounds in the development of new anti-HIV drugs.
Methods: This study used AutoDock and AutoDock Vina for virtual screening of the Indonesian herbal database for inhibitors of HIV-1 integrase and
is validated using a database of the directory of useful decoys. Optimization was accomplished by selecting the grid size, the number of calculations,
and the addition of two water molecules and a magnesium atom as cofactor.
Results: This study determined that the best grid box size is 21.1725×21.1725×21.1725 in unit space size (1 unit space equals to macromolecules 1Ǻ),
using AutoDock Vina with EF and AUC values, 3.93 and 0.693, respectively. Three important water molecules have meaning in molecular docking
around the binding pocket.
Conclusions: This study obtained the top ten ranked compounds using AutoDock Vina. The compounds include: Casuarinin; Myricetin-3-O-(2'',6''-
di-O-α-rhamnosyl)-β-glucoside; 5,7,2',4'-tetrahydroxy-6,3'-diprenylisoflavone 5-O-(4''-rhamnosylrhamnoside); myricetin 3-robinobioside; cyanidin
3-[6-(6-ferulylglucosyl)-2-xylosylgalactoside]; mesuein, cyanidin 7-(3-glucosyl-6-malonylglucoside)-4'-glucoside; kaempferol 3-[glucosyl-(1→3)-
rhamnosyl-(1→6)-galactoside]; 3-O-galloylepicatechin-(4-β→8)-epicatechin-3-O-gallate; and quercetin 4'-glucuronide.

Downloads

Download data is not yet available.

References

Radji M. Immunology and Virology. 1st ed. Jakarta: PT ISFI Penerbitan;

National AIDS Committee. World HIV/ AIDS Day 2013: Protect

Workers, Families, and Nation; 2013.

Adesokan AA, Roberts VA, Lee KW, Lins RD, Briggs JM. Prediction

of HIV-1 integrase/viral DNA interactions in the catalytic domain by

fast molecular docking. J Med Chem 2004;47(4):821-8.

Xiong J. Essential Bioinformatics. New York: Cambridge University

Press; 2006.

Ghosh AK, Dawson ZL, Mitsuya H. Darunavir, a conceptually new

HIV-1 protease inhibitor for the treatment of drug-resistant HIV. Bioorg

Med Chem 2007;15(24):7576-80.

Syahdi RR. Virtual Screening of Indonesian Herbal Database as

HIV-1 Enzymes Inhibitors. Depok: Fakultas Matematika dan Ilmu

Pengetahuan Alam Universitas Indonesia; 2011.

Huang N, Shoichet BK, Irwin JJ. Benchmarking sets for molecular

docking. J Med Chem 2006;49(23):6789-801.

Wallach I, Lilien R. Virtual decoy sets for molecular docking

benchmarks. J Chem Inf Model 2011;51(2):196-202.

Lyons T, Fisher L, Varma S, Chen D. Creating a Smart Virtual Screening

Protocol, Part 1: Preparing the Target Protein. San Diego: Accelrys; 2005.

Bender A, Glen RC. A discussion of measures of enrichment in virtual

screening: Comparing the information content of descriptors with

increasing levels of sophistication. J Chem Inf Model 2005;45(5):1369-75.

Mysinger MM, Carchia M, Irwin JJ, Shoichet BK. Directory of useful

decoys, enhanced (DUD-E): Better ligands and decoys for better

benchmarking. J Med Chem 2012;55(4):6582-94.

Fawcett T. An introduction to ROC analysis. Pattern Recognit

;27:861-74.

Yanuar A. Molecular tethering: Practices and applications on virtual

screening. Depok: Fakultas Farmasi Universitas Indonesia; 2012.

Published

30-10-2017

How to Cite

Yanuar, A., Syahdi, R. R., & Aryati, W. D. (2017). PARAMETER OPTIMIZATION AND VIRTUAL SCREENING INDONESIAN HERBAL DATABASE AS HUMAN IMMUNODEFICIENCY VIRUS -1 INTEGRASE INHIBITOR USING AUTODOCK AND VINA. International Journal of Applied Pharmaceutics, 9, 90–93. https://doi.org/10.22159/ijap.2017.v9s1.51_57

Issue

Section

Original Article(s)

Most read articles by the same author(s)

1 2 3 > >> 

Similar Articles

1 2 3 4 5 > >> 

You may also start an advanced similarity search for this article.