Hits-to-lead optimization of the natural compound 2,4,6-trihydroxy-3-geranyl-acetophenone (thga) as a potent lox inhibitor: Synthesis, structure-activity relationship (sar) study, and computational assignment

molecules

Article

Hits-to-Lead Optimization of the Natural Compound

2,4,6-Trihydroxy-3-geranyl-acetophenone (tHGA) as a

Potent LOX Inhibitor: Synthesis, Structure-Activity

Relationship (SAR) Study, and

Computational Assignment

Chean Hui Ng ^1,2, Kamal Rullah ^3,4, Faridah Abas ⁵, Kok Wai Lam ³, Intan Safinar Ismail ¹

,

Fadzureena Jamaludin ⁶and Khozirah Shaari ^1,

*

1

Laboratory of Natural Products, Institute of Bioscience, Universiti Putra Malaysia (UPM),

Serdang 43400, Selangor, Malaysia; nch_chean@hotmail.com (C.H.N.); saﬁnar@upm.edu.my (I.S.I.)

School of Pharmacy, Management and Science University (MSU), University Drive, Off Persiaran Olahraga,

Seksyen 13, Shah Alam 40100, Selangor, Malaysia

Faculty of Pharmacy, Universiti Kebangsaan Malaysia (UKM), Jalan Raja Muda Abdul Aziz,

Kuala Lumpur 50300, Malaysia; kamalrullah@yahoo.co.id (K.R.); david_lam@ukm.edu.my (K.W.L.)

Nanotechnology and Catalysis Research Centre (NANOCAT), Institute of Postgraduates Studies,

University of Malaya (UM), Kuala Lumpur 50603, Malaysia

Department of Food Science, Faculty of Food Science and Technology, Universiti Putra Malaysia (UPM),

Selangor Darul Ehsan, Serdang 43400, Selangor, Malaysia; faridah_abas@upm.edu.my

Forest Research Institute (FRIM), Selangor Darul Ehsan, Kepong 52109, Malaysia; fadzureena@frim.gov.my

Correspondence: khozirah@yahoo.com.my; Tel.: +603-8947-1248; Fax: +603-8942-3552

2

3

4

5

6

*

ꢀꢁꢂꢀꢃꢄꢅꢆꢇ

ꢀꢁꢂꢃꢄꢅꢆ

Received: 29 August 2018; Accepted: 25 September 2018; Published: 30 September 2018

Abstract: A new series of 2,4,6-trihydroxy-3-geranyl-acetophenone (tHGA) analogues were

synthesized and evaluated for their lipoxygenase (LOX) inhibitory activity. Prenylated analogues

4a

exhibit better inhibitory activity than tHGA (3a) (IC₅₀value: 23.6

hydrophobic interaction when the alkyl chain length was reduced. One geranylated analogue, 3d

with an IC₅₀value of 15.3 M, exhibited better LOX inhibitory activity when compared to tHGA (3a),

–

g

(half maximal inhibitory concentration (IC₅₀) values ranging from 35

µM to 95 µM) did not

µM) due to the reduction in

,

µ

which was in agreement with our previous ﬁndings. Kinetics study showed that the most active

analogue (3e) and tHGA (3a) acted as competitive inhibitors. The combination of in silico approaches

of molecular docking and molecular dynamic simulation revealed that the lipophilic nature of

these analogues further enhanced the LOX inhibitory activity. Based on absorption, distribution,

metabolism, excretion, and toxicity (ADMET) and toxicity prediction by komputer assisted technology

(TOPKAT) analyses, all geranylated analogues (3a–g) showed no hepatotoxicity effect and were

biodegradable, which indicated that they could be potentially safe drugs for treating inﬂammation.

Keywords: Analogues; lipoxygenase; in-silico; ADMET; TOPKAT

1. Introduction

Lipoxygenases (LOXs) are a family of nonheme iron-containing enzymes that are involved in the

oxygenation of polyunsaturated fatty acids (PUFAs) containing cis–cis 1–4 pentadiene structures to

give hydroperoxy derivatives. In general, LOXs can be found in plant and animal tissues [1]. They can

be classiﬁed as 5-, 8-, 9-, 11-, 12-, and 15-LOXs based on their positional speciﬁcity of arachidonic acid

oxidation [2].

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LOXs are potential targets for rational drug design since they are involved in a variety of disorders,

such as bronchial asthma, inﬂammation, cancer, and autoimmune diseases [ ]. The human 5-LOX

pathway is the source of potent proinﬂammatory mediators [ ]. Leukotrienes (LTs), produced through

3

4

the human 5-LOX pathway, are mediators for allergy and asthma, while cysteinyl leukotrienes (CysLTs),

the metabolites of LTs, are known to sustain bronchoconstriction, hypersecretion of mucus, and airway

edema, which can trigger asthma [5–7]. Hence, inhibitors for the human 5-LOX pathway are crucial in

therapies for various inﬂammation-related diseases.

Synthesizing a molecule with speciﬁc human 5-LOX inhibition activity has emerged as a valuable

therapeutic strategy. Thus, structural insight into the human 5-LOX active site and its interaction

with ligands is essential in designing such compounds. However, due to the difﬁculties in obtaining

the human enzyme in sufﬁciently puriﬁed form and the availability of soybean enzyme, most of the

structural research had been done using soybean LOX as a biological screen [8,9].

2,4,6-Trihydroxy-3-geranylacetophenone (tHGA) (3a) is a drug-like compound containing the

phloroglucinol structural core as the bioactive principle (Figure 1). Our earlier bioassay-guided

identiﬁcation studies identiﬁed this compound in the medicinal plant Melicope ptelefolia [10].

This compound can also be synthesized via direct C-alkylation, using 2,4,6-trihydroxyacetophenone

and geranyl bromide as the starting material [11]. Further exploration into the chemistry and

pharmacology of tHGA revealed that it is a dual inhibitor of LOX and Cyclooxygenase (COX) [10,12].

When tested in an acute murine model, tHGA was as effective as Zileuton, a commercial LOX inhibitor,

in preventing allergic airway inﬂammation [11].

Previously, we reported our synthesis and docking studies of geranylated analogues of tHGA [13].

In our preliminary SAR study, elongating the chain of acyl moieties and introducing an aromatic

moiety signiﬁcantly improved the inhibitory activity compared to tHGA. Biological evaluation of

the analogues revealed that three targeted compounds, ((E)-1-(3-(3,7-dimethylocta-2,6-dienyl)-2,4,6-

trihydroxyphenyl)propan-1-one (3c), (E)-1-(3-(3,7-dimethylocta-2,6-dienyl)-2,4,6-trihydroxyphenyl)

pentan-1-one (3e), and (E)-1-(3-(E-3,7-dimethylocta- 2,6-dienyl)-2,4,6-trihydroxyphenyl)-3-phenylprop-

2-en-1-one (3g)), displayed better activity against soybean 15-LOX compared to tHGA (Figure 1).

Preserving the lipophilic geranyl group improved the enzymatic activity compared to nongeranylated

intermediates. However, the increased lipophilicity of the compounds reduced their solubility and led

to a poor pharmacokinetic proﬁle. This motivated us to synthesize a new series of tHGA analogues by

shortening the geranyl group to a prenyl group, which we hypothesized could improve the solubility

of the compounds.

Figure 1. Half maximal inhibitory concentration (IC₅₀) values of 2,4,6-trihydroxy-3-geranyl-

acetophenone (tHGA) and analogues.

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2. Results and Discussion

2.1. Synthesis of 2,4,6-Trihydroxy-3-Geranylacetophenone (tHGA) Analogues

Previously, we reported the synthesis of the acylphloroglucinols (2b

–

c,

2e

–

g) and geranylated

analogues (3a–c, 3e–g) and evaluated them for soybean-LOX inhibitory activity [13]. Our focus in

this work is to reduce one isoprene unit from geranyl to prenyl and to replace the hydroxyl group in

positions 4 and 6 of the phloroglucinol core by methoxy groups (Figure 2).

Figure 2. Modiﬁcations carried out on the geranyl and hydroxyl groups of tHGA analogues.

Prenylated analogues (4a

(Scheme 1 ). The acylphloroglucinols (2b

through Friedel–Craft acylation by using aluminum chloride as a catalyst [14]. Prenylated analogues

were synthesized by reacting the acylphloroglucinols (2a ) with prenyl bromide through direct

–

g) were synthesized by Friedel–Craft acylation and direct C-alkylation

–

g) were ﬁrst synthesized from phloroglucinol and acyl halides

–

g

C-alkylation, using potassium carbonate as a base in dry methanol. A geranylated analogue (3d) was

also synthesized, by reacting acylphloroglucinol (2d) with geranyl bromide [11]. In order to investigate

the importance of the hydroxyl group to the bioactivity, the hydroxyl group was methylated using

methyl iodide as a methylating agent, as described by Smith (2005), to yield compounds 5a

6e 15]. The structures of the seven prenylated, one geranylated, and four methylated analogues were

established on the basis of ¹H-NMR, ¹³C-NMR, and MS spectral data (Supplementary Materials).

, 5e and 6a,

[

O

OH

O

OH

iii

R

HO

OH

O

OH

O

OH

3a-g

5a,5e

i

R

ii

HO

OH

HO

OH

1

2a-g

O

OH

O

OH

iii

R

HO

OH

O

4a-g

6a,6e

R

H₃C

a

g

c

e

f

b

d

Scheme 1. Reagents and conditions: (i) acyl chloride, anhydrous aluminum chloride, dichloromethane,

hydrochloric acid, reﬂux 6 h; (ii) geranyl/prenyl bromide, anhydrous potassium carbonate, dry

methanol, reﬂux 8 h; (iii) methyl iodide, anhydrous potassium carbonate, dimethylformamide,

hydrochloric acid, reﬂux 9 h.

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2.2. Soybean LOX-1 Inhibition Assays

The prenylated analogues (4a

IC₅₀values ranging from 35.1 to 95.4

Unfortunately, the 15-LOX inhibitory activity of the methylated compounds (5a

–

g

) demonstrated moderate dose-dependent LOX inhibition, with

µM. Geranylated analogue 3d had an IC₅₀value of 15.3

µM.

,

5e, 6a, and 6e) could

not be carried out due to insolubility of the compounds. To further understand the binding afﬁnity

of the analogues, nordihydroguaiaretic acid (NDGA), a known soybean LOX inhibitor, was used as

reference standard (Table 1).

Table 1. IC₅₀values and % inhibition for the inhibition of soybean lipoxygenase (LOX)-1 by the tested

compounds. NDGA, nordihydroguaiaretic acid.

Compound

% Inhibition (100 µg/mL)

IC₅₀Value (µM) Mean ± SEM

3a (tHGA) ^#

94.3 ± 3.4

90.3 ± 4.1

94.4 ± 3.0

90.7 ± 5.0

90.3 ± 4.4

88.8 ± 5.9

90.8 ± 7.6

94.8 ± 5.2

82.5 ± 7.3

78.1 ± 3.9

86.2 ± 6.9

79.4 ± 6.7

93.7 ± 3.8

95.2 ± 3.2

100.0 ± 0.0

#

23.6 ± 1.7

27.6 ± 3.6

12.3 ± 0.6

15.3 ± 0.5

10.3 ± 1.5

26.3 ± 1.3

15.2 ± 1.2

72.1 ± 1.2

53.7 ± 0.7

61.0 ± 1.1

39.5 ± 1.2

35.1 ± 1.3

52.6 ± 1.0

95.4 ± 4.0

0.1 ± 0.0

3b ^#

3c ^#

3d

3e ^#

3f ^#

3g ^#

4a

4b

4c

4d

4e

4f

4g

NDGA

Data published in previous work [13].

In comparison to geranylated compounds 3a

were less active in their anti-inﬂammatory effect (IC₅₀= 35.1–95.4

unit (geranyl to prenyl) reduced the lipophilicity of the compounds, which indirectly also reduced the

inhibitory effect, as lipophilicity is an important physiochemical property for LOX inhibition [16 19].

Compound 3d (IC₅₀= 15.3 M), with the longer acyl chain, showed better inhibitory activity than

tHGA (IC₅₀= 23.6 µM), which is in agreement with our previous ﬁndings [13].

–

g

(IC₅₀= 10.3–26.3

µM), prenylated compounds 4a–g

µM). The reduction by one isoprene

–

µ

The SAR pattern for the prenylated compounds was similar to that of the geranylated compounds,

where the longest aliphatic chain length on the acyl substituent, as in compound 4e, was the most

active inhibitor (IC₅₀value 35.1 µM) among the compounds. Replacement of the aliphatic chain by a

cyclohexyl ring and branched acyl substituent, as in compounds 4b and 4f, were also found to impart

less potency than the synthetic analogues. However, compound 4g, with an aromatic ring as the acyl

substituent, was not as active as the geranylated series. This may be due to the insolubility of the

compound when performing the assay. Among the active analogues of tHGA (3a), four compounds

(3c–e and 3g) exhibited higher inhibitory activity than the parent molecule, tHGA (3a). The most active

compound, 3e (IC₅₀= 10.3

(IC₅₀= 0.1 µM).

µM), was 100-fold less active when compared to the standard drug, NDGA

The most active compound, 3e, and the parent compound, tHGA (3a), were subjected to further

in silico study of their probable mechanism of inhibition. Structural-based information for a protein

alone is not enough to understand the binding afﬁnity of the enzyme inhibitor. For a deeper

understanding of how an inhibitor works with an enzyme, kinetic studies should be conducted

in order to yield more useful information. In the present study, the type of inhibition was deduced

from two plots, nonlinear regression Michaelis–Menten enzyme kinetics and the corresponding

Lineweaver–Burk double reciprocal plots, based on the parameters K_m(Michaelis–Menten constant)

and V_max(maximum enzyme velocity).

Our results show that both tHGA (3a) and compound 3e inhibited catalytic activity of the soybean

15-LOX as a function of increasing concentration of the compound. The kinetic behavior of the enzyme

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followed Michaelis–Menten kinetics. The inhibition kinetics, analyzed by a Lineweaver–Burk plot,

showed that tHGA and compound 3e shared a competitive type of inhibition (Figure 3a,b), since

increasing the inhibitor concentration resulted in a common intercept above the 1/V_maxaxis with

different slope. The K_mfor both compounds increased with increasing concentrations of inhibitor.

However, the V_maxvalues remained constant.

Lineweaver-Burk of Michaelis-Menten Data

1500

Lineweaver-Burk of Michaelis-Menten Data

1500

1250

1000

750

1250

1000

750

500

3.13 μg/mL

1.57 μg/mL

0 μg/mL

1.57 μg/mL

0 μg/mL

250

-2.0 -1.5 -1.0 -0.5

0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.0

1/[S] (mM)^-1

-2.0 -1.5 -1.0 -0.5

0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.0

1/[S] (mM)^-1

-250

-500

(a)

(b)

Figure 3. Lineweaver–Burk plot of 13-Hydroperoxyoctadeca-9,11-dienoic acid (13-HPOD) generated by

◦

soybean LOX-1 in the presence of (

a) compound 3e and (

b

) tHGA (3a) at 25 C, pH 9.0. Concentrations

of substrate used were 0.2, 0.3, 0.4, and 0.5 mM.

Since compounds 3e and tHGA (3a) are competitive inhibitors, there were no changes in maximal

velocity. Hence, to calculate the inhibitor constant (K_i), which is a measure of enzyme–inhibitor afﬁnity

or potency of different inhibitors, the slope of the Lineweaver–Burk plot was plotted against the

inhibitor concentrations, where the intercept on the inhibitor axis gave the K_ivalue [20]. The obtained

K_m, V_max, and K_ivalues are shown in Table 2. The inhibitor constant (K_i) for compound 3e (K_i= 36.1) is

lower than that of tHGA (3a) (K_i= 41.1), which suggests that compound 3e has higher afﬁnity toward

the enzyme than tHGA (3a).

Table 2. K_m(Michaelis–Menten constant), V_max(maximum enzyme velocity), and K_i(inhibitor constant)

for the inhibition of soybean LOX-1 by the tested compounds.

Concentrations (µg/mL)

Compounds

K_i(µM)

0

1.57

3.13

K_m

V_max

K_m

V_max

K_m

V_max

3e

4.62

2.63

0.035

0.020

5.20

2.96

0.035

0.020

5.78

3.29

0.035

0.020

36.1

41.1

tHGA (3a)

2.3. Homology Modeling of Soybean LOX-1

In our previous study, docking studies were performed using the soybean LOX-3 crystal structure

(PDB ID: 1IK3), although soybean LOX-1 was used in the actual experiment [13]. Since the LOX-1

crystal structure in the Protein Data Bank (PDB) library only exists in a close conformation, this negated

our attempt to dock our compounds on the active site. To overcome this, a homology model approach

was adopted by building a soybean LOX-1 model based on the template open-conformation structure

of soybean LOX-3 (PDB ID: 1IK3).

Brieﬂy, to initiate the model-building process, we used SWISS-MODEL, an automated protein

homology-modelling server, to predict the open conformation of LOX-1. The pairwise alignment of

the protein target and the template sequence is shown in Supplementary Figure S37. Since LOX-1 and

LOX-3 share a high sequence similarity of 73.13%, this allowed us to accurately predict the position of

the essential iron catalytic site (active site) in the model. The obtained model was then veriﬁed with

PROCHECK analysis. Ramachandran plot of the minimized model revealed that 98.9% of the residues

Molecules 2018, 23, 2509

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were located in the allowed regions (77.9% most favored), while 1.1% (eight residues) were outside the

allowed regions (Supplementary Figure S38). Note that residues that were located outside the allowed

regions were far from the substrate-binding domain, indicating that they may not have affected the

ligand–protein binding simulations. Thus, it was concluded that the obtained ﬁnal model of LOX-1

was satisfactory.

Although there were signiﬁcant differences in terms of size, sequence, and substrate preference

among the LOX isoenzymes, the overall fold and geometry of the essential nonheme iron-binding

site were highly conserved [21,22]. In particular, the structural geometry of the iron-binding site for

soybean LOX-1 comprises four amino acid ligands: the imidazole N-atoms of three histidine residues

(His499, His504, and His690) and the carboxylate oxygen of the C-terminal Asn694, which chelated

with the Fe³⁺. Based on the superimposition of soybean LOX-3 (PDB ID: 1IK3) over the soybean LOX-1

structure, the active site can be deﬁned as a sphere of 10 Å centered on the inhibitor co-crystallized

soybean LOX-3. Knowledge of the orientation of the essential amino acid residues in the active site

will provide useful insights for the process of designing potent inhibitors.

2.4. Molecular Docking Analysis

Compounds 3e

Compound 3e exhibited the highest binding interaction energy of

compound 4e, with 42.65 kcal/mol, and tHGA (3a) with 43.03 kcal/mol. These binding interaction

energies were well correlated with the bioassay results.

,

4e, and 3a (tHGA) were docked to the homology model’s active site by cDOCKER.

−

50.28 kcal/mol compared to

−

The results (Figure 4a,b) show that compound 3e formed three important hydrogen bonding

interactions with amino acid residues His494, His499, and Gln697. In the 2D models (Figure 4 a), the

carbonyl moiety formed a 2.3 Å hydrogen bond with His494 (C–O—-H–N), while the hydroxyl group

of the phloroglucinol moiety formed two hydrogen bonds with His499 (H–O—-H–N with a distance of

2.1 Å) and Gln697 (O–H—-O–C with a distance of 2.5 Å). In addition, the carbonyl moiety also formed

a 3.1 Å carbon–hydrogen bond with Gln495 (O–C—-H–C). The alkyl groups of the geranyl and acyl

side chains were also involved in a series of hydrophobic interactions with residues Ile538, Leu541,

Leu754, Ile839, Leu546, His504, Ile553, Trp500, Ile547, His499, Ile751, and Arg707.

(a)

Figure 4. Molecular binding models of compound 3e in the active site of the LOX-1 homology model:

(b)

(

a

) 2D diagram; ( ) 3D diagram. In ( ), green line indicates hydrogen-bonding interactions, light green

line indicates covalent bonding, pink line indicates hydrophobic interactions, and purple line indicates

interactions. In ( ), the atoms are colored gray for carbon, red for oxygen, blue for nitrogen, and

b

a

π

–

π

b

white for hydrogen; amino acid residues are in green.

Similarly, the aromatic ring of the phloroglucinol moiety (Figure 5a,b) formed π–π and π–alkyl

interactions with both Phe557 and Leu754. Figure 5a,b depict the binding of the most active prenylated

compound 4e in the active site of the LOX-1 homology model for comparison. As observed in the

Molecules 2018, 23, 2509

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2D model (Figure 5a), the oxygen atom of the carbonyl moiety formed a 3.2 Å hydrogen bond with

His494 (C–O—-H–N). The hydroxyl group of the phloroglucinol moiety formed two 2.7Å and 2.8 Å

hydrogen bonds with the amino acid residues Gln697 (O–H—-O–C) and His499 (H–O—-N–C). As with

compound 3e, the alkyl groups from the acyl and prenyl side chains of compound 4e were engaged in

hydrophobic contact with residues Arg707, Ile751, His499, Trp500, Ile547, Ile553, Ala542, Leu546, and

His504. In addition, a π–alkyl interaction between the aromatic ring of the phloroglucinol moiety with

Leu754 was also observed.

(a)

(b)

Figure 5. Molecular binding models of compound 4e in the active site of the LOX-1 homology model:

) 2D diagram; ( ) 3D diagram. In ( ), green line indicates hydrogen-bonding interactions, light green

line indicates covalent bonding, pink line indicates hydrophobic interactions, and purple line indicates

interactions. In ( ), atoms are colored gray for carbon, red for oxygen, blue for nitrogen, and white

(a

b

a

π

–π

b

for hydrogen; amino acid residues are in green.

On the other hand, tHGA (3a) was stabilized by the hydrogen bonding interactions between

the hydroxyl group of the phloroglucinol moiety with amino acid residue Gln495 (O–H—-O–C with

distances of 2.4 Å and 2.5 Å, respectively) and a 2.5 Å carbon-hydrogen bonding interaction with

His499 (O–H—-C–N) (Figure 6a,b). The geranyl moiety of tHGA (3a) formed a hydrophobic cluster

with His494, His499, Ile751, Arg707, and Val354. In addition, the phloroglucinol moiety of tHGA (3a

)

formed another hydrophobic cluster with Ile553, Leu546, and His499 residues. Apart from these, the

aromatic ring of tHGA (3a) also had a

π

–alkyl interaction with residues Ile553 and Leu546 and a π–π

interaction with residue His499.

(a)

(b)

Figure 6. Molecular binding models of tHGA (3a) in the active site of the LOX-1 homology model: (

2D diagram; ( ) 3D diagram. In ( ), green line indicates hydrogen-bonding interactions, light green

line indicates covalent bonding, pink line indicates hydrophobic interactions, and purple line indicates

interactions. In ( ), atoms are colored gray for carbon, red for oxygen, blue for nitrogen, and white

for hydrogen; amino acid residues are in green.

a)

b

a

π

–π

b

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2.5. Molecular Dynamics Simulation

Molecular dynamics (MD) simulation plays an important role in drug discovery, as it allows

drug designers to have clear insight into the movement of ligand in a protein binding site. In this

study, MD simulations were started with the parameterization of ligands by using the Automated

Topology Builder (ATB). The prepared complex was then pretreated, followed by restraints positioned

on residues 499, 504, 690, and 694 (residues chelate with Fe atom). Figure 7 shows that the overall

structure of the soybean LOX-1 model was well equilibrated after 1 ns, with a root-mean square

deviation (RMSD) of 3.0 Å for the backbone atoms. It is clear that the position and orientation of

compounds 3e

end of the simulation, as shown in Supplementary Figures S39–S41. The simulation results revealed

that the inhibitors (3e 4e, and tHGA (3a)) may bind in a similar manner to the LOX-1 binding site.

, 4e, and tHGA (3a) in the binding site were slightly different than the initial input at the

,

Notably, the alkyl side chains of the compounds were engaged in a series of hydrophobic contacts with

ﬁve amino acid residues, His499, Trp500, Ala542, Ile547, and Leu754.

Figure 7. Total root-mean square deviation (RMSD) evolution along simulation time.

The Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA) calculation was further

employed to evaluate the free energy decomposition at the atomic level, especially the Van der Waals

and electrostatic energy contributions. This calculation is extremely useful in understanding ligand

binding behavior in binding sites. Residues that favor binding interactions are colored in red, while

residues that are not favorable for binding interactions are shown in blue (Figure 8).

Molecules 2018, 23, 2509

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(a)

(b)

(c)

Figure 8. Stereo view of binding sites of (

a) compound 3e, (b) compound 4e, and (c) compound 3a

(tHGA) after simulation. Residues that favor binding interactions are colored in red; residues that are

not favorable for binding interactions are shown in blue.

The results show that the phloroglucinol aromatic ring of the most active compound (3e

)

formed a stacked

Supplementary Figures S42 and S43. This particular amino acid residue could play an important role

in the placement of the compound in the active site via hydrophobic interaction ( interaction) with

signiﬁcant total free binding interaction energy ( G_bind7.14 kcal/mol) (Supplementary Table S1).

Based on the calculated residue-based energy decomposition, two amino acid residues, Ile751

G_bind5.13 kcal/mol) and Leu546 ( G_bind4.04 kcal/mol), were identiﬁed to have favorable

π–π interaction with Phe557 taken from the ﬁnal ns of the simulation, as shown in

π–π

∆

=

−

(

∆

=

−

∆

=

−

interaction with the ligand via π–alkyl interaction (Supplementary Table S1).

Similar results were also observed for compound 4e. As shown in Supplementary Table S2, the

amino acid residues that contributed to signiﬁcant binding interaction energy with compound 4e were

Ile751 (

and Leu546 (

while the prenyl side chain formed

Figures S44 and S45). On the other hand, the aromatic ring was engaged in

∆

G_bind

=

−

6.34 kcal/mol), Val750 (

G_bind4.51 kcal/mol). The acyl side chain formed a

–alkyl interactions with Ile547 and Ile546 (refer to Supplementary

–alkyl interactions with

∆

G_bind

=

−

6.13 kcal/mol), Ile547 (

∆

G_bind

=

−

5.18 kcal/mol),

∆

=

−

π–alkyl interaction with Ile751,

π

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Val750 and Ile751, and formed a

π–sigma interaction with Val750 (Supplementary Figures S44 and

S45). Note that residue Val750, which played a major role in hydrophobic interactions, was not found

in the docking results. The abovementioned amino acid residues are shown in red in Figure 8b.

From our observation, tHGA (3a) was stabilized by three important amino acid residues,

Leu754, Leu546, and Ile538, which contributed to signiﬁcantly high values of total free binding

interaction energy, with values of

−

8.71 kcal/mol,

−

7.45 kcal/mol, and

−

6.63 kcal/mol, respectively

(Supplementary Table S3). These amino acid residues were involved in the hydrophobic interaction

with the hydrophobic geranyl side chain and phloroglucinol aromatic ring of tHGA (3a) (refer to

Supplementary Figures S46 and S47). In addition, residue Glu256 also contributed signiﬁcant total free

binding interaction energy (

with the carbonyl moiety of tHGA (3a) (refer to Supplementary Figures S46 and S47).

Table 3 summarizes the binding free energy ( G_bind) for compounds 3e 4e, and tHGA (3a).

The most lipophilic geranylated compound 3e 150.71 kJ/mol), with larger hydrophobic interactions

with the adjacent amino acid residues, had the highest binding free interaction energy when compared

to the less lipophilic prenylated compound 4e 111.79 kJ/mol) and tHGA (3a) ( 148.04 kJ/mol).

The major favorable contributors to inhibitor binding were Van der Waals energy ( E_vdw) and nonpolar

solvation energy ( G_np). Although electrostatic energy ( E_ele) was as high as nonpolar solvation

energy ( G_np), the unfavorable polar solvation energy ( G_pb) minimized its effect. The results suggest

that the Van der Waals interaction was the main contributor to the binding afﬁnity of these compounds

3e 4e, and tHGA (3a)). Overall, compound 3e had larger hydrophobic interaction contact when

compared to compound 4e and tHGA (3a). This observation correlates well with the bioassay result,

∆

G_bind

=

−

6.90 kcal/mol) from the carbon–hydrogen bonding interaction

∆

,

(

−

(

−

∆

(

,

in which compound 3e is a more potent inhibitor (IC₅₀= 10.31

(IC₅₀= 23.61 µM, K_i= 41.06) and compound 4e (IC₅₀= 35.10 µM).

µM, K_i= 36.08) than tHGA (3a)

Table 3. Summary of binding free energy (∆G_bind) for compounds 3e, 4e and tHGA (3a).

Van der Waals

Energy

Electrostatic

Energy

Polar Solvation

Energy

Nonpolar Solvation

Energy

Total Binding

Energy

Compound

3e

4e

−200.44 (8.75)

−175.29 (7.67)

−171.62 (9.16)

−16.93 (8.53)

−7.39 (5.74)

−14.40 (4.19)

87.65 (13.26)

89.10 (11.91)

57.28 (9.08)

−20.99 (1.02)

−18.21 (0.99)

−19.30 (0.93)

−150.71 (11.30)

−111.79 (12.59)

−148.04 (10.89)

tHGA (3a)

Nevertheless, the crucial iron-chelating His499 residue was shown to interact with compounds 3e

,

4e, and tHGA (3a) during the simulation. This further led to distortion of the iron active site geometry.

In fact, the kinetics results suggest that both tHGA (3a) and the most active compound 3e compete

with the substrates without chelating with the iron metal.

2.6. ADMET Analysis

Absorption, distribution, metabolism, excretion, and toxicity (ADMET) prediction is an important

tool for compound selection and prioritization in rational drug design. The information helps reduce

the time and computational cost of screening compound libraries to select compounds feasible for

synthesis and further testing [23,24]. The results are presented in Table 4.

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Table 4. Results of absorption, distribution, metabolism, excretion, and toxicity (ADMET) prediction

on selected parameters of selected compounds.

Compound

HIA

AS

BBB

PBB

CYP2D6

HT

3a **

3b

3c

3d

3e *

3f

3g

4a

4b

4c

Good

Moderate

Poor

Good

Low

Medium

Bound

Inhibitor

Noninhibitor

Inhibitor

Noninhibitor

Nontoxic

Toxic

–

Low

–

Good

Low

Good

Medium

High

4d

4e

4f

Toxic

4g

Good

Low

* Most active compound; ** parent compound. HIA, human intestinal absorption; AS, aqueous solubility; BBB,

blood–brain barrier; PPB, protein plasma binding; CYP2D6, cytochrome P450 2D6; HT, hepatotoxicity.

Based on the ADMET ﬁndings, tHGA (3a) and all prenylated compounds (4a

4e), except for compounds 4f and 4g, showed good intestinal absorption and good aqueous solubility.

In addition, tHGA (3a) and compounds 4b could be potent candidates for the treatment of central

, 4b, 4c, 4d, and

–

g

nervous system inﬂammatory disorders due to their moderate to high blood–brain barrier (BBB)

penetration. Compound 4a showed low BBB penetration.

For protein plasma binding (PBB), all compounds were expected to be highly bound to protein

plasma, which implied that dosing issues must be addressed in order to achieve desirable therapeutic

effects. In addition, compounds 3f, 3g, 4a–c, and 4f–g were noninhibitors for CYP2D6, indicating their

tolerance toward CYP2D6. On a positive note, none of the geranylated compounds (tHGA (3a), 3b–g)

showed hepatotoxicity effect.

2.7. TOPKAT Analysis

The major goal in medicinal chemistry is to develop safe drugs with few side effects. Thus,

toxicology studies, especially during the preclinical and clinical stages, must be performed in order to

assess the potential toxic effects of drugs. Toxicity prediction by komputer assisted technology

(TOPKAT) is a common tool for predicting the potential ecotoxicity, toxicity, mutagenicity, and

reproductive or developmental toxicity of drug candidates.

The 14 selected compounds from ADMET analysis were further screened with TOPKAT for

the following toxicity prediction properties: aerobic biodegradability, Ames mutagenicity, rodent

carcinogenicity, ocular irritancy, skin irritancy, and skin sensitization. The results are presented

in Table 5. It was found that, in general, all compounds were skin sensitizers but nonmutagenic,

noncarcinogenic, and nonirritant. All of the compounds were predicted to be biodegradable, except

for compound 4g. Nine of the compounds (3a–g, 4a and 4g) were predicted to be ocular nonirritants.

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Table 5. Results of toxicity predictive test on six important parameters.

Compound

AB

AM

RC

OI

SI

SS

3a **

3b

3c

3d

3e *

3f

3g

4a

4b

4c

Degradable

Nonmutagen Noncarcinogen Nonirritant

Nonirritant

Sensitizer

Nonmutagen Noncarcinogen

Irritant

4d

4e

4f

4g

Nondegradable Nonmutagen Noncarcinogen Nonirritant

* Most active compound; ** parent compound. AB, aerobic biodegradability; AM, Ames mutagenicity; RC, rodent

carcinogenicity; OI, ocular irritancy; SI, skin irritancy; SS, skin sensitization.

3. Materials and Methods

3.1. Synthesis of 2,4,6-Trihydroxy-3-Geranylacetophenone (tHGA) Analogues

3.1.1. General Methods

All reagents and solvents used were analytical grade. Column chromatography was performed

with Merck 7734 (0.040–0.063 mm) or Merck 9385 (0.063–0.200 mm) silica gel, while elutes were

analyzed with Merck TLC silica gel 60 F₂₅₄. Nuclear magnetic resonance (NMR) was recorded in

CD₃OD or CDCl₃using a 500 MHz Varian spectrometer, and mass analysis was done with a Shimadzu

QP5050A mass spectrometer. Melting points were determined using a Fisher–Johns hot stage melting

point apparatus equipped with microscope.

3.1.2. Two-Step Reaction: Friedel–Crafts Acylation and Direct C-Alkylation (3d, 4a–g)

Friedel–Crafts acylation: Small amounts of phloroglucinol (0.05 mol) and anhydrous aluminum

chloride (0.1 mol) were ﬁrst dissolved in dichloromethane (50 mL) and kept heated for 1 h at 40 ^◦C.

Acyl chloride (0.05 mole) was added dropwise into the reaction mixture, reﬂuxed for 8 h, and quenched

with 0.05 mole of HCl upon completion of the reaction. After the reaction was completed, the reaction

mixture was extracted with ethyl acetate and concentrated under reduced pressure. The residues

were subjected to column chromatography using silica gel eluted with hexane/ethyl acetate (10:1) [25].

Direct C-alkylation: A well-mixed mixture of acylphloroglucinol (1 mmol), geranyl bromide or prenyl

bromide (1 mmol), and anhydrous potassium carbonate (0.5 mmol) in dry methanol (3 mL) was

reﬂuxed for 8 h. After completion of the reaction, excess methanol was removed through high vacuum

and the residues were extracted with ethyl acetate. The organic layers were combined, dried, and

concentrated. Column chromatography over silica gel eluted with petroleum ether/ethyl acetate (10:1)

gave geranylated/prenylated compounds [11].

(E)-1-(3-(3,7-dimethylocta-2,6-dienyl)-2,4,6-trihydroxyphenyl)butan-1-one (3d). Light yellow solid (9.7%),

m.p. 116–118 ^◦C. ¹H-NMR (500 MHz, Methanol-d₄) d 5.89 (1H, s, H-4), 5.17 (1H, t, J = 6.5 Hz, H-2⁰⁰),

5.05 (1H, t, J = 6.6 Hz, H-7⁰⁰), 3.18 (2H, d, J = 7.0 Hz, H-1⁰⁰), 3.01 (2H, t, J = 7.2 Hz, H-2⁰), 2.04 (2H, q,

J = 7.4 Hz, H-6⁰⁰), 1.93 (2H, t, J = 7.4 Hz, H-5⁰⁰), 1.73 (3H, s, H-4⁰⁰), 1.66–1.70 (2H, m, H-3⁰), 1.60 (3H,

s, H-10⁰⁰), 1.55 (3H, s, H-9⁰⁰), 0.97 (3H, t, J = 7.4 Hz, H-4⁰). ¹³C-NMR (126 MHz, methanol-d₄) 205.96

(C-1⁰), 163.55 (C-3) 162.14 (C-1), 160.01 (C-5), 133.27 (C-3⁰⁰), ₀1₀30.54 (C-8⁰⁰), 124.09 (C-7⁰⁰), 123.22 (C-2⁰⁰),

0

00

106.63 (C-2), 103.85 (C-6), 93.43 (C-4), 45.46 (C-2 ), 39.49 (C-5 ), 26.30 (C-6 ), 24.41 (C-10 ), 20.65 (C-1 ),

18.25 (C-9⁰⁰), 16.27 (C-3⁰), 14.77 (C-4⁰⁰), 13.0 (C-4⁰). DIP: m/z 332.15.

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1-(2,4,6-trihydroxy-3-(3-methylbut-2-enyl)phenyl)ethanone (4a). Light yellow solid (12.5%), m.p. 164–166 ^◦C.

00

¹H-NMR (500 MHz, methanol-d₄) d 5.89 (1H, s, H-4), 5.16 (1H, t, J = 7.1 Hz, H-2 ), 3.16 (2H, d, J = 7.1 Hz,

H-1⁰⁰), 2.59 (3H, s, H-2⁰), 1.73 (3H, s, H-5⁰⁰), 1.63 (3H, s, H-4⁰⁰). ¹³C-NMR (126 MHz, Methanol-d₄) d

203.14 (C-1⁰), 163.36 (C-3), 162.47 (C-1), 160.36 (C-5), 129.63 (C-3⁰⁰), 123.09 (C-2⁰⁰), 106.47 (C-2), 104.07

(C-6), 93.32 (C-4), 31.39 (C-2⁰), 24.51 (C-4⁰⁰), 20.68 (C-1⁰⁰), 16.40 (C-5⁰⁰). DIP: m/z 236.10.

2-methyl-_◦1-(2,4,6-trihydroxy-3-(3-methylbut-2 enyl)phenyl)propan-1-one (4b). Yellow solid (10.8%), m.p.

1

142–144 C. H-NMR (500 MHz, methanol-d₄) d 5.88 (1H, s, H-4), 5.16 (1H, t, J = 6.5 Hz, H-2⁰⁰),

0

00

3.95–4.03 (1H, m, H-2 ), 3.17 (2H, d, J = 7.1 Hz, H-1 ), 1.73 (3H, s, H-4 ), 1.63 (3H, s, H-5 ), 1.12 (6H, d,

J = 6.9 Hz, H-3⁰, 4⁰). ¹³C-NMR (126 MHz, Methanol-d₄) 210.30 (C-1⁰), 163.85 (C-3)₀, 161.98 (C-5), 159.58

00

(C-1), 129.60 (C-3 ), 123.16 (C-2 ), 106.71 (C-6), 103.07 (C-2), 93.53 (C-4), 38.48 (C-2 ), 24.52 (C-5 ), 20.78

(C-1⁰⁰), 18.36 (C-3⁰, 4⁰), 16.41 (C-4⁰⁰). DIP: m/z 264.10.

◦

1-(2,4,6-trihydroxy-3-(3-methylbut-2-enyl)phenyl)propan-1-one (4c). Light brown solid (8.0%), m.p. 138–140 C.

¹H-NMR (500 MHz, methanol-d₄) d 5.88 (1H, s, H-4), 5.16 (1H, t, J = 7.5 Hz, H-2 ), 3.17 (2H, d, J = 7.1 Hz,

00

H-1⁰⁰), 3.05 (1H, q, J = 7.3 Hz, H-2⁰), 1.73 (3H, s, H-4⁰⁰), 1.63 (3H, s, H-5⁰⁰), 1.12 (3H, t, J = 7.3 Hz, H-3⁰).

¹³C-NMR (126 MHz, methanol-d₄) 206.52 (C-1⁰), 163.40 (C-3), 162.04 (C-5), 160.03 (C-1), 129.61 (C-3⁰₀⁰₀),

00

0

00

123.15 (C-2 ), 106.55 (C-6), 103.66 (C-2), 93.38 (C-4), 36.58 (C-2 ), 24.52 (C-5 ), 20.73 (C-1 ), 16.41 (C-4 ),

7.94 (C-3⁰). DIP: m/z 250.10.

◦

1-(2,4,6-trihydroxy-3-(3-methylbut-2-enyl)phenyl)butan-1-one (4d). Light yellow solid (9.1%), m.p. 138–140 C.

¹H-NMR (500 MHz, methanol-d₄) d 5.88 (1H, s, H-4), 5.16 (1H, t, J = 7.1 Hz, H-2⁰⁰), 3.16 (2H, d,

J = 7.1 Hz, H-1⁰⁰), 2.99–3.02 (2H, m, H-2⁰), 1.73 (3H, s, H-4⁰⁰), 1.68 (2H, dd, J = 7.4, 14.8 Hz, H-3⁰), 1.63

(3H, s, H-5⁰⁰), 0.97 (3H, t, J = 7.4 Hz, H-4⁰). ¹³C-NMR (126 MHz, methanol-d₄) 205.92 (C-1⁰), 163.53

00

(C-3), 162.11 (C-1), 160.00 (C-5), 129.60 (C-3 ), 123.15 (C-2 ), 106.57 (C-2), 103.82 (C-6), 93.40 (C-4), 45.45

(C-2⁰), 24.51 (C-5⁰⁰), 20.72 (C-1⁰⁰), 18.21 (C-4⁰⁰), 16.40 (C-3⁰), 12.98 (C-4⁰). DIP: m/z 264.10.

◦

1-(2,4,6-trihydroxy-3-(3-methylbut-2-enyl)phenyl)pentan-1-one (4e). Light yellow solid (5.5%), m.p. 133–135 C.

¹H-NMR (500 MHz, methanol-d₄) d 5.88 (1H, s, H-4), 5.16 (1H, t, J = 6.5 Hz, H-2 ), 3.16 (2H, d, J = 7.1 Hz,

00

H-1⁰⁰), 3.01–3.04 (2H, m, H-2⁰), 1.73 (3H, s, H-5⁰⁰), 1.60–1.63 (5H, m, H-3⁰, 4⁰⁰), 1.35–1.41 (2H, m, H-4⁰),

0.94 (3H, t, J = 7.4 Hz, H-5 ). ¹³C-NMR (126 MHz, methanol-d₄) 206.14 (C-1 ), 163.54 (C-3), 162.13 (C-1),

0

00

0

159.98 (C-5), 129.61 (C-3 ), 123.14 (C-2 ), 106.57 (C-2), 103.79 (C-6), 93.40 (C-4), 43.21 (C-2 ), 27.16 (C-3 ),

24.51 (C-5⁰⁰), 22.31 (C-4⁰), 20.73 (C-1⁰⁰), 16.41 (C-4⁰⁰), 12.88 (C-5⁰). DIP: m/z 278.10.

1

Cyclohexyl(2,4,6-trihydroxy-3-(3-methylbut-2-enyl)phenyl)methanone (4f). Dark brown oil (6.5%). H-NMR

(500 MHz, methanol-d₄) d 5.87 (1H, s, H-4), 5.16 (1H, t, J = 7.2 Hz, H-2⁰⁰), 3.70–3.74 (1₀H₀, m, H-2⁰), 3.16

00

0

00

(2H, d, J = 7.1 Hz, H-1 ), 1.73–1.90 (4H, m, H-3 , 7 ), 1.73 (3H, s, H-5 ), 1.65 (3H, s, H-4 ), 1.25–1.40 (6H,

m, H-4 , 5 , 6 ). ¹³C-NMR (126 MHz, methanol-d₄) 209.39 (C-1 ), 167.98 (C-3), 161.90 (C-5), 159.62 (C-1),

129.61 (C-3⁰⁰), 123.16 (C-2⁰⁰), 106.71 (C-2), 103.23 (C-6), 93.56 (C-4), 49.19 (C-2⁰), 29.39 (C-3⁰, 7⁰), 25.93

(C-4⁰, 5⁰, 6⁰), 24.51 (C-4⁰⁰), 20.77 (C-1⁰⁰), 16.41 (C-5⁰⁰). DIP: m/z 304.10.

0

(E)-3-phenyl-1-(2,4,6-trihydroxy-3-(3-methylbut-2-enyl)phenyl)prop-2-en-1-one (4g). Yellow solid (13.9%),

m.p. 203–205 ^◦C. ¹H-NMR (500 MHz, methanol-d₄) d 7.49 (2H, d, J = 7.5 Hz, H-5⁰, 9⁰), 7.41 (2H, t,

J = 7.5 Hz, H-6⁰, 8⁰), 7₀.₀36 (1H, d, J = 7.4 Hz, H-7⁰), 5.97 (1H, s, H-4), 5.43 (1H, d, J = 17.5 Hz, H-2⁰), 5.19

00

0

00

(1H, t, J = 7.1 Hz, H-2 ), 3.20 (2H, d, J = 7.1 Hz, H-1 ), 2.76 (1H, d, J = 17.5 Hz, H-3 ), 1.75 (3H, s, H-5 ),

1.65 (3H, s, H-4⁰⁰). ¹³C-NMR (126 MHz, methanol-d₄) 197.43 (C-1⁰), 166.02 (C-3), 162.50 (C-1), 162.38

(C-5), 140.63 (C-4⁰), 131.66 (C-3⁰⁰), 129.72 (C-6⁰, 8⁰), 129.61 (C-7⁰), 127.36 (C-5⁰, 9⁰), 123.88 (C-2⁰⁰), 109.83

(C-2), 103.25 (C-6), 95.48 (C-4), 80.46 (C-2⁰), 44.39 (C-3⁰), 25.99 (C-5⁰⁰), 21.91 (C-1⁰⁰), 17.88 (C-5⁰⁰). DIP:

m/z 323.95.

3.1.3. Three-Step Reaction: Friedel–Crafts Acylation, Direct C-Alkylation, and Methylation (5a

and 6e)

, 5e, 6a,

Methylation: A well-mixed mixture of geranylated/prenylated acylphloroglucinols (0.5 mmol) and

K₂CO₃(3 mmol), and 20 mL of dimethylformamide (DMF) were allowed to react, with constant stirring,

Molecules 2018, 23, 2509

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for 20 min. Methyl iodide (2.3 mmol) was added dropwise into the reaction mixture and the mixture was

heated for 9 h at 80 ^◦C. Concentrated HCl (15 mL, 1 M) was added to quench the reaction, and it was

stirred for another 10 min. The resultant products were extracted with dichloromethane (DCM) followed

by cold water 3 times. The residue was puriﬁed using silica gel column chromatography (hexane:ethyl

acetate = 10:1) [26].

(E)-1-(3-(3,7-dimethylocta-2,6-dienyl)-2-hydroxy-4,6-dimethoxyphenyl)ethanone (5a). Light yellow solid

(35.0%), m.p. 72–74 ^◦C. ¹H-NMR (500 MHz, methanol-d₄) d 6.16 (1H, s, H-4), 5.11 (1H, t, J = 7.7 Hz,

H-2⁰⁰), 5.03 (1H, t, J = 7.9 Hz, H-7⁰⁰), 3.93 (3H, s, 2⁰⁰⁰), 3.90 (3H, s, H-1⁰⁰⁰),₀3₀.21 (2H, d, J = 7.1 Hz, H-1⁰⁰),

0

00

2.58 (3H, s, H-2 ), 2.02 (2H, q, J = 7.9 Hz, H-6 ), 1.92 (2H, t, J = 7.9 Hz, H-5 ), 1.73 (3H, s, H-4 ), 1.59 (3H,

s, H-10 ), 1.54 (3H, s, H-9 ). ¹³C-NMR (126 MHz, methanol-d₄) 203.39 (C-1 ), 163.67 (C-3), 162.82 (C-1),

162.11 (C-5), 133.67 (C-3⁰⁰), 130.52 (C-8⁰⁰), 124.01 (C-7⁰⁰), 122.69 (C-2⁰⁰), 108.98 (C-2), 105.31 (C-6), 86.08

(C-4), 54.71 (C-1⁰⁰⁰), 54.66 (C-2⁰⁰⁰), 39.43 (C-5⁰⁰), 31.86 (C-2⁰), 26.27 (C-6⁰⁰), 24.39 (C-10⁰⁰), 20.57 (C-1⁰⁰),

16.25 (C-9⁰⁰), 14.71 (C-4⁰⁰). DIP: m/z 332.20.

00

0

(E)-1-(3-(3,7-dimethylocta-2,6-dienyl)-2-hydroxy-4,6-dimethoxyphenyl)pentan-1-one (5e). Brown oil (46.6%).

00

¹H-NMR (500 MHz, methanol-d₄) d 6.16 (1H, s, H-4), 5.10–5.13 (1H, m, H-2 ), 5.01–5.04 (1H, m, H-7 ),

000

00

0

3.93 (3H, s, 2 ), 3.90 (3H, s, H-1 ), 3.21 (2H, d, J = 7.0 Hz, H-1 ), 2.97–3.00 (2H, m, H-2 ), 2.03 (2H, dd,

J = 6.6, 14.0 Hz, H-6⁰⁰), 1.92 (2H, t, J = 7.5 Hz, H-5⁰⁰), 1.73 (3H, s, H-4⁰⁰), 1.63 (2H, dd, J = 7.5, 14.9 Hz,

H-3⁰), 1.59 (3H, s, H-10⁰⁰), 1.54 (3H, s, H-9⁰⁰), 1.39 (2H, td, J = 7.2, 14.6 Hz, H-3⁰), 0.95 (3H, t, J = 7.4 Hz,

H-5⁰). ¹³C-NMR (126 MHz, methanol-d₄) 207.68 (C-1⁰), 164.77 (C-3), 164.37 (C-1), 163.18 (C-5), 135.05

(C-3⁰⁰), 131.96 (C-8⁰⁰), 125.45 (C-7⁰⁰), 124.17 (C-2⁰⁰), 110.48 (C-2), 106.48 (C-6), 87.49 (C-4), 56.13 (C-1⁰⁰⁰),

56.09 (C-2⁰⁰⁰), 45.23 (C-2⁰), 40.89 (C-5⁰⁰), 28.40 (C-3⁰), 27.70 (C-6⁰⁰), 25.88 (C-10⁰⁰), 23.73 (C-4⁰), 22.08

(C-1⁰⁰), 17.73 (C-9⁰⁰), 16.19 (C-4⁰⁰), 14.41 (C-5⁰). DIP: m/z 374.10.

1-(2-hydroxy-4,6-dimethoxy-3-(3-methylbut-2-enyl)phenyl)ethanone (6a). Light yellow solid (9.1%), m.p.

97–99 ^◦C. ¹H-NMR (500 MHz, methanol-d₄) d 5.95 (1H, s, H-4), 5.17 (1H, t, J = 6.3 Hz, H-₀₀2⁰⁰), 3.88 (3H,

000

00

0

s, 2 ), 3.88 (3H, s, H-1 ), 3.26 (2H, d, J = 6.8 Hz, H-1 ), 2.60 (3H, s, H-2 ), 1.76 (3H, s, H-5 ), 1.66 (3H, s,

H-4⁰⁰). ¹³C-NMR (126 MHz, methanol-d₄) 203.26 (C-1⁰), 163.52 (C-3), 163.20 (C-1), 161.68 (C-5), 131.31

(C-3⁰⁰), 122.66 (C-2⁰⁰), 109.76 (C-2), 105.99 (C-6), 85.84 (C-4), 55.45 (C-1⁰⁰⁰), 55.33 (C-2⁰⁰⁰), 33.08 (C-2⁰),

25.76 (C-4⁰⁰), 21.27 (C-1⁰⁰), 17.71 (C-5⁰⁰). DIP: m/z 264.10.

1-(2-hydroxy-4,6-dimethoxy-3-(3-methylbut-2-enyl)phenyl)pentan-1-one (6e). Light yellow solid (38.0%),

◦

00

m.p. 84–86 C. ¹H-NMR (500 MHz, methanol-d₄) d 5.95 (1H, s, H-4), 5.18 (1H, t, J = 7.0 Hz, H-2 ), 3.89

000

00

0

00

(3H, s, 2 ), 3.88 (3H, s, H-1 ), 3.26 (2H, d, J = 7.0 Hz, H-1 ), 2.96–2.99 (2H, m, H-2 ), 1.76 (3H, s, H-5 ),

1.60–1.66 (5H, m, H-3⁰, 4⁰⁰), 1.35–1.42 (2H, m, H-4⁰), 0.94 (3H, t, J = 7.3 Hz, H-5⁰). ¹³C-NMR (126 MHz,

methanol-d₄) 206.31 (C-1⁰), 163.62 (C-3), 162.88 (C-1), 161.42 (C-5), 131.39 (C-3⁰⁰), 122.69 (C-2⁰⁰), 109.96

(C-2), 106.09 (C-6), 85.82 (C-4), 55.45 (C-1⁰⁰⁰), 55.34 (C-2⁰⁰⁰), 44.20 (C-2⁰), 29.70 (C-3⁰), 27.07 (C-5⁰⁰), 25.83

(C-4⁰), 22.66 (C-1⁰⁰), 21.32 (C-4⁰⁰), 14.04 (C-5⁰). DIP: m/z 306.05.

3.2. In Vitro Soybean 15-Lipoxygenase (LOX) Inhibition Assay

Brieﬂy, sodium phosphate buffer (160

15-LOX (1.13.11.12) type I-B solution (20

temperature for 15 min. The substrate linoleic acid (10

µ

L, 100 mM, pH 8.0), test sample (10

L, 320 U/well) were mixed and incubated at room

L, 0.6 mM) solution was added to initiate

µL), and soybean

µ

the reaction. End product from the enzymatic conversion was measured at absorbance of 234 nm

over a period of 6 min and the assay was performed in triplicate. Dimethyl sulfoxide (DMSO) was

used as a solvent to dissolve test samples and reference standard. Test concentrations in the range

of 1.57 to 100

concentrations in the range of 0.00625 to 25

reference compound, nordihydroguaiaretic acid (NDGA). IC₅₀values were calculated by the nonlinear

µg/mL were used to determine the IC₅₀values of the pure compounds, while test

µg/mL were used to determine the IC₅₀value of the

Molecules 2018, 23, 2509

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regression ﬁtting curve of GraphPad Prism 5. The percentage of inhibition can be calculated by the

following formula [10,11]:

ODcontrol − ODsample

Inhibitory% =

ODcontrol

Kinetics study: Enzyme kinetics was performed similar to the above inhibition assay with slight

modiﬁcation. In brief, sodium phosphate buffer (160

soybean 15-LOX (1.13.11.12) type I-B solution (20 L, 320 U/well) were mixed and incubated for 15 min

at room temperature. About 10 L each of 4 linoleic acid substrate concentrations (0.2, 0.3, 0.4, and

µL, 100 mM, pH 9.0), test sample (10 µL), and

µ

0.5 mM) was added to initiate the enzymatic conversion. End product of the reaction was measured at

234 nm over a period of 10 min, with readings taken every 30 s. The type of inhibition (competitive,

uncompetitive, noncompetitive) was determined by nonlinear regression Michaelis–Menten enzyme

kinetics and the corresponding Lineweaver–Burk plots using 3 concentrations of each inhibitor: 0, 1.57,

and 3.13 µg/mL. All experiments were performed in triplicate and the average values and standard

errors were plotted. The K_mand V_maxvalues were calculated from the nonlinear regression ﬁtting

curve of GraphPad Prism 5.

3.3. Homology Modeling

The target amino acid sequence of soybean LOX-1 (Accession ID: P08170) was taken from

UniProtKB in FASTA format. Lipoxygenase-3 (soybean), sequestered from Research Collaboratory

for Structural Bioinformatics (RCSB) PDB (PDB ID: 1IK3), was used as the template. Homology

modeling of soybean LOX-1 was performed based on the reference protein model using Swiss model

(http://swissmodel.expas y .org/) [26–28]. The optimized model was visualized using PyMol version

1.3 and evaluated by PDBsum (https://ww w .ebi.ac.uk/pdbsum/) and PROCHECK for validation of

the 3D structure and stereochemical quality, respectively [29,30].

3.4. Molecular Docking

Docking studies were carried out using cDOCKER protocol under the receptor-ligand interaction

section in Discovery Studio^®3.1 (Accelrys, Inc., San Diego, CA, USA) based on scoring option.

The receptor was the homology model and was pretreated before docking by adding hydrogen atoms,

and all ionizable residues were set at their default protonation of pH 7.4. Meanwhile, all the 3D

structures of the ligands were built with ChemBioOfﬁce^®2008 (PerkinElmer, Inc., Waltham, MA, USA)

and minimized. The receptor was held rigid while the ligands were allowed to ﬂex during the docking

process. The heating and cooling temperature were set, respectively, to 700 K in 2000 steps and 300 K

in 5000 steps, and the grid extension was set to 10 Å. Finally, 10 ligand-binding poses were ranked

according to their cDOCKER energy, and the predicted binding interactions were analyzed [31].

3.5. Molecular Dynamic Simulation

The docked structure of the ligands and LOX-1 (homology model) were obtained from cDOCKER.

The parameterization of ligands was carried out using the Automated Topology Builder (ATB) module

implemented in the Groningen Machine for Chemical Simulation (GROMACS) 4 program [32]. The

input ﬁles for MD simulations were prepared using the “grompp” script in GROMACS, and the

ﬁeld of united-atom GROMOS96 54a7 was chosen [33]. A 10 Å isomeric truncated octahedral box of

pre-equilibrated TIP3P water was used to immerse the prepared complex structure while counterions

were added to neutralize the net charge of the system [34]. To adjust the ionic strength, 0.150 M of

NaCl was added.

At ﬁrst, position restraints on residues 499, 504, 690, and 694 were carried out by using the steepest

descent algorithm followed by energy minimization. The constant number of particles, volume, and

temperature (NVT) with the coupling scheme of V-rescale and constant number of particles, pressure,

and temperature (NPT) ensembles with the coupling scheme of Parrinello–Rahman were performed in

Molecules 2018, 23, 2509

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association with position restraint on ligand. The parameters for NVT were 310 K with a coupling

constant of 0.1 ps with duration of 1000 ps for temperature stabilization, while pressure stabilization

was done by adopting a constant pressure of 1 bar with a coupling constant of 2.0 ps with duration of

1000 ps. The particle mesh Ewald (PME) method interaction was used with a 1.4 Å cutoff for short

range and the Lincs algorithm for all bond constraints [35

with a 2 fs time step.

–37]. Simulations were performed for 10 ns

The evolution of structural properties over time, including the backbone atoms root mean square

deviations (C RMSd), were calculated from the MD trajectories using GROMACS distribution tools.

α

MM-PBSA calculations: The binding free energies were calculated based on a single trajectory

approach through the snapshots taken during MD simulation. A summation of average energy of

molecular mechanics (

G_bind) (1), while bonded (E_bond, E_angle, and E_torsion) and nonbonded (E_vdwand E_EEL) contributed

average molecular mechanics energy E_MM(2). Summation of the polar solvation free energy

evaluated using the Poisson–Boltzmann equation, G_PB, and the nonpolar contribution to exterior

water gave G_solv(3). Solvent-accessible surface area (SASA) with a probe radius of 1.4 Å was

estimated by using the Maximum Speed Molecular Surface (MSMS) algorithm. The surface tension

proportionality constant

was set to 0.0072 kcal/mol/Å²to calculate total nonpolar solvation

∆E_MM) and solvation free energy (∆G_solv) contributed binding free energy

(

∆

γ

energy [38,39]. The overall equations are summarized as follows:

∆G = ∆E_MM+ ∆G_solv

(1)

In which:

∆E_MM= ∆E_bond+ ∆E_angle+ ∆E_torsion+ ∆E_vdw+ ∆E_EEL

(2)

(3)

(4)

∆G_solv= ∆G_PB+ ∆G_SA

∆G_SA= γSA + b

3.6. ADMET and TOPKAT Analyses

ADMET analysis and toxicity proﬁling (TOPKAT) of all tHGA analogues were performed using

Discovery Studio^®3.1 (Accelrys, Inc., San Diego, CA, USA). The ADMET analysis included aqueous

solubility (AS), human intestinal absorption (HIA), blood–brain barrier (BBB), cytochrome P450 2D6

(CYP2D6), plasma protein binding (PPB), and hepatotoxicity (HT) descriptors. The toxicity prediction

proﬁle included aerobic biodegradability, mutagenicity, rodent carcinogenicity, ocular irritancy, skin

irritancy, and skin sensitization descriptors.

4. Conclusions

In an attempt to develop a new LOX inhibitor, a series of 3a (tHGA) analogues were synthesized

and evaluated for their soybean 15-LOX inhibitory activity. It was found that substituting the geranyl

chain with prenyl did not improve the inhibitory activity, and the geranylated compound 3e with the

longest aliphatic chain length on the acyl group was shown to be the most promising LOX inhibitor

from the entire series. The results from the computational studies agreed well with the bioassay results.

Therefore, the present study provides some useful insights into the way tHGA and its analogues

bind in the active site of the soybean LOX-1 enzyme. Furthermore, ADMET and TOPKAT analyses

facilitated an understanding of the drug efﬁciency and possible toxicity of the compounds. These

ﬁndings suggest that the –OH groups of the phloroglucinol moiety, the =CO group of the acyl moiety,

and the lipophilic nature of the prenylating group all contributed to the LOX inhibition. It is also

suggested that lengthening the prenylating group could further improve the bioactivity and is thus

recommended for future design of analogues.

Molecules 2018, 23, 2509

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Supplementary Materials: The following are available online: Full experimental data (including ¹H, ¹³C NMR,

ESI-MS) for all synthetic compounds are provided. Additionally, the computational work (including sequence

alignment, homology modeling, and molecular dynamic simulation) is also provided.

Author Contributions: K.S. and K.W.L. designed the research; C.H.N. performed the research and analyzed the

data; K.R., F.A., I.S.I., and F.J. contributed ideas/bioassay; K.S., C.H.N., and K.W.L. wrote the paper.

Funding: The authors wish to thank the Malaysian Ministry of Science, Technology, and Innovation (MOSTI) for

providing a research grant under the eScience grant scheme (02-01-04-SF1593).

Acknowledgments: C.H.N. acknowledges the Ministry of Higher Education (KPT) for a PhD scholarship.

The authors also acknowledge the Forest Research Institute Malaysia (FRIM) for soybean 15-LOX inhibition

assay facilities.

Conﬂicts of Interest: The authors declare no conﬂict of interest.

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Sample Availability: Samples of the compounds are not available from the authors.

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2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access

article distributed under the terms and conditions of the Creative Commons Attribution

(CC BY) license (http://creativecommons.org/licenses/by/4.0/).

Article Doi

Hits-to-lead optimization of the natural compound 2,4,6-trihydroxy-3-geranyl-acetophenone (thga) as a potent lox inhibitor: Synthesis, structure-activity relationship (sar) study, and computational assignment

DOI: 10.3390/molecules23102509

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