INTRODUCTION:

The quantity of free radicals or reactive oxygen species (SOR) that increases in the body has a role in the occurrence of degenerative diseases. Free radicals can damage blood vessel endothelial cells and cause various clinical conditions such as kidney disorders and increase the risk of coronary heart disease and stroke [1]. Free radicals that react with cell membrane lipids can cause the formation of lipid peroxide, which is a detrimental effect on the body if in excessive amounts [2] . Its presence which is still needed by the body causes the importance to control the amount of SOR. Superoxide dismutase, catalase, and glutathione peroxidase are enzymes that function as antioxidants produced by the human body itself.

Antioxidants were generally used as additives in food and pharmaceutical compounds to protect the oxidation process. At present, the most commonly used antioxidants are butylated hydroxyanisole (BHA), butylated hydroxytoluene (BHT), propyl gallate, and tert-butyl hydroquinone. However, BHA and BHT are thought to be responsible for liver damage and carcinogenesis [3]. Therefore, the use of natural antioxidants is more preferred [4–6]. In general, many food supplements in the community contain natural antioxidants. These food supplements generally come from natural ingredients such as vitamin A, vitamin C, vitamin E, beta carotene, zinc, manganese, and selenium.

Curcumin is a natural source of antioxidants [7]. Curcumin was reported to have potential as an anti-inflammatory and also have the ability to inhibit lipid peroxidation in several animal models [8]. Curcumin is scavenging of various reactive oxygen species, including hydroxyl radicals [8] and nitrogen dioxide radicals [9]. Curcumin is a non-polar antioxidant. Curcumin places itself inside the cell membrane, where it can block lipid radicals and become phenoxyl radicals. Phenoxyl radicals have become more polar than curcumin, causing it to move to the membrane surface, which can be regenerated by polar antioxidants such as ascorbic acid [10]. Similar to curcumin, mono-ketone analogs of curcumin (figure 1) were reported to have lipid peroxidation inhibition [11], cyclooxygenase inhibition and antibacterial activity [12].

Figure 1. Structure of mono-ketone analogs of curcumin [12]

Mono-ketone analogs of curcumin were known to have much biological activity, but there are still many shortcomings such as low water solubility, chemical and metabolic stability, and relatively poor bioavailability in vivo [12,13]. The structure of mono-ketone analogs of curcumin has been modified to obtained new analogs that have not only better biological activity, but also better physical and chemical properties. One of the more effective and efficient new drug discovery techniques is the Quantitative Structure-Activity Relationship (QSAR) approach. QSAR approaches can be carried out to get a better understanding of chemical and biological processes at the molecular level [14]. In the QSAR Study, between molecular structure and biological activity assumed that have a quantitative relationship. In the process, the QSAR studies use observation and calculation data (from docking or quantum chemistry, and so on.) which can correlate with experimental data [15]. Thus the drug may be designed to obtained new compounds that are more potent. This study aims to design mono-ketone analogs of curcumin compound and determine its lipid peroxidation inhibition.

MATERIALS AND METHODS:

Data set:

The material in this study was structure data of mono-ketone analogs of curcumin and its lipid peroxidation inhibition activity obtained from the literature as shown in table 1. lipid peroxidation inhibition activity were determined as pIC₅₀ (negative log of the IC₅₀in Molar) explaining the ability of each compound in lipid peroxidation inhibition.

Table 1. Data sets of compounds with Lipid peroxidation inhibition activity (16)

Comp.	Substituent					pIC₅₀ LPO Inh.
Comp.	R₁	R₂	R₃	R₄	R₅	pIC₅₀ LPO Inh.
A0	-H	-H	-OH	-H	-H	4.17
A1	-H	-OCH₃	-OH	-H	-H	5.05
A11	-H	-CH₃	-OH	-CH₃	-H	5.55
A12	-H	-C₂H₅	-OH	-C₂H₅	-H	5.70
A14	-H	t- CH₃	-OH	t- CH₃	-H	4.36
B1	-H	-OCH₃	-OH	-H	-H	5.19
B15	-H	-OCH₃	-OH	-OCH₃	-H	6.05
B16	-H	-Cl	-OH	-Cl	-H	4.83
C11	-H	-CH₃	-OH	-CH₃	-H	5.89

Chemicals:

3,4-dimethoxybenzaldehyde, 3-ethoxy-4-hydroxybenzaldehyde, 3-bromo-4-methoxybenzaldehyde, cyclohexanone, tetrahydrofuran, Hydrochloric acid, ethanol, ethyl acetate, sodium hydroxide, methanol, buffer Tris-HCl Ultrol^® (pH 7.4), 2-thiobarbituric acid (TBA), butylated hydroxytoluene (BHT), trichloroacetic acid (TCA), Ferrous sulfate, Ascorbic Acid acquired from Sigma-Merck. All other chemicals used were analytical grade and acquired from Sigma–Aldrich or Merck. Rat (Sprague-Dawley) Microsomes was obtained from Thermo Fisher Scientific.

Instrument:

PC with Intel Core i3-6006U 2.0 GHz, 4GB and Windows 7 as the operating system. AM-1 quantum mechanical calculations and descriptors were performed using the Molecular operating environment (MOE) version 2018.0101. BuildQSAR was used to generate the QSAR equation best model. BUCHI Melting Point B-540 with a temperature gradient at 5°C/min was used for the melting point test. The purity of the synthesized compound was measured using HPLC Elite La-Chrome^®. JEOL^® spectrophotometer 500 MHz was used to measure the ¹H-NMR Spectrum.

Procedure:

Molecular modelling:

MOE 2018.01.01 software used in molecular modeling studies. Semi-empirical AM-1 in MOPAC MOE was used to optimize the structure of compounds.

Descriptor calculation:

Descriptor values were obtained from a single-point calculation in MOE from an optimized structure. All molecular descriptors are available in 2D and i3D MOE databases selected for further QSAR studies.

Statistical analysis performed on each descriptor value from the data set using GA-MLRA technique in BuildQSAR of the lipid peroxidation inhibitory activity expressed as pIC₅₀ [17]. he best equation model obtained was used to predict the IC₅₀ values of the inhibitory activity of lipid peroxidation calculations for each compound. The selection of the best equation model considers several statistical parameters. This approach makes it possible to choose the best model with the following characteristics, such as the highest regression coefficient (r), highest Fisher coefficient (F), and lowest standard deviation [12,18]. The best equation model was validated using leave-one-out cross-validation (LOOCV) to determine its ability and robustness in predicting as has been confirmed by the quadratic validation coefficient (Q2) and Predictive Error Sum of Squares (sPRESS).

Procedure synthesis of A103, A116, A153:

In each round bottom flask added 6.018mmol of 3-ethoxy-4-hydroxybenzaldehyde and 3.009mmol of cyclohexanone; 4.650mmol of 3-Bromo-4-methoxybenzaldehyde and 2.325mmol of cyclohexanone; 6.018mmol of 3, 4-dimethoxybenzaldehyde and 3.009mmol of cyclohexanone. 2ml of THF and 0.2ml of concentrated hydrochloric acid were added to each flask and stirred at room temperature for 2 hours. Then, the temperature raised to 40-50^oC, and stirring was continued for 8 hours until the reaction was complete. The crude product was washed out by ethanol: cold water (1: 1) then filtered by Buchner. The second washed for residue was performed by different ratio of ethanol and cold water (3: 2) until pH 7-8 reached out. The residue was filtered and dried in the oven. Recrystallization performed by dissolving the residue in acetone, then cold water was added until a precipitate formed. TLC and melting point tests were carried out to find out the purity of product qualitatively.

Purity test by HPLC:

Analysis purity test of the product synthesis using HPLC, as a comparison used starting material (aldehydes). Synthesis products and starting material analyzed at 100ppm concentration. Observations determined at UV wavelength 350nm and a mobile phase of acetonitrile: water (80:20) with a flow rate of 1 ml/ min, 100 psi pressure, and 20µL volume injection in column C₁₈.

Table 2. HPLC purity test results

Compound

Retention time (min)

Area (%)

A103

Starting material of A103

1.81

1.36

99.284

100.00

A116

Starting material of A116

6.24

1.68

100.00

47.555

A153

material of A153

2.31

2.18

99.235

79.230

The different retention times of each compound indicate the real yield of the synthesized compound. So it known that each compound could be adequately separated using the HPLC system. The results showed that the synthesized compound was pure, which was confirmed using the respective starting material.

Scheme 1. Reagent and condition of synthesis: a) THF and HCl; 8h and 50^oC

2, 6-bis-(3’-ethoxy, 4’-hydroxybenzylidene)- cyclohexanone (A103):

Greenish yellow powder, yield 57.84%, mp 156.1-157.8°C; Rf=0.3, ethyl acetate:CHCl3(1:20); IR γ (cm-1) (KBr): 3368.86 -OH bonded, 2979.35 =C-H stretch aromatic, 2937.47 -C-H stretch aliphatic, 1595.93-C=C stretch aliphatic, 1509,24-C=O stretch αβ,α’β’-unsat, 1458.76 -C=C stretch aromatic, 1477.30-C-H bending aliphatic, 1282.37-C-O stretch, 1213.24 -C-CO-C coupled stretch and bending, 1161.497-C-OH stretch; MS (EI-MS, m/z )394 [M++2H]; 61 (base line); 1 H-NMR (500 MHz, ppm, CDCl3): δ 1.450 (6H, t, C1,23, CH3 aliphatic), δ 1.814 (2H, qui, H12, CH2 cyclohexanone); δ 2.912 (4H, qui, H11,13, CH2 cyclohexanone); δ 4.142 (4H, q, H2,23, CH aliphatic); δ 5.869 (2H, s, H9,16, CH aliphatic); δ 6.940 (2H, d, J=8Hz, H5,19, Ar-CH); δ 6.956 (2H, d, J=1.5Hz, H8,22, Ar-CH); δ 7.054 (2H, dd, J1=1.5Hz J2=8Hz, H6,18, Ar-CH); δ 7.702 (2H, s, Ar-OH).

2, 6-bis-(3'-bromo, 4'-methoxybenzylidene)-cyclohexanone (A116):

Yellow crystal, yield 62.76%, mp 182.1-182.5 oC, Rf=0.58, ethyl acetate : n-hexane (1:9); IR γ (cm-1) (KBr): 2939.52 =C-H stretch aromatic, 2839.22 -C-H stretch aliphatic, 1658.78 -C=C stretch aliphatic, 1589.34 -C=O stretch αβ,α’β’-unsat, 1496.76 -C=C stretch aromatic, 1288.45 -C-CO-C coupled stretch and bending, 1157.29 -C-O-C stretch, 551.41 C-Br stretch; MS (EI-MS, m/z): 492 [M+] (100%); 1H-NMR (500 MHz, CDCl3): δ 1.807 (2H, qui, C11, CH2 cyclohexanone); δ 2.887 (4H, qui, C10,12, CH2 cyclohexanone), δ 3.911 (3H, s, C1,22, CH aliphatic), δ 6.914 (2H, d, J=9Hz C3,20, CH aliphatic); δ 7.389 (2H, dd, J1=J2=2Hz, C4,21 Ar-CH); δ 7.647 (2H, s, C8,15, Ar-CH); δ 7.672 (2H, d, J= 2Hz, C6,17 Ar-CH).

2, 6-bis-(3', 4'-dimethoxybenzyllidene)-cyclohexanone (A153):

Yellow powder, yield 42.02%, mp 149.7-151.6 oC, Rf=0.23, DCM : n-hexane (2:1); IR γ (cm-1) (KBr): 2931.42 =C-H stretch aromatic, 2837.33 -C-H stretching aliphatic, 1650.70 C=C stretching aliphatic, 1595.85 C=O stretch αβ,α’β’-unsat, 1458.18 C=C stretch aromatic, 1334.92 C-H bending aliphatic, 1285.56 C-CO-C coupled stretch and bending, 1139.51 C-O-C stretch; MS (EI-MS, m/z): 394 [M++2H]; 131 (base line); 1H-NMR (500 MHz, CDCl3): δ 1.795 (2H, qui, C12, CH2 cyclohexanone); δ 2.902 (4H, qui, C11,13, CH2 cyclohexanone), δ 3.864 (12H, s, C1,2,23,24, CH aliphatic), δ 6.860 (2H, d, J=8.5Hz, C8,19, Ar-CH); δ 6.971 (2H, d, J=2.5Hz, C5,22, Ar-CH); δ 7.065 (2H, dd, J1=J2=2Hz, C7,18, Ar-CH); dan δ 7.702 (2H, s, C9,16, CH aliphatic).

Determination of lipid peroxidation inhibition:

The microsomes used in this assay obtained from GIBCO^®. Microsomes extracted from the liver of Sprague-Dawley strain have 20mg/ml concentration. Preparation of reagent was carried out by dissolving Butylated hydroxytoluene (BHT) 1.5mg/ml in absolute ethanol, 2-Thiobarbituric acid (TBA) 41.6mg/10ml in TCA-HCl solution. The TBA-TCA-HCl-BHT reagent made in ethanol (10: 1). Ascorbic acid and FeSO₄ made in 200μM and 10mM final concentration, respectively. Test compounds prepared by dissolving in DMSO. Determination of lipid peroxidation inhibition was carried out by adding 30μl of test compounds (final concentrations of 8.0, 4.0, 2.0, 1.0, 0.5μM) and 30μl of microsomes (final concentration of 2mg/ml) then incubated at 37^oC for 5 minutes in Tris-HCl buffer 50 mM, pH 7.4). Ascorbic acid (0.5ml, 200μM) which previously neutralized with KOH, was added to the mixture. The reaction begins with the addition of FeSO₄ (0.5ml, 10μM), then incubated at 37^oC for 60 minutes. The reaction stopped by adding 2ml of cold TBA-TCA-HCl- BHT solution. The mixture heated at 80^oC for 15 minutes, then centrifuged at 4000rpm for 10 minutes. The results measured at 535nm wavelength.

RESULT AND DISCUSSION:

Result of QSAR studies:

QSAR studies performed on lead compounds that reported have lipid peroxidation inhibitory activity. Eighty descriptors selected in this study from 2D and i3D molecular databases available in the MOE database. The descriptors selected were intended to provide a suitable physical and chemical properties of the compound. Several descriptors selected in the QSAR studies, as shown in table 3.

Table 3. List of several descriptor used in QSAR studies

Symbol	Descriptor
Apol	Sum of Polarizability
logP(o/w)	Partition coefficient in octanol / water
mr	Molar Refractivity
vdw-area	Van der waals surface area
vdw-volum	Van der waals volume
AM1_dipole	Dipole moment
AM1_E	Total Energy
AM1_Eele	Electronic energy
AM1_HF	Heat of formation
AM1_HOMO	Energy of the highest occupied molecular orbital
AM1_IP	Ionization potential
AM1_LUMO	Energy of the lowest unoccupied molecular orbital
ASA	Water accessible area
ASA_H	Total hydrophobic surface area
vsurf_A	Amphiphilic moment
vsurf_CP	Critical packing parameter
vsurf_CW	Capacity factor
vsurf_D	Hydrophobic volume
vsurf_EDmin	Lowest Hydrophobic volume
vsurf_EWmin	Lowest Hydrophilic energy
vsurf_G	Surface globularity
vsurf_HB	H-bond donor capacity
vsurf_HL	Hydrophilic-lipophilic balance
vsurf_ID	Hydrophobic integy moment
vsurf_IW1	Hydrophilic integy moment
vsurf_R	Surface rugosity
vsurf_S	Interaction field area
vsurf_V	Interaction field volume
vsurf_W	Hydrophilic volume
vsurf_Wp	Polar volume

Descriptor calculations were performed on an optimized structure using the AM-1 semi-empirical method with a convergence/gradient limit of 0.01 RMS Kcal/mol/ A^2. QSAR studies of mono-ketone analogs of curcumin with the AM-1 method were reported to provide better analytical results as antioxidant and antibacterial compared to PM3 method [12,19].

In Table 4, the best statistical parameter values shown in model 1. The model has the most significant r (0.998), and the largest F (343.729) values, the smallest standard deviation (s) is 0.058. The cross-validation value also has shown a first statistical parameter where the Q2 (0.987) value was the highest and had the lowest sPRESS (0.094) value compared to other models. Tables 5 and 6 are the best equation models used in designing mono-ketone analogs of curcumin as antioxidants.

Table 5. The best equation model to calculated calculation-value of lipid peroxidation inhibition

Equation: pIC₅₀= + 4.2153 (± 0.4162) AM1_HOMO + 19.9814 (± 3.2287) vsurf_CW6 - 3.1153 (± 0.6332) vsurf_ID2 + 42.3321 (± 3.7490)
Comp.	AM1_HOMO	vsurf_CW6	vsurf_ID2	pIC₅₀ calc	pIC₅₀ obs	IC₅₀ calc	IC₅₀ obs	Residual
A0	-8.858	0.017	0.357	4.22	4.17	60.19	67.61	-7.42
A1	-8.706	0.026	0.366	5.01	5.05	9.70	8.91	0.79
A11	-8.703	0.033	0.211	5.65	5.55	2.25	2.82	-0.57
A12	-8.700	0.031	0.176	5.73	5.70	1.86	2.00	-0.13
A14	-8.921	0.005	0.157	4.34	4.36	45.90	43.65	2.25
B1	-8.703	0.032	0.362	5.16	5.19	6.95	6.46	0.49
B15	-8.677	0.056	0.268	6.04	6.05	0.91	0.89	0.02
B16	-9.104	0.058	0.093	4.83	4.83	14.96	14.79	0.16
C11	-8.684	0.035	0.193	5.82	5.89	1.50	1.29	0.21

Calc: calculation value

Obs: observation value

Figure 2. Correlation analysis between calculation and observation QSAR

Table 6. New design of mono-ketone curcumin analogues compound with lipid peroxidation inhibition activity

Equation: pIC₅₀ = + 4.2153 (± 0.4162) AM1_HOMO + 19.9814 (± 3.2287) vsurf_CW6 - 3.1153 (± 0.6332) vsurf_ID2 + 42.3321 (± 3.7490)
Comp.	Descriptor			pIC₅₀ calc	IC₅₀ (µM) calc
Comp.	vsurf_D7	vsurf_HB1	vsurf_ID8
A103	-8.6792297	0.018273853	0.27841276	5.24	2.95
A116	-8.9933104	0.064166854	0.10269324	5.38	0.95
A153	-8.6707096	0.054440063	0.51383364	5.27	2.45

Calculation of the best model shown as in table 5, selected based on the value of the best statistical parameters so that the model also used in designing new compounds from curcumin mono-ketone analogs with antioxidant activity. This equation also has good robustness and accuracy seen from the residual value so that it used in designing new analogs. The new compound designs obtained from the best equation are as shown in table 6.

In vitro evaluation of new curcumin analogues mono-ketone compound:

The compounds used in the lipid peroxidation inhibition assay were A103, A116, and A153, which dissolved in the DMSO. Based on the results of QSAR studies that have been carried out, these compounds have promised predictive values for further in vitro assay. Ascorbic acid used as the positive.

As the previous explanation, lipid peroxidation involved in a variety of degenerative diseases and aging, including atherosclerosis, cataracts, and rheumatoid arthritis. Antioxidant mechanisms may divide into four categories: prevention of active oxidant formation, scavenger of active radicals, elimination of active oxidants, repair of damage and excretion of toxic oxidation products, and adaptive responses [20,21]. Microsome lipid peroxidation stimulated by one of the following systems: i) Fe³⁺ /ADP/NADPH enzymatic system and ii) Fe²⁺/ascorbate system that is not dependent on enzymes as was done in this study.

In this study, lipid peroxide concentration was measured by the method of thiobarbituric acid reactive substances (TBARS) through measurement of malondialdehyde as the final product of lipid oxidation. TBARS is one of the earliest lipid peroxidation indicators used in research [22]. The measurement uses a spectrophotometer based on the absorption of colors formed at a wavelength of 532nm from the reaction of two TBA molecules and the carbonyl group of one MDA molecule. This method often used in measuring lipid peroxide because it is cheaper, easy to apply, and sensitive [21,23–25].

Microsomes were a source of lipids. Vit C is responsible for keeping iron ions in a reduced condition (Fe²⁺) by forming Vit C radicals, dehydroascorbic acid. Glutathione (GSH) is an antioxidant that is responsible for keeping Vit C in its original form by forming Glutathione disulfide (GSSG) which is the result of reduction of GSH (as shown in figure 3). GSH is an enzyme produced from microsomal heating. Lipid peroxidation is a complex process, which can be thought of as a sequence of events initiated by the abstraction of hydrogen atoms, followed by the reaction of oxygen with radicals formed, and by further free radical chain reactions. Iron ions play an essential role, because they act as catalysts in the early stages of peroxidation, and accelerate the breakdown of lipid hydroperoxides which usually contaminate the microsomal fraction.

Figure 3. non-enzymatic lipid peroxidation inhibition [20]

In this study, lipid peroxidation products determined by measuring the amount of malondialdehyde (MDA). MDA is a product of oxidation of unsaturated fatty acids by free radicals in the body. MDA is also a metabolite of cell components produced by free radicals [26]. High malondialdehyde concentration indicates the oxidation process in the cell membrane. Conversely, a decrease in the amount of MDA, usually followed by a high increase in antioxidant status. Therefore, the high or low amount of MDA is very dependent on the antioxidant potential of a compound.

Based on the results of the study, it obtained the percent value of lipid peroxidation inhibition which then used as a basis for determining IC₅₀ values — the percentage value of lipid peroxidation inhibition as shown in figure 4. From Figure 4, it known there is a correlation between the concentration of compounds with the percentage inhibition of lipid peroxidation. The higher the concentration of the test compound, the more actively it reduces lipid peroxidation.

Figure 4. Percent inhibition of lipid peroxidation

The results of the percent value of inhibition of lipid peroxidation of each compound were used to determine the IC₅₀ value. IC₅₀ values indicate the ability of compound concentrations to inhibit lipid peroxidation by 50%. The smallest IC50 value shows the best ability to inhibit lipid peroxidation. IC₅₀ values of each compound, as shown in table 7.

Table 7. IC50 Value of lipid peroxidation inhibition

Comp.	IC₅₀ value (µM)
A103	2.95
A116	0.95
A153	2.45
Vit C	0.59

Table 7 shows that compound A116 had the lowest IC50 value compared to A153 and A103. Table 7 shows that compound A116 has the best ability to inhibit lipid peroxidation compared to A153 and A103. However, the Vitamin C compound still has a smaller IC50 value than the A116 compound so it can conclude that Vitamin C is still better at inhibiting lipid peroxidation than the A116 compound.

In general, the test compound has two main structures that are thought to be related to its active site (binding site), namely the substituent portion of the symmetrical aromatic benzene and the aromatic benzene, α ketone, β-unsaturated (Enone group). Antioxidant and anti-inflammatory activity of the mono-ketone curcumin analogs compounds due to the fall of electron donors such as methoxy on aromatic substituents which can increase the inhibitory activity of lipid peroxides and inhibition of the cyclooxygenase enzyme [16]. The results of the test compound showed the potential to inhibit lipid peroxidation as a free radical scavenger (OH*) that is, the ability as an antioxidant to capture active oxygen species shown with low MDA levels.

CONCLUSION:

The results of this study prove that the new mono-ketone analogs of curcumin from the QSAR studies using BuildQSAR was a new analogs compound that has been shown to have potential lipid peroxidation inhibition by scavenging free radicals.

ACKNOWLEDGEMENT:

The authors are grateful to Medicinal Chemistry Department, Faculty of Pharmacy, and Universitas Gadjah Mada, Yogyakarta, Indonesia for license of MOE 2018.01.01 and Funding this research.

FUNDING:

This research was funded by Rekognisi Tugas Akhir (RTA) Program from Universitas Gadjah.

AUTHORS CONTRIBUTIONS:

All the author has contributed equally.

CONFLICT OF INTERESTS:

The authors confirm that this article content has no conflicts of interest.

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Received on 09.09.2019 Modified on 29.10.2019

Research J. Pharm. and Tech. 2020; 13(10):4829-4835.

DOI: 10.5958/0974-360X.2020.00850.1

Model	n	m	Descriptor			Statistical value
Model	n	m	X1	X2	X3	r	s	F	Q2	sPRESS	sDEP
1	8	3	vsurf_CW6	vsurf_ID2	AM1_HOMO	0.998	0.058	343.729	0.987	0.094	0.074
2	8	2	vsurf_D8	vsurf_D7		0.951	0.237	28.243	0.597	0.485	0.42
3	8	1	vsurf_D7			0.864	0.356	20.557	0.617	0.437	0.409