Cholesterol esterase inhibitory activity of flavonoids ...

930

Asian Pac J Trop Dis 2012; 3(2): 9

Contents lists available at ScienceDirect

Asian Pacific Journal of Tropical Disease journal homepage: www.elsevier.com/locate/apjtd

Document heading

Cholesterol

vitro studies

doi:

襃

2013 by the Asian Pacific Journal of Tropical Disease. All rights reserved.

esterase inhibitory activity of flavonoids using in silico and in 1*

2

Thirumalaisamy Sivashanmugam , Soundararajan Muthukrishnan , Muthuswamy Umamaheswari 1 1 1 1 Asokkumar , Varadharajan Subhadradevi , Puliyath Jagannath , Arumugam Madeswaran

1

, Kuppusamy

Department of Pharmacology, College of Pharmacy, Sri Ramakrishna Institute of Paramedical Sciences, Coimbatore, Tamil Nadu, India

1

Department of Pharmacology, Sankaralingam Bhuvaneshwari College of Pharmacy, Sivakasi, Tamil Nadu, India

2

PEER REVIEW

ABSTRACT

Peer reviewer D r. R . S ambathkumar, P rofessor, Department of Pharmaceutics, J.K.K. N atarajah C ollege of P harmacy, Komarapalayam, Tamil Nadu, India. Tel: 98427 79911 E-mail: [email protected]

Objective: To investigate the cholesterol esterase inhibitory activity of flavonoids using in silico and in vitro studies. Methods: In this perspective, flavonoids like catechin, chalcone, 4-hydroxy coumarin, morin and quercetinwere selected. Gallic acid, a known cholesterol esterase inhibitor was used as the standard. In silico docking studies were carried out using AutoDock 4.2, based on the Lamarckian genetic algorithm principle and in vitro cholesterol esterase inhibitory activity was carried out. In the docking studies, three important parameters like binding energy, inhibition constant and intermolecular energy were determined. Results: The results showed that all the selected flavonoids showed binding energy ranging between -6.98 to -5.06 kcal/mol, when compared with that of the standard (-4.11 kcal/mol). Inhibition constant (7.69 to 193.95 µmol/L) and intermolecular energy (-7.87 to -6.85 kcal/mol) of the flavonoids also coincide with the binding energy. In the cholesterol esterase assay, IC50 value of chalconewas found to be (18.30依0.31) µg/ mL, whereas that of gallic acid was (759.69依31.56) µg/mL. All the remaining compounds exhibited IC50 values ranging from (32.90依0.06) µg/mL to (166.35依4.10) µg/mL. Conclusions: All the selected flavonoids contributed cholesterol esterase inhibitory activity, because of its structural properties. These molecular docking analyses could lead to the further development of potent cholesterol esterase inhibitors for the treatment of diabetes.

Comments T his is a good study in which the

authors evaluated the flavonoids for its anti-diabetic activity using in silico and in vitro analysis. The results are quite interesting and suggested that the potential compounds for the development of anti-diabetic drugs. (Details

on Page )

KEYWORDS Binding energy, Inhibition constant, Enzyme kinetics, Docking studies, AutoDock tools

1. Introduction Obesity is becoming one of the greatest threats to global

health in this millennium, with more than 1 billion overweight adults and of those, at least 300 million are clinically obese. The obesity market reached US$ 3.7 billion by 2008 and has been predicted to reach US$ 6.1 billion by 2015. The mushrooming market for these drugs and the vast sum of money at stake guarantee that research in this therapeutic area will not slow down within the predictable future[1]. Overweight and obesity are currently on the increase in lowand middle-income countries, particularly in urban settings. Around 35 million overweight children are living in developing countries and 8 million in developed countries[2]. Obesity is *Corresponding author: Thirumalaisamy Sivashanmugam, M. Pharm., Lecturer, D epartment of P harmacology, C ollege of P harmacy, S ri R amakrishna I nstitute of Paramedical Sciences, Coimbatore-641 044, Tamil Nadu, India. Tel: +91 9994981368 E-mail: [email protected]

resulting from an energy imbalance caused by increased ratio of caloric intake to energy expenditure and the excess body fats thus formed are stored in body. Obesity is also known to be risk factor for the development of metabolic disorders, dyslipidemia and atherosclerosis and type-2 diabetes. In recent years, there has been a great increase in the use of herbal medicines for the treatment of obesity[3]. Overweight and obesity are the fifth leading risks for global deaths. At least 2.8 million adults die each year as a result of being overweight or obese[4]. Cholesterol esterase (CEase) is proposed to contribute to the availability of free cholesterol by catalyzing the hydrolysis of cholesterol esters and contribute to the formation of lysolecithin-containing micelles, which are the vehicles for efficient absorption of cholesterol, by catalyzing the hydrolysis Article history: Received 3 Feb 2013 Received in revised form 9 Feb, 2nd revised form 13 Feb, 3rd revised form 17 Feb 2013 Accepted 28 Mar 2013 Available online 28 Apr 2013

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Thirumalaisamy Sivashanmugam et al./Asian Pac J Trop Dis 2013; 3(2):

of lecithin. Inhibitors of pancreatic CEase have the potential to modify cholesterol metabolism at multiple sites. Pancreatic CEase, an enzyme, which is also known as bile salt-activated lipase, is responsible for the hydrolysis of various substrates, including dietary cholesterol esters, fat-soluble vitamins, triglycerides, and phospholipids. CEase is secreted from vertebrate pancreas into the intestinal track and activated by primary bile salts. It is present in few mammals including humans[5]. CEase is necessary for the full absorption of cholesterol across the intestinal mucosa into the blood stream. It is one of the risk factor for atherosclerosis and ischemic heart disease[6]. CEase belongs to α/ß-hydrolase fold family. The active site includes both the catalytic triad (Ser-194, Asp-320, His-435) and oxyanion hole (Gly-107, Ala-108, Ala -195) residues[5]. Docking is carried out using one of several search methods. The most efficient method is a Lamarckian genetic algorithm (LGA), but traditional genetic algorithms and simulated annealing are also available. For typical systems, AutoDock is run several times to give several docked conformations, and analysis of the predicted energy and the consistency of results is combined to identify the best solution. AutoDock tools include a number of methods for analyzing the results of docking simulations, including tools for clustering results by conformational similarity, visualizing conformations, visualizing interactions between ligands and proteins, and visualizing the affinity potentials created by Auto Grid[7]. Flavonoids are a large group of non-nutrient compounds naturally produced from plants as part of their defense mechanisms against stresses of different origins. They emerged from being considered an agricultural oddity only after it was observed that these compounds possess a potential protective function against several human degenerative diseases[8]. Flavonoids possess various biological activities like, antiamoebic activity, antiinflammatory, antivascular activity, anticoagulant, antimetastatic, anticancer, antioxidants and antispasmodic[9-15]. 2. Materials and methods 2.1. Enzyme and chemicals Porcine pancreatic CEase (C26745) and p-nitro phenyl butyrate

(pNPB), catechin, were purchased from the Sigma Aldrich, USA.

Acetonitrile, taurocholate, chalcone, were purchased from Loba chemicals, Mumbai. Sodium dihydrogen phosphate was purchased from Qualigens Fine Chemicals, Mumbai. Sodium chloride was purchased from SD Fine Chemicals, Mumbai.

morin, rutin, quercetin, 4-hydroxy coumarin were purchased from HiMedia Mumbai. 2.2. In silico docking studies We employed the LGA for ligand conformational searching,

which is a hybrid of a genetic algorithm and a local search algorithm. This algorithm first builds a population of individuals (genes), each being a different random conformation of the docked molecule. Each individual was then mutated to acquire a slightly different translation and rotation and the local search algorithm then performs energy minimizations on a userspecified proportion of the population of individuals. The individuals with the low resulting energy were transferred to the next generation and the process was then repeated. The algorithm is called Lamarckian because every new generation of individuals is allowed to inherit the local search adaptations of their parents. An extended PDB format, termed as PDBQT file was used for coordinate files which includes atomic partial charges. AutoDock Tools was used for creating PDBQT files from traditional PDB files[16]. T he preparation of the target protein 1 F 6 W with the AutoDock Tools software involved adding all hydrogen atoms to the macromolecule, which is a step necessary for correct calculation of partial atomic charges. Gasteiger charges were calculated for each atom of the macromolecule in AutoDock 4.2 instead of Kollman charges which were used in the previous versions of this program. Three-dimensional affinity grids of size 277 Å× 277 Å× 277 Å with 0.6 Å spacing were centered on the geometric center of the target protein and were calculated for each of the following atom types: HD, C, A, N, OA, and SA, representing all possible atom types in a protein. AutoDock was run several times to get various docked conformations, and used to analyze the predicted docking energy. The binding sites for these molecules were selected based on the ligand-binding pocket of the templates[18]. AutoDock Tools provided various methods to analyze the results of docking simulations such as, conformational similarity, visualizing the binding site and its energy and other parameters like intermolecular energy and inhibition constant. For each ligand, ten best poses were generated and scored using AutoDock 4.2 scoring functions[19]. 2.3. In vitro CEase enzyme inhibitory activity Stock solution of CEase (19.5 ng/mL) and taurocholate (12 mmol/L) were prepared by sodium phosphate buffer of pH 7.0. Stock solution of pNPB (200 µmol/L), extracts and standard of different concentration (10-1280 µg/mL) were prepared by using acetonitrile (6%). A final volume of 1 mL was taken into a cuvette containing 430 µL of assay buffer, 500 µL of taurocholate (TC) solution. A total of 40 µL of acetonitrile, 10 µL of pNPB solution and 10 µL of an inhibitor solution were added and thoroughly mixed. Incubation for 2 min at 25 °C, the reaction was initiated by adding 10 µL of the enzyme solution. The absorbance was measured at 405 nm against blank. Percentage inhibition was calculated by using the formula:

[

]

Enzyme activity with inhibitor CEase inhibition % I= 1伊100 Enzyme activity without inhibitor

932


Uninhibited enzyme activity was determined by adding acetonitrile instead of the inhibitor solution. Gallic acid was used as reference standard[20, 21].

2.4. Enzyme kinetics To determine the mode of inhibition by most active flavonoids, Lineweaver-Burk plot analysis was performed. The assay was

carried out in the presence or absence of the flavonoids with varying concentration of pNPB (50, 100, 150, 200 and 250 µmol/ L) as the substrate, using CEase assay method. The mode of inhibition was analyzed along with positive control Gallic acid. The mode of inhibition was determined using the LineweaverBurk plot. Enzyme kinetics calculation and draw a LineweaverBurk plot is done in GraphPad Prism 5 Software[17].

In silico docking study, was carried out to identify the inhibiting potential of selected flavonoids against CEase enzyme. In this study, 5 different flavonoids were selected for the in silico docking studies. The docking studies were performed by the use of AutoDock4.2. In the docking studies, if a compound shows lesser binding energy compared to the standard it proves that the compound has higher activity[22]. In Figure 2, the flavonoid ligands like catechin, chalchone, 4hydroxycoumarin, morin, quercetin and gallic acid were built using ChemSketch and optimized using “prepare ligands” in the AutoDock 4.2 for docking studies.

2.5. In silico docking In silico docking study, was carried out to identify the inhibiting potential of selected flavonoids against CEase enzyme. In this study, 5 different flavonoids were selected for the in silico docking studies. The docking studies were performed by the use of AutoDock 4.2. In the docking studies, if a compound shows lesser binding energy compared to the standard, it proves that the compound has higher activity[21]. 2.6. Statistical analysis Data collected from the above specified studies were subjected to one-way ANOVA , followed by D unnet’s comparison by using Graph pad prism 5. Version 5.01.

3. Results Crystal structure of CEase enzyme was downloaded from the Brookhaeven protein data bank (Figure 1).

Figrue 2. The optimized ligand molecules. 1: catechin; 2: chalcone; 3 and 4: hydroxy coumarin; 4: morin; 5: quercetin; 6: gallic acid.

Lead optimization of the selected compounds was done by computation of druglikeness properties. The druglikeness scores of the compounds were evaluated with the help of Lipinski’s rule. The various parameters of the ligands like molecular formula, molecular weight, partition coefficient, hydrogen bond donor, hydrogen bond acceptor andtopological polar surface area were tabulated in Table 1.

3.1. Docking orientations of flavonoids The binding mode of the flavonoids with in the active site of CEase has been analyzed. Common and critical binding sites of the compounds were studied and found to be Trp-227, Ala117, Leu-124, Ser-194 and Phe-324 (Figure 3). These aminoacid

residues were largely found in the binding sites of almost all the compounds. As shown in Table 2, flavonoids showed binding energy ranging between -6.98 to -5.06 kcal/mol. Chalcone showed better binding energy -6.98 kcal/mol than the standard gallic acid (-4.11 kcal/mol). All the selected flavonoids had showed binding energy compared to that of standard.

Table 2 Docking parameters of compounds using human cholesterol esterase enzyme (PDB code 1F6W). Ligands 4-hydroxy coumarin

Figure 1. Cholesterol esterase enzyme from Brookhaeven protein data bank (1F6W).

Catechin Chalcone Morin Quercetin Gallic acid

Binding energy (kCal/mol)

-5.31 -6.25 -6.98 -5.44 -5.06 -4.11

Inhibitory

constant (µmol/L) 127.48 26.38 7.69 103.32 193.95 757.77

Intermolecular

energy

(kCal/mol)

-5.61 -8.04 -7.87 -7.23 -6.85 -6.19

933


100

-0.01 0.00

Compound

Catechin Chalcone 4-Hydroxy coumarin Morin Quercetin A

GIY 221 ALA400

SER225

VAL222

LEU222 XAL228

ALA223

Pubchem ID

Molecular weight

Molecular

9064

290.268 06

C15H14O6 C15H12O C9H6O3 C15H10O7 C15H10O7

208.255 18

637760

54682930

162.142 14

5280343

302.235 7

302.235 7

5281670

GLY217

ALA195

LEU190

SER209 PRO300 LYR304 THR204 LEJ202 LEU205 GLN203

D TYR125

ALE439

ALA436

HIS435

ILE213

ALA108 GLY106 194 XLO198 SER VER220 ALA195

PHE393

100

0.03

-0.01 0.00

C

Control Standand

200

100

E

0.01 0.02 1/pNPB

-0.01 0.00 0.01 0.02 0.03 1/pNPB

0.03

Hydrogen bond

Hydrogen bond

5

6

LEU392

acceptor

0

F

7

5

7 MET281

PHE324

PHE351

PHE324

GLU193

TYR105 ALA117

TPR227

LEU282

VML285

LEU392 TPR227

HIS435

ASP328

ASP437 ASP438 ALA436

SER194

surface area 110.0 17.1 75.6 127.0 127.0

3

5

MPO280

Topological polar

1

1

ALA108

PHE393

GLU388

PHE393 LEU392

300

1/V

1/V

0.02

100

Control Quercetin

donor

TPR227 LEU282 MET281

HIS435

ALA195

300

200

Hydroxycoumarim

-0.01 0.00 0.01 0.01 0.03 1/pNPB

C

F

PHE109

SER194

LEU124

LYS445

ALA117

TYR125

ILE439 GLN440

GLY107 GLY106

GLY107

TYR105

1/pNPB

Partition coefficient 0.4 3.1 1.3 1.5 1.5

ALA108

E

PHE324

0.01

D

Control

4-

200

Figure 4. Lineweaverburk plot analysis of the ligands. A : catechin; B : chalcone; C : 4 -hydroxy coumarin; D : morin; E : quercetin; F: standand.

SER194

ILE323

-0.04 -0.02 0.00 0.02 0.04 1/pNPB

VAL285

ALA216

ALA198 SER201 VAL200

0.03

1/V

-0.01 0.00

B

50

Control Morin

100

B

SER218 ILE217 LYR312

0.02

200

formula

(g/mol)

1/pNPB

300

3.3. Enzyme kinetic studies T he enzyme kinetic studies were performed using Lineweaver Burk plot analysis (Figure 4). Table 1 Ligand parameters.

0.01

150

100

A

300

Control Chalcone

200

1/V

1/V

All the selected flavonoids exhibited a dose dependent inhibition of CEase enzyme activity. It is proved that inhibition of cholesterol esterase was measured by UV spectroscopy. All the compounds demonstrated CEase inhibitory activity at a concentration of 100 µg/mL, showing an inhibition greater than 50%. Their IC50 values were shown in Table 3.

250

Control Catechin

300 200

1/V

3.2. In vitro cholesterol esterase inhibitory activity

ASN122 PHE119

ASN121

LEU124

TYR125

Figure 3. Binding orientations of cholesterol esterase enzyme (1F6W) with the ligands. A: catechin; B: chalcone; C: 4-hydroxy coumarin; D: morin; E: quercetin; F: gallic acid.

Table 3 In vitro xanthine oxidase inhibitory activity of the selected compounds. Compounds Catechin Chalcone

Percentage inhibition (mean依SEM)

10

20

40

Concentration (µg/mL)

80

18.80依0.40 40.59依1.21 55.12依0.71

67.31依0.53

4-hydroxy coumarin 12.24依1.62 21.14依0.95 36.02依0.60

41.65依1.80

19.27依0.42 28.64依1.12 39.66依0.95

44.93依0.42

Morin Quercetin Gallic acid

32.98依1.84 52.89依0.88 66.49依0.76 9.90依1.42 17.39依1.80 33.80依1.52 5.44依2.87 14.93依0.73 27.70依0.84

320

78.79依0.30

55.82依0.71

70.00依0.71

74.22依0.51

81.60依0.30

44.81依0.92

58.28依0.71

34.62依1.42

39.42依0.71

Values are mean依SEM (n=3), Pcatechin>morin>4hydroxycoumarin>quercetin>gallic acid. The in vitro results coincide with the virtual screening analysis which further proves the inhibitory potential of the flavonoids against the enzyme. In the selected flavonoids chalcone, morin and quercetin were found to be uncompetitive inhibitors of CEase due to their increase in substrate concentration and larger Km value in the Lineweaver Burk plot analysis. The remaining flavonoids such as catechin, 4-hydroxycoumarin and gallic acidwere found to be noncompetitive inhibitors of CEase in the Lineweaver Burk plot analysis.

Binding energy proves that flavonoids consist of potential CEase inhibitory binding sites similar to that of the standard. In addition, two other parameters like inhibition constant and intermolecular energy were also determined. Inhibition constant is directly proportional to binding energy. All the selected

compounds had lesser inhibition constant when compared to the standard. Thus, the potential CEase inhibitory activity of the flavonoids was compared with the caffeine. The results of the present study clearly demonstrated the CEase inhibitory activity of the selected flavonoids by virtual screening analysis and in vitro assay. Virtual screening analysis is actually an added advantage to screen the CEase inhibition. The flavonoids such as chalcone and catechin showed excellent activity when compared to the standard gallic acid, is interesting and merits for its further characterization. Further investigations on the above compounds and in vivo studies are necessary to develop potential chemical entities for the prevention and treatment of diabetes. Conflict of interest statement We declare that we have no conflict of interest. Comments Background D rug design is an inventive process of finding new medications based on the knowledge of the biological target. Drug discovery and development is an intense, lengthy and an interdisciplinary endeavor. It is a linear, consecutive process that starts with target and lead discovery, followed by lead optimization and pre-clinical in vitro and in vivo studies to determine if such compounds satisfy a number of pre-set criteria for initiating clinical development.

Research frontiers Molecular docking studies are gaining importance in the new drug discovery process as a tool for high through put screening. In order to understand the mechanism of ligand binding and to identify potent cholesterol esterase molecular docking and virtual screening analyses were carried out for flavonoids. Related reports Madeswaran et al. (2012), were studied In silico docking studies of lipoxygenase inhibitory activity of commercially available flavonoids. In this study, the authors had focused the cholesterol esterase inhibitory activity of flavonoids for the treatment of diabetes. Innovations & breakthroughs The structural models of the ligands in cholesterol esterase binding sites may facilitate further development of more potent cholesterol esterase inhibitory agents for treatment of diabetes.


Applications In this study, flavonoids were analyzed against cholesterol esterase for their anti-diabetic activity. This research highlights the information about the structural models of the flavonoids in the cholesterol esterase binding sites, which may facilitate further development of more potent cholesterol esterase inhibitory agents. Peer review This is a good study in which the authors evaluated the flavonoids for its anti-diabetic activity using in silico and in vitro analysis. The results are quite interesting and suggested that the potential compounds for the development of antidiabetic drugs. References [1] Birari RB, Bhutani KK. Pancreatic lipase inhibitors from natural sources: unexplored potential. Drug Discov Today 2007; 12: 879-888. [2] Allison DB, Fontaine KR, Manson JE, Stevens J, VanItallie TB. Annual deaths attributable to obesity in United States. J Am Med Assoc 1999; 282: 1530-1538. [3] Ramgopal M, AttitallaIH, Avinash P, Balaji M. Evaluation of anti-lipidemic and anti-bbesity efficacy of Bauhinia purpurea Bark extract on rats fed with high fat diet. Acad J Plant Sci 2010; 3: 104-107. [4] Barness LA, OpitzJ M, Gilbert-Barness E. Obesity: genetic, molecular, and environmental aspects. Am J Med Genet A 2007; 143: 3016-3034. [5] John S, Thangapandian S, Sakkiah S, Lee KW. Discovery of potential pancreatic cholesterol esterase inhibitors using pharmacophore modelling, virtual screening and optimization studies. J Enzyme Inhib Med Chem 2010; 1: 1-11. [6] Sutton LD, Lantz JL, Eibes T, Quinn DM. Dimensional mapping of the active site of cholesterol esterase with alkylboronic acid inhibitors. Acta Biochim Biophys Sin 1990; 1041: 79-82. [7] Morris GM, Goodsell DS, Pique ME, Lindstrom WL Huey R, Forli S. AutoDock version-4.2 User guide of 2010. [Online] Available from: http://autodock.scripps.edu. [Accessed on 2011 Jul 12]. [8] Galluzzo P, Marino M. Nutritional flavonoids impact on nuclear and extraneuclear estrogen receptor activites. Genes Nutr 2006; 1: 161-176. [9] Budakoti A, Bhat AR, Azam A. Synthesis of new 2-(5substituted-3-phenyl-2-pyrazolinyl)-1,3-thiazolino[5,4-b] quinoxaline derivatives and evaluation of their antiamoebic activity. Eur J Med Chem 2009; 44: 1317-1325. [10] L iu B , R aeth T , B euerle T , B eerhues L . A novel

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