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. 2024 Feb 29;20(2):103–109. doi: 10.6026/973206300200103

Molecular docking analysis of flavonoids with AChE and BACE-1

Sittarthan Viswanathan 1,*, Thennavan Arumugam 2,*, Kavimani Subramanian 1,*, Rengaraj Sivaraj 3,*, Vimalavathini Ramesh 1,*, A Hannah Rachel Vasanthi 4,*
PMCID: PMC10941774  PMID: 38497082

Abstract

Flavonoids are promising therapeutics for the treatment of Alzheimer's disease (AD). Therefore, it is of interest to study the anti-AD potential of 35 flavonoids towards the inhibition of AchE and BACE-1. Hence, the physicochemical, pharmacokinetic parameters, toxicity risk and drug-likeliness of the selected 35 flavonoids were computed. Further, the molecular docking analysis of flavonoids with AChE and BACE-1 were completed. A binding energy of -10.42 kcal/mol Epicatechin gallate, -10.16 kcal/mol sterubin and -10.11 kcal/mol Fisetin was observed with AchE as potential inhibitors. Similarly, Biochainin-A -9.81kcal/mol, Sterubin -8.96 kcal/mol and Epicatechin gallate -7.4 7 kcal/mol showed with BACE-1. Thus, these flavonoids are potential leads for structure-based design of effective anti-Alzheimer's agents.

Keywords: Alzheimer's, disease, Flavonoids, BACE-1, AChE, OSIRIS

Background:

Alzheimer's disease (AD) is a chronic, progressive, irreversible neurodegenerative disorder. It is characterized by immense loss of functional deficits, and slowly destroys memory, thinking skills and eventually the ability to behaviour. The two major hallmarks of AD's is amyloid-(β) peptide-containing extracellular amyloid plaques and hyper-phosphorylated tau (p-tau) protein-containing intracellular neurofibrillary tangles (NFT) are formed in the brain [1]. The United States Food and Drug Administration (FDA) have thus far approved two categories of medications for the treatment of AD: Acetylcholinesterase inhibitors and N-methyl-D-aspartate (NMDA) receptor antagonists [2]. However, these drug classes can only provide limited and temporary relief from symptoms, in addition to causing undesirable side effects [3]. Additionally, the existing treatments for AD are only partially effective and cannot halt, reverse, or prevent the progression of the disease [4]. The neurotransmitter acetylcholine (Ach) plays an important role in learning and memory in the hippocampus. Under normal physiological conditions, Ach is hydrolysis by cholinesterase's are a common class of serine hydrolases that break down choline esters. The two most well-known types are acetylcholinesterase (AChE) and butyrylcholinesterase (BChE). Acetylcholine (ACh) is hydrolysed by AChE into choline and acetate, eliminating the neurotransmitter's action at cholinergic synapses; BChE performs some of the same functions, but its function in the brain is still unknown. The "Cholinergic hypothesis of AD" states that AD causes severe damage to cholinergic neurons in the basal forebrain, followed by neuronal loss and a decrease in the ACh synthesis and degeneration [5].

Amyloid beta (Aβ) peptides are generated through proteolytic cleavage of amyloid precursor proteins (APP) by beta-secretase (BACE-1) in a healthy brain. Usually, the proteolytic processing of APP is regulated by alpha-secretase; however, when this is suppressed, beta- and gamma-secretases take over and produces neurotoxic Aβ40/42 peptides. The sequential proteolysis of APP into Aβ40/42 is mediated by: (i) BACE-1, which cleaves APP extracellularly at Asp671 to produce a 99 amino acid beta-carboxyl terminal fragment (c99), and (ii) gamma-secretase, which cleaves c99 to release βA peptides into the extracellular space. These βA peptides then accumulate to form toxic senile plaques outside the cells [6]. In the fields of nutrition and medicine, natural herbs are crucial. The flavonoids, phenolics, alkaloids, and tannins are the chemical components of herbs that are most important. Flavonoids are polyphenolic substances that are widely found in natural herbs and are an essential component of a regular human diet. It consists of two aromatic rings including benzopyran and benzene [7, 8,9]. Flavonoids align with the characteristics of NDDs by suppressing lipid peroxidation, inhibiting inflammatory mediators, modulating gene expression, and activating antioxidant enzymes. As a result, flavonoids support the maintenance of neuron's endogenous antioxidant status, safeguarding them against neurodegeneration [10,11]. Accordingly, flavonoids are subdivided into the following subgroups; flavonols (e.g. quercetin), flavones (e.g. apigenin), isoflavones (e.g. genistein), flavanones (e.g. hesperetin), flavanols (e.g. catechin), anthocyanidins (e.g. pelargonidin), 3-hydroxy derivatives of flavan (e.g. catechin). Numerous studies have revealed that flavonoids have a wide range of pharmacological properties, involving antioxidant, anti-inflammatory, hepatoprotective, antiangiogenic, anti-diabetic, cardioprotective, neuroprotective, and anti-Alzheimer's characteristics [12, 13]. Moreover, it has been known that AChE and BACE-1 are linked to amyloid plaques and cholinergic dysfunction, which seems to encourage the development of amyloid Aβ fibrils. The most effective approach to suppress the development of Aβ42 is anti-amyloid treatment. BACE-1 inhibition is thought to be one of the most successful ways to treat AD according to the amyloid hypothesis. BACE-1 inhibitors are efficient in combating new Aβ plaques but inefficient against growth of existing plaques, suggesting early treatment with the aim of preventing initial plaque formation. Thus, inhibition of both enzymes is a highly desirable feature of AD therapy [14]. Therefore, it is of interest to investigate the potential interaction between natural phyto-constituents with AchE and BACE-1 protein linked with AD.

Methodology:

Software and Hardware:

We used online databank such as PubChem [15] and Protein Data Bank [16], Online tools such as Swiss ADMET [17], [18] OSIRIS Data Warrior 4.7.3. Using software like, AutoDockTools-1.5.6 else using protein visualizer Bio-Discovery studio.

Retrieval of target enzyme structures:

Protein Data Bank was used for retrieving the structure of the following enzymes involved in the pathogenies of AD's of Homo sapiens origin, which are recognized as targets of AChE (4EY7) & BACE-1 (5HDZ). All water molecules and hetero atom removed.

Retrieval of ligand:

The structures of 36 Compounds were retrieved from the PubChem database. These structures were used for docking studies. The selected 3D structure of the ligands was retrieved from PubChem compound database in SDF format followed by conversion in the PDB format and optimization using Bio-Discovery Studio. Structure, Compound, Molecular formula, and PubChem ID of Flavonoids present in the study shown in Table 1.

Table 1. Compound, Molecular formula, and PubChem ID of Flavonoids present in the study.

Sl. NO Compound Molecular formula PubChem ID
1 Petunidin C16H13O7 441774
2 Peonidin C16H13O6 441773
3 Pelargonidin C15H11O5 440832
4 Malvidin C17H15O7 159287
5 Delphinidin C15H11ClO7 68245
6 Cyanidin C15H11O6 128861
7 Tangeritin C20H20O7 68077
8 Luteolin C15H10O6 5280445
9 Baicalein C15H10O5 5281605
10 Apigenin C15H10O5 5280443
11 Phloridzin C21H24O10 6072
12 Phloretin C15H14O5 4788
13 Chalcone C15H12O 637760
14 Chalconaringenin C15H12O5 5280960
15 Arbutin C12H16O7 440936
16 Epicatechin gallate C22H18O11 65064
17 Gallocatechin C15H14O7 65084
18 Catechin C15H14O6 73160
19 Taxifolin C15H12O7 439533
20 Rutin C27H30O16 5280805
21 Quercitrin C21H20O11 5280459
22 Quercetin C15H10O7 5280343
23 Kaempferol C15H10O6 5280863
24 Isoharmnetin C16H12O7 5281654
25 Fisetin C15H10O6 5281614
26 Naringenin C15H12O5 932
27 Hesperidin C28H34O15 10621
28 Hesperetin C16H14O6 72281
29 Eriodictyol C15H12O6 440735
30 Sterubin C16H14O6 4872981
31 Glycitein C16H12O5 5317750
32 Genistin C21H20O10 5281377
33 Formononetin C16H12O4 5280378
34 Daidzin C15H10O4 5281708
35 Biochainin A C15H10O4 5280373
36 Donepezil C24H29NO3 3152
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Prominent active site prediction:

Prior to docking analysis, prominent active site prediction of AChE & BACE-1 were carried out by PDB Sum database https://www.ebi.ac.uk/thornton-srv/databases/cgi-bin/pdbsum/GetPage.pl?pdbcode=index.html [19].

ADME properties:

In order to predict the ADME properties of the selected flavonoid, Swiss ADME web tool was used. It is a free web tool to compute pharmacokinetics, ADME properties, drug-likeliness, and medicinal chemistry friendliness of small molecules. The import tool on the input zone of the Swiss ADME submission page was used to retrieve the compound structure from databases, converted into SMILES format databases, converted into SMILES format and then calculations were run. In some cases, the SMILE format of the compound was copied from the PubChem database and directly pasted before running. When results were loaded, they were saved as a CSV file.

Toxicity risks assessment and drug likeliness:

To assess the toxicity risks of the selected flavonoid, their SMILES were retrieved from PubChem database and illustrated in the OSIRIS Property Explorer open source program which computes toxicity risks and drug-relevant properties of compounds and provides results as safe, mild and moderate coded features.

Molecular docking:

Ligand Preparation:

Compound from different groups of the flavonoid family such as flavonones, flavonols, flavone, isoflavone, anthocyanins, flavanols, flavanonol and chalcones selected to test for their inhibitory capabilities among the selected protein. The 2-dimensional structures (2D) of 35 flavonoids were retrieved from the NCBI PubChem database in .sdf format. Whereas, the 2D structure of the ligands was prepared and converted into PDB file using Bio-Discovery Studios.

Molecular docking:

Molecular docking was performed using Autodock 1.5.6 software, based on Lamarckian Genetic Algorithm, which combines energy evaluation through grids of affinity potential to find the suitable binding position for a ligand on a given protein. Polar hydrogen atoms were added to protein targets and kollman united atomic charges were computed. The grid dimensions were 60 Å X 60 Å X 60 Å with points separated by 0.375 Å. The grid box was then allocated properly in the target to include the active residue in the center. For all ligands, random starting positions, random orientations and torsions were used. The Docking parameters Number of Genetic Algorithm (GA) runs: 25, Population size: 150, Maximum number of evaluations: 2,500,000, Maximum number of generations: 27,000 were used for this study. The structure with the lowest binding free energy and the most cluster members was chosen for the optimum docking conformation. Finally, results were visualized using Visualizer Bio-Discovery Studio [20, 21,22,23, 24].

Results & Discussion:

The main objective of this study was to explore the potential of flavonoids as a treatment for Alzheimer's disease by examining their interactions with essential proteins involved in the disease. Specifically, this study focused on docking 35 flavonoids with acetylcholinesterase and β-secretase, as shown in Figure 1. The pharmacokinetic properties of natural compounds to be considered drug candidates were based on Lipinski's Rule of Five (RO5). The Lipinski rule of five was applied to the 35 selected flavonoids using SwissADME software. The results, including Lipinski (RO5) and physicochemical properties of the docked compounds, are presented in Table 2 and Table 3, respectively. Molecules that violate more than one of these rules may cause bioavailability problems. The entire set of compounds well followed the RO5 except 7 of the compounds, out of which four compounds (Hesperidin, Procyanidin, Quercetin and Rutin) violated more than one of these rules and three compounds violated only a single rule (Phloridzin, Dephilidin and Genistein) that created the Lipinski's rule violation by having, and that can make a problem in oral bioavailability. Table 4 shows the toxicity profiles of the compounds obtained using the OSIRIS Property Explorer. This includes assessment of the potential risks of mutagenicity, tumorigenicity, irritancy, and reproductive toxicity. Among these compounds Apigenin, Kaempferol, Isoharmnetin, Fisetin and Naringenin have high risk of mutagenicity. Arbutin, Glycitein, Daidzin have a high risk of reproductive toxicity, whereas phloridzin has a mild risk of reproductive toxicity. Tangeritin and Quercetin have a high risk of mutagenic and tumorigenic effects, respectively. Genistin exhibits both tumorigenic and reproductive toxicities. However, these compounds are at high risk and do not possess good drug profiles.

Figure 1.

Figure 1

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35 Flavonoids were docked with acetylcholinesterase and β-secretase protein

Table 2. Physicochemical properties of flavonoids.

Sl. No Ligand Molecular weight No of rotatable bonds H bond donor H bond acceptor clog P Solubility log S TPSA
1 Petunidin 317.27 2 5 7 1.57 -3.27 110.38
2 Peonidin 301.27 2 4 6 1.91 -3.57 90.15
3 Pelargonidin 271.25 1 4 5 1.98 -3.55 80.92
4 Malvidin 331.3 3 4 7 1.84 -3.59 99.38
5 Delphinidin 338.7 1 6 7 1.29 -2.96 121.38
6 Cyanidin 287.25 1 5 6 1.64 -3.25 101.15
7 Tangeritin 372.37 6 0 7 3.02 -3.83 72.45
8 Luteolin 286.24 1 4 6 1.99 -2.56 107.22
9 Baicalein 270.24 1 3 5 2.34 -2.86 86.99
10 Apigenin 270.24 1 3 5 2.34 -2.86 86.99
11 Phloridzin 436.41 7 7 10 0.06 -2.41 177.14
12 Phloretin 274.27 4 4 5 2.04 -2.52 97.99
13 Chalcone 208.26 3 0 1 3.3 -3.84 17.07
14 Chalconaringenin 272.26 3 4 5 1.92 -2.66 97.99
15 Arbutin 272.25 3 5 7 -1.02 -0.91 119.61
16 Epicatechin gallate 458.37 4 8 11 2.05 -2.16 197.37
17 Gallocatechin 306.27 1 6 7 1.16 -1.47 130.61
18 Catechin 290.27 1 5 6 1.51 -1.76 110.38
19 Taxifolin 304.25 1 5 7 0.96 -1.94 127.45
20 Rutin 610.52 6 10 16 -1.26 -2.4 265.52
21 Quercitrin 448.38 3 7 11 0.58 -2.7 186.37
22 Quercetin 302.24 1 5 7 1.49 -2.49 127.45
23 Kaempferol 286.24 1 4 6 1.84 -2.79 107.22
24 Isoharmnetin 316.26 2 4 7 1.77 -2.8 116.45
25 Fisetin 286.24 1 4 6 1.84 -2.79 107.22
26 Naringenin 272.26 1 3 5 2.16 -2.64 86.99
27 Hesperidin 610.56 7 8 15 -0.81 -2.75 234.29
28 Hesperetin 302.28 2 3 6 2.09 -2.66 96.22
29 Eriodictyol 288.25 1 4 6 1.81 -2.34 107.22
30 Sterubin 302.28 2 3 6 2.09 -2.66 96.22
31 Glycitein 284.27 2 2 5 1.9 -3.04 75.99
32 Genistin 432.38 4 6 10 -0.36 -2.61 166.14
33 Formononetin 268.27 2 1 4 2.25 -3.34 55.76
34 Daidzin 254.24 1 2 4 1.97 -3.02 66.76
35 Biochainin A 284.27 2 2 5 1.9 -3.04 75.99
36 Donezepil 379.5 6 0 4 4.21 -4.35 38.77
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Table 3. Predicted ADME Properties of flavonoids.

Sl.No Ligand HIA BBB Permeate P-gp Substrate CYP1A2 inhibitor CYP2C19 inhibitor CYP2C9 inhibitor CYP2D6 inhibitor CYP3A4 inhibitor Log Kp (Skin permeation cm/s)
1 Petunidin High No Yes Yes No No No No -6.88 cm/s
2 Peonidin High No Yes Yes No No No No -6.53 cm/s
3 Pelargonidin High No Yes Yes No No Yes No -6.33 cm/s
4 Malvidin High No Yes Yes No No No No -6.73 cm/s
5 Delphinidin High No Yes No No No No No -7.50 cm/s
6 Cyanidin High No Yes Yes No No No No -7.51 cm/s
7 Tangeritin High Yes No No No Yes No Yes -6.41 cm/s
8 Luteolin High No No Yes No No Yes Yes -6.25 cm/s
9 Baicalein High No No Yes No No Yes Yes -5.70 cm/s
10 Apigenin High No No Yes No No Yes Yes -5.80 cm/s
11 Phloridzin Low No Yes No No No No No -8.58 cm/s
12 Phloretin High No No Yes No Yes No Yes -6.11 cm/s
13 Chalcone High Yes No No Yes No No No -5.38 cm/s
14 Chalconaringenin High No No Yes No Yes NO Yes -5.96 cm/s
15 Arbutin High No No No No No No No -8.92 cm/s
16 Epicatechin gallate Low No No No No No No No -8.27 cm/s
17 Gallocatechin High No No No No No No No -8.17 cm/s
18 Catechin High No Yes No No No No No -7.82 cm/s
19 Taxifolin High No No No No No No No -7.48 cm/s
20 Rutin Low No Yes No No No No No -10.2 cm/s
21 Quercitrin Low No No No No No No No -8.42 cm/s
22 Quercetin High No No Yes No No Yes Yes -7.05 cm/s
23 Kaempferol High No No Yes No No Yes Yes -6.70 cm/s
24 Isoharmnetin High No No Yes No No Yes Yes -6.90 cm/s
25 Fisetin High No No Yes No No Yes Yes -6.65 cm/s
26 Naringenin High No No Yes No Yes No Yes -5.96 cm/s
27 Hesperidin Low No Yes No No No No No -10.12 cm/s
28 Hesperetin High No Yes Yes No No No Yes -6.30 cm/s
29 Eriodictyol High No Yes No No No No Yes -6.62 cm/s
30 Sterubin High No Yes Yes No No No Yes -6.48 cm/s
31 Glycitein High No No Yes No No Yes Yes -6.30 cm/s
32 Genistin Low No No No No No No No -8.33 cm/s
33 Formononetin High Yes No Yes No No Yes Yes -5.95 cm/s
34 Daidzin High Yes No Yes No No Yes Yes -6.10 cm/s
35 Biochainin A High No No Yes No No Yes Yes -5.91 cm/s
36 Donepezil High Yes Yes No No No Yes Yes -5.58 cm/s
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Table 4. Toxicity risks predicted by OSIRIS Property Explorer.

Sl.No Ligand Mutagenicity Tumorigenicity Skin Irritation Reproductive effective
1 Petunidin Safe safe Safe safe
2 Peonidin Safe safe Safe safe
3 Pelargonidin Safe safe Safe safe
4 Malvidin Safe safe Safe safe
5 Delphinidin Safe safe Safe safe
6 Cyanidin Safe safe Safe safe
7 Tangeritin Mutagenic Tumorigenic Safe safe
8 Luteolin Safe safe Safe safe
9 Baicalein Safe safe Safe safe
10 Apigenin Mutagenic safe Safe safe
11 Phloridzin Safe safe Safe Mild
12 Phloretin Safe safe Safe safe
13 Chalcone Safe safe Safe safe
14 Chalconaringenin Safe safe Safe safe
15 Arbutin Safe safe Safe Yes
16 Epicatechin gallate Safe safe Safe safe
17 Gallocatechin Safe safe Safe safe
18 Catechin Safe safe Safe safe
19 Taxifolin Safe safe Safe safe
20 Rutin Safe safe Safe safe
21 Quercitrin Safe safe Safe safe
22 Quercetin Mutagenic Yes Safe safe
23 Kaempferol Mutagenic safe Safe safe
24 Isoharmnetin Mutagenic safe Safe safe
25 Fisetin Safe safe Safe safe
26 Naringenin Mutagenic safe Safe safe
27 Hesperidin Safe safe Safe safe
28 Hesperetin Safe safe Safe safe
29 Eriodictyol Safe safe Safe safe
30 Sterubin Safe safe Safe safe
31 Glycitein Safe safe Safe Yes
32 Genistin Safe Yes Safe Yes
33 Formononetin Safe safe Safe safe
34 Daidzin Safe safe Safe Yes
35 Biochainin A Safe safe Safe safe
36 Donezepil Safe safe Safe safe
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Molecular docking was employed using Auto-dock 1.5.6 in order to predict the interactions of the protein with its ligands. The binding mode competency of AChE, BACE-1, and the flavonoids were investigated via molecular docking. The flavonoids chosen were docked with 25 Run and compared with the reference standard, donepezil. The docking energies of the selected flavonoids indicated high binding affinities to the target receptor, as shown in Table 5. Among the docked compounds for both proteins, the top 3 ligands for AChE targets (Epicatechin galate -10.42 kcal/mol, Sterubin -10.16 kcal/mol and Fisetin -10.11 kcal/mol) and BACE-1 (Fisetin -9.81 kcal/mol, Sterubin -8.96 kcal/mol, Epicatechin gallate -7.47 kcal/mol) were compared with Donepezil as shown in 2D structures (Figure 2 and Figure 3) which depict non-covalent interactions such as van der Waals, columbic contacts, u-u interactions, and hydrogen interactions. These compounds do not have toxicity and possessed large binding energy towards the target being studied. Certain critical amino acids in the ligand-binding domains of human AchE and BACE-1 have also been identified. The major non-covalent interactions between the examined ligands and the AchE and BACE-1 ligand binding domains were explored. These amino acids have been involved in ligand interactions with AchE and BACE-1, as well as in the inhibition of the ligand-binding domains of AchE and BACE-1. In patients with Alzheimer's disease, plaques block the connections of neurons, causing messages to be delayed or lost. By reducing the breakdown of acetylcholine to the choline moiety, AChE inhibition can improve signalling [25]. Beta-secretase is known to cause the cleavage of beta-amyloid protein into beta-amyloid plaques, which are a characteristic of Alzheimer's and dementia. By suppressing beta-secretase activity, it is possible to prevent the transformation of amyloid precursor protein into insoluble beta-amyloid [26, 27,28,29].

Table 5. Autodock binding energy scoring values of compounds on AChE and BACE-1.

Sl. No Ligands Proteins
AchE 4EY7 Affinity (Kcal.mol) BACE-1 5HDZ Affinity (Kcal.mol)
1 Petunidin -7.19 -6.72
2 Peonidin -7.69 -7.07
3 Pelargonidin -7.42 -7.11
4 Malvidin -8.69 -7.01
5 Delphinidin -6.76 -6.2
6 Cyanidin -8.01 -7.08
7 Tangeritin -9.24 -6.76
8 Luteolin -5.1 -6.3
9 Baicalein -7.79 -6.96
10 Apigenin -8.87 -6.38
11 Phloridzin -7.63 -5.91
12 Phloretin -7.9 -6.81
13 Chalcone -8.06 -7.14
14 Chalconaringenin -7.49 -6.3
15 Arbutin -6.82 -6.38
16 Epicatechin gallate -10.42 -7.47
17 Gallocatechin -7.03 -7.9
18 Catechin -7.97 -6.84
19 Taxifolin -8.67 -6.58
20 Rutin -8.59 -7.04
21 Quercitrin -9.22 -7.6
22 Quercetin -8.21 -6.54
23 Kaempferol -8.08 -6.37
24 Isoharmnetin -9.16 -8.96
25 Fisetin -10.11 -9.81
26 Naringenin -8.9 -6.55
27 Hesperidin -8.51 -7.73
28 Hesperetin -9.55 -6.42
29 Eriodictyol -8.23 -6.29
30 Sterubin -10.16 -8.96
31 Glycitein -8.53 -6.55
32 Genistin -9.92 -6.84
33 Formononetin -8.38 -6.97
34 Daidzin -8.93 -7.66
35 Biochainin A -8.47 -9.81
36 Donepezil -11.03 -8.83
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Figure 2.

Figure 2

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2-D interaction diagram of top 3 ranked screened flavonoids (A) Epicatechin gallate, (B) Sterubin (C) Fisetin interacted with AChE (4EY7) and (D) Donepezil respectively.

Figure 3.

Figure 3

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2-D interaction diagram of top 3 ranked screened flavonoids (A) Fisetin, (B) Sterubin and (C) Epicatechin gallate interacted with BACE-1 (5HDZ) and (D) Donepezil respectively.

Conclusion:

Data shows that the flavonoids epicatechin gallalate, sterubin and biochanin A have high binding with targets linked with Alzheimer's disease for further considerations in vitro and in vivo.

Disclosure statement:

The authors declare no conflicts of interests.

Ethical approval:

This article does not contain any human participant and animal work.

Author contributions:

All author contributed equally.

Funding:

None declared or Self-funding

Data availability statement:

All dataset supporting this article is available within the article and its supplementary files.

Edited by P Kangueane

Citation: Viswanathan et al. Bioinformation 20(2):103-109(2024)

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Data Availability Statement

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