Molecular Docking of South Sulawesi Propolis against Fructose 1,6-Bisphosphatase as a Type 2 Diabetes Mellitus Drug
Corresponding email: sahlan@che.ui.ac.id
Published at : 27 Nov 2020
Volume : IJtech
Vol 11, No 5 (2020)
DOI : https://doi.org/10.14716/ijtech.v11i5.4332
Sahlan, M., Faris, M.N.H.A., Aditama, R., Lischer, K., Khayrani, A.C., Pratami, D.K., 2020. Molecular Docking of South Sulawesi Propolis against Fructose 1,6-Bisphosphatase as a Type 2 Diabetes Mellitus Drug. International Journal of Technology. Volume 11(5), pp. 910-920
| Muhamad Sahlan | Department of Chemical Engineering, Faculty of Engineering, Universitas Indonesia, Kampus UI Depok, West Java 16424, Indonesia |
| Muhammad Nizar Hamzah Al Faris | Department of Chemical Engineering, Faculty of Engineering, Universitas Indonesia, Kampus UI Depok, West Java 16424, Indonesia |
| Reza Aditama | Biochemistry Research Group, Faculty of Mathematics and Natural Sciences, Institut Teknologi Bandung, Bandung, West Java 40132, Indonesia |
| Kenny Lischer | Department of Chemical Engineering, Faculty of Engineering, Universitas Indonesia, Kampus UI Depok, West Java 16424, Indonesia |
| Apriliana Cahya Khayrani | Department of Chemical Engineering, Faculty of Engineering, Universitas Indonesia, Kampus UI Depok, West Java 16424, Indonesia |
| Diah Kartika Pratami | Lab of Pharmacognosy and Phytochemistry, Faculty of Pharmacy, Pancasila University, Jakarta, 12640, Indonesia |
Diabetes
mellitus is one of the metabolic diseases, characterized by hyperglycemia,
which is usually caused by endogenous glucose production through
gluconeogenesis. Furthermore, fructose 1,6-bisphosphatase (FBPase), which is
the last enzyme involved in gluconeogenesis, is used as inhibition target due
to its relatively safe effect. In addition, It is known that propolis has shown
antidiabetic activity through some sets of mechanisms due to its varied
constituents. Therefore, this study aims to explore the antidiabetic activity
of South Sulawesi propolis compounds against the allosteric site of FBPase (PDB
ID: 3KC1) through molecular docking on Autodock Vina. The results show that 18
out of 30 propolis compounds outweigh AMP affinity. Furthermore, only two
flavonoids showed 100% interaction similarity to the re-docked native ligand
and AMP natural inhibition. These two compounds were Broussoflavonol F and
Glyasperin A, which had docking score of -9 kcal/mol and -8.2 kcal/mol,
respectively. This indicates that both compounds are capable of being used as
FBPase inhibitors for the treatment of diabetes mellitus.
Allosteric inhibition; Diabetes mellitus; Fructose 1,6-Bisphosphatase; Molecular docking; Propolis
Diabetes
mellitus is a world-wide metabolic disease that is characterized by
hyperglycemia, which is usually caused by insulin secretion deficiency (Association,
2014; Abdillah and Suwarno, 2016). In severe hyperglycemia cases, the
disease is worsened by the accompaniment of organ failures (Association,
2014; Seeberger and Rademacher, 2014). Among several classifications of the
disease, type 2 diabetes mellitus (T2DM), for which insulin resistance is an
additional symptom, is accounted for 90–95% of the total recorded cases. Most
T2DM patients frequently go undiagnosed for many years, and the risk increases
with age, obesity, and an unhealthy lifestyle (Moller,
2001; Association, 2014; Control, 2020). To date, several T2DM drugs
have been developed and marketed, including thiazolidinediones and metformin
groups. Unfortunately, the use
of thiazolidinediones
Fructose 1,6-Bisphosphatase (FBPase) is known to be the
penultimate enzyme in the gluconeogenesis pathway that catalyzes the hydrolysis
of fructose 1,6-bisphosphate to fructose 6-phosphate by controlling the
conversion of all substrates into glucose (Erion
et al., 2005; Tsukada et al., 2009; Seeberger and Rademacher, 2014). Two reasons for choosing FBPase
as an inhibition target are, that: (1) it does not directly involved in
glycogenolysis, glycolysis, or the tricarboxylic acid cycle (Erion et al., 2005); and (2) the genetic deficiency of the
compound in humans shows no severe anomaly in biochemical and clinical
parameters (Matsuura et al.,
2002; Seeberger and Rademacher, 2014). In regulating blood glucose
levels, the inactive state of FBPase is naturally inhibited by AMP at the
allosteric site, and by fructose 2,6-bisphosphate at the substrate part (Tsukada
et al., 2009). This study focuses on the
allosteric site, since its nature is not highly hydrophilic, unlike that of the
substrate (Erion
et al., 2005).
Propolis is a resinous material collected by honeybee from various
plant, which has been preclinically proven for its variety of chemical
constituent, exhibiting a wide range of biological activities, including antioxidant,
antimicrobial, anti-inflammatory, and antidiabetic (Fuliang
et al., 2005; Diva et al., 2019; Pratami et al., 2019). Propolis constituents include
polyphenols, aromatic acids, terpenoids, steroids, and amino acids depending on
its vegetation and geographical origin (Kumazawa
et al., 2004; Miyata
et al., 2020). Propolis has been shown to have
antidiabetic properties in that it reduces the total cholesterol levels,
decreases low and increases high-density lipoproteins, and regulates blood
glucose levels (Fuliang
et al., 2005). According to Miyata et al. (2020) there are several new
compounds that have been obtained from South Sulawesi propolis through X-ray
structure analysis (Miyata et al., 2020).
In modern drug discovery, virtual screening of constituents has
become an important step in evaluating and reducing the number of compounds to
be subjected to experimental testing (Seeliger and de Groot,
2010). There are two common methods of
virtual screening in drug discovery: (1) molecular docking, which simulates
small molecules to protein binding sites by assuming the receptor to be rigid
and have a constant covalent length and angles, as well as a rotatable ligand
bond (Trott
and Olson, 2010); and (2) molecular dynamics,
which evaluates every single atom during simulation. This technique, however,
requires many processes and high-performance hardware (Suhartanto et al., 2018). In general, docking programs use a scoring
function based on empirical free binding energies to measure conformation (Trott and Olson,
2010; Forli et al., 2016). Despite the fact that there is
no scoring function that accurately measures binding affinity, due to its
simplification and insufficient experimental data, fitness accuracy is reached
by employing optimizers, such as those used in AutoDock (Trott
and Olson, 2010; Seeberger and Rademacher, 2014).
This research aims to evaluate the antidiabetic activity of South
Sulawesi propolis compounds from LC-MS/MS analysis and results published by Miyata et al. (2020) by inhibiting fructose 1,6-bisphosphatase at
the allosteric site. Although there have been many molecular docking studies,
the use of South Sulawesi propolis as a drug candidate for diabetes mellitus
has not been carried out. Therefore, this study is recommended as a reference
for further in vitro research.
In this study, the in silico antidiabetic activity of South Sulawesi
propolis was investigated. Among 30 selected propolis compounds, only 18 showed
promising docking scores compared to AMP (-6.7 kcal/mol). Meanwhile,
Broussoflavonol F and Glyasperin A showed docking scores of -9 kcal/mol and
-8.2 kcal/mol, respectively, indicating 100% residue similarity in its
interaction compared to the two re-docked positive controls and the AMP
reference. Thus, both compounds have the potential to act against T2DM by
inhibiting FBPase. Furthermore, the flavonoid structure is recommended for
designing FBPase inhibitors. Finally, to ensure the validity of this finding,
further research should be conducted by employing in vitro studies.
We acknowledge the financial support from the Ministry of
Research, Technology, and Higher Education Republic of Indonesia through the
Grants Penelitian Tesis Magister (Nomor:8/E1/KP.PTNBH/2020 and
Nomor:255/PKS/R/UI/2020).
Abdillah, A.A., Suwarno., 2016.
Diagnosis of Diabetes using Support Vector Machines with Radial Basis Function
Kernels. International Journal of Technology, Volume (7)5, pp. 849–858
Association, A.D., 2014.
Diagnosis and Classification of Diabetes Mellitus. Diabetes Care, Volume
37(Supplement 1), pp. S81–S90
Control, C.F.D.P., 2020. National
Diabetes Statistics Report. Atlanta, GA: Centers for Disease Control and
Prevention, US Department of Health and Human Services
Daina, A., Michielin, O., Zoete,
V., 2017. SwissADME: A Free Web Tool to Evaluate Pharmacokinetics,
Drug-Likeness and Medicinal Chemistry Friendliness of Small Molecules. Scientific
Reports, Volume 7(42717), pp. 1–13
Diva, A.N., Pratami, D.K.,
Wijanarko, A., Hermansyah, H., Sahlan, M., 2019. Effect of Ethanolic Propolis
Extract from Tetragonula Biroi Bees on the Growth of Human Cancer Cell Lines
Hela and MCF-7. In: AIP Conference
Proceedings, Volume 2092(1), p. 030002
Erion, M.D., Van Poelje, P.D.,
Dang, Q., Kasibhatla, S.R., Potter, S.C., Reddy, M.R., Reddy, K.R., Jiang, T.,
Lipscomb, W.N., 2005. MB06322 (CS-917): A Potent and Selective Inhibitor of
Fructose 1, 6-Bisphosphatase for Controlling Gluconeogenesis in Type 2
Diabetes. In: Proceedings of the National Academy of Sciences, Volume
102(22), pp. 7970–7975
Forli, S., Huey, R., Pique, M.E.,
Sanner, M.F., Goodsell, D.S., Olson, A.J., 2016. Computational Protein–Ligand
Docking and Virtual Drug Screening with the Autodock Suite. Nature Protocols,
Volume 11(5), pp. 905–919
Fuliang, H., Hepburn, H., Xuan,
H., Chen, M., Daya, S., Radloff, S., 2005. Effects of Propolis on Blood
Glucose, Blood Lipid and Free Radicals in Rats with Diabetes Mellitus. Pharmacological
Research, Volume 51(2), pp. 147–152
Ghorbani, A., 2017. Mechanisms of
Antidiabetic Effects of Flavonoid Rutin. Biomedicine & Pharmacotherapy,
Volume 96, pp. 305–312
Harborne, S.P., Ruprecht, J.J.,
Kunji, E.R., 2015. Calcium-Induced Conformational Changes in the Regulatory
Domain of the Human Mitochondrial ATP-Mg/Pi Carrier. Biochimica et
Biophysica Acta (BBA)-Bioenergetics, Volume 1847(10), pp. 1245–1253
Kaur, R., Dahiya, L., Kumar, M.,
2017. Fructose-1, 6-Bisphosphatase Inhibitors: A New Valid Approach for
Management of Type 2 Diabetes Mellitus. European Journal of Medicinal
Chemistry, Volume 141, pp. 473–505
Kumazawa, S., Hamasaka, T.,
Nakayama, T., 2004. Antioxidant Activity of Propolis of Various Geographic
Origins. Food chemistry, Volume 84(3), pp. 329–339
Lalau, J.D., 2010. Lactic
Acidosis Induced by Metformin: Incidence, Management and Prevention. Drug
safety, Volume 33(9), pp. 727–740
Lipinski, C.A., 2004. Lead-and
Drug-Like Compounds: The Rule-of-Five Revolution. Drug Discovery Today:
Technologies, Volume 1(4), pp. 337–341
Lipinski, C.A., Lombardo, F.,
Dominy, B.W., Feeney, P.J., 1997. Experimental and Computational Approaches to
Estimate Solubility and Permeability in Drug Discovery and Development
Settings. Advanced Drug Delivery Reviews, Volume 23(1-3), pp. 3–25
Marcou, G., Rognan, D., 2007.
Optimizing Fragment and Scaffold Docking by Use of Molecular Interaction Fingerprints.
Journal of Chemical Information and Modeling, Volume 47(1), pp. 195–207
Matsuura, T., Chinen, Y.,
Arashiro, R., Katsuren, K., Tamura, T., Hyakuna, N., Ohta, T., 2002. Two Newly
Identified Genomic Mutations in a Japanese Female Patient with Fructose-1,
6-Bisphosphatase (Fbpase) Deficiency. Molecular Genetics and Metabolism,
Volume 76(3), pp. 207–210
Miyata, R., Sahlan, M., Ishikawa,
Y., Hashimoto, H., Honda, S., Kumazawa, S., 2020. Propolis Components and
Biological Activities from Stingless Bees Collected on South Sulawesi,
Indonesia. HAYATI Journal of Biosciences, Volume 27(1), pp. 82–82
Moller, D.E., 2001. New Drug Targets
For Type 2 Diabetes and The Metabolic Syndrome. Nature, Volume 414, pp. 821–827
Pasaribu, A.P., Siddiq, M.F.,
Fadhila, M.I., Hilman, M.H., Yanuar, A., Suhartanto, H., 2017. A Preliminary
Study on Shifting from Virtual Machine to Docker Container for Insilico Drug
Discovery in the Cloud. International
Journal of Technology, Volume 8(4), pp. 611–621
Pratami, D.K., Mun’im, A., Yohda,
M., Hermansyah, H., Gozan, M., Putri, Y.R.P., Sahlan, M., 2019. Total Phenolic
Content and Antioxidant Activity of Spray-Dried Microcapsules Propolis from Tetragonula
Species. In: AIP Conference
Proceedings. Volume 2085(1), p. 020040
Sarian, M.N., Ahmed, Q.U., So’ad,
M., Zaiton, S., Alhassan, A.M., Murugesu, S., Perumal, V., Syed Mohamad, S.N.A.,
Khatib, A., Latip, J., 2017. Antioxidant and Antidiabetic Effects of
Flavonoids: A Structure-Activity Relationship Based Study. BioMed Research International,
Volume 2017, pp. 1–14
Seeberger, P.H., Rademacher, C.,
2014. Carbohydrates as Drugs. Springer International Publishing
Seeliger, D., De Groot, B.L.,
2010. Ligand Docking and Binding Site Analysis with PyMOL and Autodock/Vina. Journal
of Computer-Aided Molecular Design, Volume 24(5), pp. 417–422
Singh, S., Loke, Y.K., Furberg,
C.D., 2007. Thiazolidinediones and Heart Failure: A Teleo-Analysis. Diabetes
Care, Volume 30(8), pp. 2148–2153
Suhartanto, H., Yanuar, A.,
Wibisono, A., Hermawan, D., Bustamam, A., 2018. The Performance of a Molecular
Dynamics Simulation for the Plasmodium falciparum Enoyl-acyl carrier-protein
Reductase Enzyme using Amber and GTX 780 and 970 Double Graphical Processing
Units. International Journal of Technology, Volume 9(1), pp. 150–158
Trott, O., Olson, A.J., 2010.
AutoDock Vina: Improving the Speed and Accuracy of Docking with a New Scoring
Function, Efficient Optimization, and Multithreading. Journal of
Computational Chemistry, Volume 31(2), pp. 455–461
Tsukada, T., Takahashi, M.,
Takemoto, T., Kanno, O., Yamane, T., Kawamura, S., Nishi, T., 2009. Synthesis,
SAR, and X-ray Structure of Tricyclic Compounds as Potent FBPase Inhibitors. Bioorganic
& Medicinal Chemistry Letters, Volume 19(20), pp. 5909–5912
Tsukada, T., Takahashi, M.,
Takemoto, T., Kanno, O., Yamane, T., Kawamura, S., Nishi, T., 2010. Structure-based
Drug Design of Tricyclic 8H-indeno [1, 2-d][1, 3] Thiazoles as Potent FBPase
Inhibitors. Bioorganic & Medicinal Chemistry Letters, Volume 20(3),
pp. 1004–1007
Vinayagam, R., Xu, B., 2015.
Antidiabetic Properties of Dietary Flavonoids: A Cellular Mechanism Review. Nutrition
& Metabolism, Volume 12(1), pp. 1–60
Warren, G.L., Do, T.D., Kelley,
B.P., Nicholls, A., Warren, S.D., 2012. Essential Considerations for using
Protein–Ligand Structures in Drug Discovery. Drug Discovery Today,
Volume 17(23-24), pp. 1270–1281
Wishart, D.S., Knox, C., Guo, A.C.,
Shrivastava, S., Hassanali, M., Stothard, P., Chang, Z., Woolsey, J., 2006.
DrugBank: A Comprehensive Resource for in Silico Drug Discovery and
Exploration. Nucleic Acids Research, Volume 34, pp. D668-72