VIRTUAL SCREENING OF BETA-SECRETASE 1 (BACE1) INHIBITORS IN THE INDONESIAN HERBAL DATABASE AS USING AUTODOCK AND AUTODOCK VINA

Authors

  • Asti Anna Tanisa Department of , Faculty of Pharmacy, Universitas Indonesia, Depok, Indonesia.
  • Rezi Riadhi Department of , Faculty of Pharmacy, Universitas Indonesia, Depok, Indonesia.
  • Arry Yanuar Department of , Faculty of Pharmacy, Universitas Indonesia, Depok, Indonesia

DOI:

https://doi.org/10.22159/ajpcr.2017.v10s5.23119

Keywords:

Virtual screening, Herbal database, BACE1, Molecular docking

Abstract

 

 Objective: Alzheimer's is a neurodegenerative disease caused by the accumulation of senile plaque in the brain that affects neuronal system leading to a less sensitive cellular response from neurons. Previous research has found that beta-secretase 1 (BACE1) plays an important role in the senile plaque formation, become a target in Alzheimer's medication.

Methods: In this study, virtual screening of BACE1 inhibitors on the Indonesian Herbal Database was done using AutoDock and AutoDock Vina. The screening was validated using the directory of useful decoys: Enhanced database. Parameters for validation process of AutoDock and AutoDock Vina are enrichment factor (EF), receiver operating characteristics, and area under the curve (AUC).

Results: The dimensions of grid boxes were 30×30×30 (AutoDock) and 11.25×11.25×11.25 (AutoDock Vina). The EF 1% and AUC values obtained from the AutoDock are 7.74 and 0.73, respectively, and in the AutoDock Vina are 4.6 and 0.77, respectively. Based on the virtual screening results, the top six compounds obtained using AutoDock (binding energy ranging from −7.84 kcal/mol to −8.79 kcal/mol) include: Azadiradione, cylindrin, lanosterol, sapogenin, simiarenol, and taraxerol. The top seven compounds (binding energy ranging from −8.8 kcal/mol to −9.4 kcal/mol) obtained using AutoDeck Vina include: Bryophyllin A, diosgenin, azadiradione, sojagol, beta-amyrin, epifriedelinol, and jasmolactone C.

Conclusions: Only azadiradione was obtained from the virtual screening conducted using both types of software; it interacts with the active region in BACE1 at residue Trp 76 (AutoDock result) and Thr 232 (AutoDock Vina result).  

Downloads

Download data is not yet available.

References

Vyas V, Jain A, Jain A, Gupta A. Virtual screening: A fast tool for drug design. Sci Pharm 2008;76(3):333-60.

Gravenfors Y, Viklund J, Blid J, Ginman T, Karlström S, Kihlström J. New aminoimidazoles as β - Secretase (BACE-1) inhibitors showing Amyloid-β (Aβ) lowering in brain. J Med Chem 2012;55(21):9297-311.

Hwang EM, Ryu YB, Kim HY, Kim DG, Hong SG, Lee JH, et al. BACE1 inhibitory effects of lavandulyl flavanones from Sophora flavescens. Bioorg Med Chem 2008;16:6669-74.

Cumming JN, Smith EM, Wang L, Misiaszek J, Durkin J, Iserloh U. Structure based design of iminohydantoin BACE1 inhibitors: Identification of an orally available, centrally active BACE1 inhibitor. Bioorg Med Chem Lett 2012;22(7):2444-9.

Alvarez J, Shoichet B. Virtual Screening in Drug Discovery. Boca Raton: CRC Press Taylor & Francis Group; 2005.

Yanuar A, Mun’im A, Lagho AB, Syahdi RR, Rahmat M, Suhartanto H. Medicinal plants database and three dimensional structure of the chemical compounds from medicinal plants in Indonesia. Int J Comput Sci 2011;8(5):180-3.

Pribadi ER. Pasokan dan permintaan tanaman obat Indonesia serta arah penelitian dan pengembangannya. Perspectives 2009;8(1):52-64.

Yanuar A. Penambatan Molekular: Praktek Dan Aplikasi Pada Virtual Screening. Depok: Fakultas Farmasi, Universitas Indonesia; 2012. p. 39-60.

Cerqueira NM, Gesto D, Oliveira EF, Santos-Martins D, Brás NF, Sousa SF. Receptor-based virtual screening protocol for drug discovery. Arch Biochem Biophys 2015;582:56-7.

Lemke TL, Williams DA, Roche VF, Zito SW. Foye’s principles of medicinal chemistry. 6th ed. USA: Lippincott Williams & Wilkins; 2008.

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

Screening Protocol, Part I : Preparing the Target Protein.

Study; 2005. p. 1.Pharmaceutical Case

Kirchmair J, Markt Æ, Distinton S, Wolber Æ. Evaluation of the performance of 3D virtual screening protocols: RMSD comparisons, enrichment assessments, and decoy selection - What can we learn from earlier mistakes ? J Comput Aided Mol 2008;22(3-4):213-8.

Kaur J, Goyal S, Sharma S, Hamid R, Grover A. Mechanistic insights into mode of action of potent natural antagonists of BACE-1 for checking Alzheimer’s plaque pathology. Biochem Biophys Res Commun 2014;443(3):1054-9.

Vinh NB, Simpson JS, Scammells PJ, Chalmers DK. Virtual screening using a conformationally flexible target protein: Models for ligand binding to p38α MAPK. J Comput Aided Mol Des 2012;26(4):409-23.

Huang D, Liu Y, Shi B, Li Y, Wang G, Liang G. Comprehensive 3D-QSAR and binding mode of BACE-1 inhibitors using R-group search and molecular docking. J Mol Graph Model 2013;45:65-83.

Youn K, Lee J, Yun E, Ho C. Short communications biological evaluation and in silico docking study of γ-linolenic acid as a potential BACE1 inhibitor. J Funct Foods 2014;10:187-91.

Published

01-10-2017

How to Cite

Tanisa, A. A., R. Riadhi, and A. Yanuar. “VIRTUAL SCREENING OF BETA-SECRETASE 1 (BACE1) INHIBITORS IN THE INDONESIAN HERBAL DATABASE AS USING AUTODOCK AND AUTODOCK VINA”. Asian Journal of Pharmaceutical and Clinical Research, vol. 10, no. 17, Oct. 2017, pp. 148-52, doi:10.22159/ajpcr.2017.v10s5.23119.

Issue

Section

Original Article(s)

Most read articles by the same author(s)