Research Article | Volume 10, Issue 6, November, 2022

Identification of phytocompounds from Paris polyphylla Smith as potential inhibitors against two breast cancer receptors (ERÞ and EGFR tyrosine kinase) through chromatographic and In silico approaches

Debmalya Das Gupta Saurov Mahanta Sasti Gopal Das Sanjib Kumar Das Dipayan Paul Hui Tag Pallabi Kalita Hui   

Open Access   

Published:  Sep 20, 2022

DOI: 10.7324/JABB.2022.100607
Abstract

In the current decade, the potential side effects caused by synthetic kinase domain inhibitors have paved the way for developing an alternative anti-breast cancer drug from botanical sources. Estrogen receptor-α (ERα) and epidermal growth factor receptor (EGFR) tyrosine kinase receptors play a key role in the activation of genomic and non-genomic related pathways of breast cancer progression. Paris polyphylla Smith (Melanthiaceae) is a rich source of steroidal saponins reported as an anti-breast cancer agent used among the local communities of Asian countries. In the present study, a total of 116 phytocompounds were characterized and identified from P. polyphylla rhizomes using gas chromatography–mass spectrometry and liquid chromatography–mass spectrometry tools. They were subjected to virtual screening, molecular docking, and molecular simulation analysis with these two breast cancer receptors. Among them, only three steroidal saponins, namely, diosgenin, pennogenin, and 7-ketodiosgenin acetate binding affinity with target receptors were on the higher side when compared with natural ligands. The highest affinity for the receptors ERα and EGFR tyrosine kinase was shown by 7-ketodiosgenin acetate with docking scores of −10.4 Kcal/mol and −11.2 Kcal/mol, respectively, followed by diosgenin and pennogenin. LigPlot+ analysis revealed that the selected three steroidal saponins utilized a combination of hydrogen bonding and hydrophobic interactions to align themselves more efficiently in the ligand-binding pocket of the target receptors. Molecular simulation analysis revealed a stable interaction between the phytocompounds and the target receptors. Lipinski’s rule confirmed pennogenin as the best phytocompound that could be used as a potential inhibitor against the two target breast cancer receptors (ERα and EGFR tyrosine kinase).


Keyword:     Breast cancer Paris polyphylla Steroidal saponins Molecular docking Binding affinity Molecular simulation


Citation:

Gupta DD, Mahanta S, Das SG, Das SK, Paul D, Tag H, Hui PK. Identification of phytocompounds from Paris polyphylla Smith as potential inhibitors against two breast cancer receptors (Erα and EGFR tyrosine kinase) through chromatographic and in silico approaches. J App Biol Biotech.2022;10(6):60-80. https://doi.org/10.7324/JABB.2022.100607

Copyright: Author(s). This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike license.

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1. INTRODUCTION

During the past several decades, the basic information on cancer biology has provided a ray of hope for developing gene-targeted cancer therapy. However, cancer continues to be one of the top killers of humankind [1]. Various factors aid in the progression of cancer, namely, transformation, survival, proliferation, invasion, angiogenesis, and metastasis. Among the several cancers types reported, breast cancer is one of the top killers of women globally, while in 2019, the number of females with breast cancer residing in the United States was more than 3.8 million, and the mortality of patients due to breast cancer is estimated to be around 15% [2,3]. The majority of breast cancer deaths are due to metastasis of the disease to the lungs, bone, and brain. However, death due to breast cancer has been reported more in the developing countries, especially among Black women of the African region. Several factors, including late diagnosis, and high incidence of obesity, coupled with unfavorable tumor properties, have been cited as a significant reason for increased mortality among women with breast cancer [2]. Most breast cancer (approx. 70%) cases reported are hormone receptive [4]. Being a heterogeneous disease, it expresses several hormone receptors, namely, estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2). Estrogen signaling follows both the genomic and non-genomic pathways. In the genomic pathway, ERs such as ERα and ERβ play an essential role in activating cancer-related pathways. In hormone-dependent cancer types such as breast cancer, endometrial cancer, and ovarian cancer, ERα promotes cancer formation [5]. Natural estrogen, namely, 17 β-estradiol, upregulates cellular Myc and cyclinD1 expression, stimulating the migration of epithelial cells present in mammary glands from the G1 phase to the S phase [6]. Moreover, an active ER pathway automatically increases the expression of progesterone in breast cancer cells since it is the end product of ER stimulation. Hence, blocking the active site of the ER that binds to this natural ligand could prevent the binding of the natural estrogen, thereby blocking subsequent steps for cancer progression [7].

However, estrogen signaling can also be mediated by a non-genomic pathway. This involves secondary messengers and interaction with membrane receptors such as EGFR tyrosine kinase [8]. Phosphorylation of EGFR initiates further signal transduction events such as stimulation of Src, phosphatidylinositol-3-kinase, serine/threonine-protein kinase (Akt), and mitogen-activated protein kinase, leading to cancer formation [9]. Tyrosine kinase inhibitor (TKI) drugs such as erlotinib and gefitinib bind to EGFR tyrosine kinase reversibly and block further signaling events and, hence, be able to stop the growth of cancer cells. Since breast cancer results from the dysregulation of multiple genes, targeting only a particular pathway may render the drug less potent [10]. Therefore, targeting multiple inflammatory pathways using phytocompounds from traditional medicinal plants could provide new opportunities and insights for cancer prevention and treatment. They are readily available in nature, have low cost, and potential to modulate multiple cell signaling pathways and potential check tumor development [11].

The genus Paris belonging to the family Melanthiaceae has 36 species and 10 varieties worldwide. However, the majority of the species are reported from Eurasian plains, Eastern Himalayas, and the parts of Asia, particularly in South Central and South-East regions of China, India, Nepal, Bangladesh, Bhutan, Myanmar, Laos, Thailand, Tibet, and Vietnam [12,13]. It is also found distributed inside the forest floor of moist subtropical and temperate regions of Kameng, Subansiri, Kurung Kumey, Siang, Lohit, Tirap, and Changlang districts (ca 1800–3000 m) of the Arunachal Himalayan Region (AHR) of India [14,15]. The rhizome is reported to cure several ailments such as cancer, Alzheimer’s, abnormal uterine bleeding, and leishmaniasis [16]. The local tribal communities of the Eastern Himalayan region of India use the rhizome as an antidote for snake and insect poison [17]. The steroidal saponins are the major class of compounds reported from Paris polyphylla rhizomes and also comprise triterpenoid saponins [18,19], while steroidal saponins such as dioscin, polyphyllin D, and balanitin 7 are reported as bioactive phytocompounds from the rhizome of P. polyphylla Smith [20]. Recent phytochemical studies on P. polyphylla from Eastern Himalaya have confirmed the diosgenin and other steroidal saponins, namely, pennogenin and 7-Ketodiosgenin acetate as major bioactive phytoconstituents [19]. However, molecular docking studies of individual phytoconstituents (steroidal saponins) of P. polyphylla effective against specific breast cancer receptors are not reported to date.

The purpose of this study is to identify bioactive steroidal saponins from P. polyphylla rhizome as effective inhibitors against breast cancer receptors, namely, ERα EGFR tyrosine kinase [Figure 1] through the in silico approach using AutoDock 4.1 program suite of MGL Tools 1.5.4 software. AutoDock software is widely used as a computational tool, and it is simple, cost free, more realistic in energy prediction, and uses wider conformational space in the protein. It has the edge over other methods having low conformational space constrained by several factors, namely, rigidity in receptor and bond angles and simplified scoring function based on free energies of binding [21].

Figure 1: (a) Estrogen receptor α (PDB ID: 3ERT) and (b) epidermal growth factor receptor tyrosine kinase (PDB ID: 1M17).



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2. MATERIALS AND METHODS

2.1. Sample Collection and Preparation of Ethanolic Extract of P. Polyphylla Rhizome (EEPPR) for Liquid Chromatography–Mass Spectrometry (LC–MS) Characterization

P. polyphylla rhizomes were collected from the subtropical forest area of Godak (28°21’50.38”N and 92°80’36.77”E) in Kamle district of Arunachal Pradesh (Eastern Himalayan Region of India). The voucher specimen No. 06/DD/HT/2019 dated May 11, 2019 of P. polyphylla was prepared and authenticated at BSI ASSAM Herbarium, Shillong, and the accepted name was verified at www.plantsoftheworldonline.org (POWO) and deposited to Herbarium of Arunachal University, Department of Botany, Rajiv Gandhi University, Rono Hills, Doimukh-791112, Arunachal Pradesh, for future reference [22]. Clean and oven-dried (35–40°C) P. polyphylla rhizomes were sliced and subsequently powdered. It was followed by soaking into 70% ethanol (1:10 ratio for sample: solvent) for 24 h without any heat with intermittent shaking using an orbital shaker (Cole-Parmer Model Stuart SSL1). The samples were then filtered (Whatman No. 1 filter paper) and were concentrated at a vacuum pressure of 200 Mpa, temperature 45–50°C in a rotary vacuum evaporator (IKA Model No. GS90A24, Germany). The concentrated crude extract (10% w/v) – EEPPR obtained was stored in a freezer at 4°C keeping chemical degradation at bay and was further used for LC-MS characterization of the phytocompounds.


2.2. LC–MS Characterization of Phytocompounds

The LC–MS characterization of the EEPPR was performed in LC–MS (Thermo Scientific Plus with Dionex Ultimate 3000) using a C18 column having a diameter of 150 × 2.1 mm and particle size of 1.9 μ at room temperature. The sample volume injected was 10 µL, with the mobile phase being acetonitrile and 0.2% aqueous acetic acid v/v, respectively. Sample running time was set at 20 min with flow rate fixed at 0.6 mL/min. The diode-array detection detector was set at 280 nm to obtain the respective chromatograms generated. Triple quadruple mass spectrometer (Thermo Scientific) pre-equipped with ion sources electrospray ionization with mass range for full scans m/z 50–6000 was used. The m/z values of the resolved peaks obtained were compared with m/z values obtained from public databases such as MassBank [23], METLIN [24], and HMDB [25].


2.3. Selection and Preparation of Compounds Library from P. polyphylla as Ligands

A total of 79 phytocompounds were characterized and identified from EEPPR through LC–MS studies which were used as a compound library [Table 1]. We also consulted and selected a total of 37 phytochemicals (compound library) reported earlier [19] from P. polyphylla of the AHR characterized through gas chromatography–mass spectrometry profiling. Therefore, in the present docking study, 116 phytocompounds were selected from P. polyphylla rhizome. The chemical names, structure, and molecular weight were verified from Dr. Duke’s Phytochemical and Ethnobotanical Database [26] PubChem and ChemSpider [27]. The 3D structures of the target phytochemicals were downloaded from various libraries (PubChem, zinc database, and ChemSpider). Finally, all the chemical structures were converted to PDB format with the help of PyMOLv0.99 [28].

Table 1: Phytocompounds characterized and identified from EEPPR using LC–MS tool.

S. No.Chemical namePPMMolecular mass (g/mol)
1.2,5-Dimethoxycinnamic acid3208.21
2.Kaempferol3286.24
32-Benzylsuccinic acid3208.21
4.Sinapyl aldehyde3208.073
5.6-Methoxymellein3208.21
6.2-Benzylsuccinate3208.21
7.5-[(3,4-Dihydroxyphenyl) methyl] oxolan-2-one3208.073
8.Furapiole3208.21
9.1-(2-Methoxy-3,4-methylenedioxyphenyl)-1-propanone3208.21
10.4-Methyl-4-aza-5-pregnene-3,20-dione8329.5
11.Butanedioic acid4118.09
12.Gallic acid5170.12
13Chlorogenic acid5354.31
14.Sumatriptan9295.402
15.4-(8, 9-Dihydro-8-methyl-7H-1, 3-dioxolo (4,5-H) (2,3) benzodiazepin-5-yl) benzenamine2295.34
16.Tetrahydrothiophene-2-carboxylic acid8132.18
17.3-methyl sulfolene8132.18
18.3-Oxo-3-ureidopropanoate7145.09
19.5-N-Methyloxaluric acid7146.1
20.3-Hydroxy-3-methyl-glutaric acid8162.141
21.Levoglucosan8162.141
22.2-Hydroxyadipic acid8162.140
23.3,3-diethoxy-1-propanol8148.2
24.2S-Hydroxy-hexanedioic acid8162.14
25.3-Hydroxymethyl-glutaric acid8162.141
26.L-Rhamnono-1,4-lactone8162.14
27.2-Dehydro-3-deoxy-L-rhamnonate8161.13
28.2-Dehydro-3-deoxy-D-fuconate8162.14
29.(R)-2-Ethylmalate8160.12
30.5-Ureido-4-imidazole carboxylate1170.13
31.Magnesium propionate4170.45
32.1-Naphthoic acid8172.18
33.Menadoine8172.18
34.Dehydromatricaria ester8172.18
35.Methyl (Z)-dec-2-en-4,6,8-triynoate8172.18
36.1-Hydroxy-2-naphthaldehyde8172.18
37.2-Naphthoic acid8172.18
38.3Z-Undecene-5,7,10-triynoic acid8172.18
39.4E-Undecene-6,8,10-triynoic acid8172.18
40.L-Ascorbic acid1176.12
41.2-Ketogulonolactone1194.14
42.Glucuronolactone1176.12
43.5-Dehydro-4-deoxy-D-glucuronate1175.12
44.(4S)-4,6-Dihydroxy-2,5-dioxohexanoate1175.12
45.2-Hydroxy-3-oxoadipate1176.12
46.2-Hydroxydibenzofuran8184.19
47.Dibenzo-p-dioxin8184.2
48.4-Hydroxy-4-methyl-2-oxoglutaric acid1174.11
49.D-Glucurono-6,2-lactone1176.12
50.(4S,5S)-4,5-Dihydroxy-2,6-dioxohexanoate1176.032
51.D-Galacturonolactone1176.12
52.4-Hydroxybenzophenone9198.22
53.Splitomicin9198.22
54.3,4-Dihydroxyfluorene9198.22
55.1,2-Dihydroxyfluorene9198.22
56.Dehydrosafynol9198.22
57.Capillarin9198.22
58.2-Phenyl-3-(2-furyl) prop-2-enal9198.22
59.4-Hydroxybenzophenone9198.22
60.2-Phenyl-3-(2-furyl) prop-2-enal9198.22
61.Porphobilinogen6226.22
62.Carbidopa6226.23
63.2-(2,4-Hexadiynylidene)-1,6-dioxaspiro[4.4]non-3-ene1220.23
64.D-Erythro-Biopterin1237.21
65.Orinapterin1237.21
66.Dyspropterin1237.22
67.Primapterin1237.22
68.Sepiapterin1237.22
69.N-Acetyl-D-glucosamine5221.21
70.Glycolyl-D-mannosamine5237.21
71.Deoxyeritadenine5237.22
72.2-(7’- Methylthio) heptylmalic acid4276.35
73.3-(7’- Methylthio) heptylmalic acid4276.35
74.Purpuritenin B5292.3
75.Purpuritenin A5292.3
76.Coumatetralyl5292.33
77.N-gamma-Glutamyl-S-propylcysteine2292.35
78.(all-E)-1,7-bis (4-hydroxyphenyl)-1,4,6-heptatrien-3-one5292.334
79.(2S,4S)-Monatin8292.29

2.4. Preparation of Receptor Proteins

The crystal 3D structure of ERα (PDB ID: 3ERT) and EGFR tyrosine kinase (PDB ID:1M17) was resolved by peer researchers through X-ray diffraction technique with a resolution of 1.90 Å and 2.60 Å, respectively [Figure 1]. The 3D structure of both the receptors was retrieved from the RCSB Protein Data Bank (www.rcsb.org/). The 3-D structure of the major active metabolite of tamoxifen, that is, afimoxifene docked with ERα (https://www.rcsb.org/structure/3ERT) and EGFR tyrosine kinase domain docked with 4-anilinoquinazoline inhibitor erlotinib (https://www.rcsb.org/structure/1M17), was also downloaded in required format from the RCSB PDB (https://www.rcsb.org/). After recording the active site information, the bounded natural ligands were removed from the complexes using UCSF Chimera and reconfirmed with a SWISS PDB viewer. The selected protein files were further optimized by eliminating the solvent water and unwanted residues. The result was visualized in BIOVIA Discovery Studio visualizer.


2.5. Molecular Docking Between Ligands and the Receptors

A computational docking experiment was conducted using the AutoDock 4.1 program suite using the MGL Tools 1.5.4 platform [29]. Different parameters such as polar hydrogens, Kollman charges, and atomic solvation charges were defined. The ligands, polar hydrogens, atomic charges, and flexible torsions were accordingly described for the ligands used in the docking. The corresponding docking parameter file was prepared using these parameters. The genetic algorithm was selected for the docking simulations. The final docking simulations were performed in Raccoon VS, a graphical interface for preparing AutoDock virtual screenings. The binding energy obtained from docking experiments is reported in Kcal/mol.


2.6. Molecular Simulation Studies

The online server CABS-flex 2.0 was used for the molecular simulations of selected steroidal saponins from EEPPR with the best binding affinities with target receptors following the method suggested previously [30]. The values were set as the default parameter as indicated by the server. The root mean square fluctuation (RMSF) curves were visualized using Jupyter Notebook and matplotlib, a Python package. As a result of the simulations under 100 ns, the backbone root mean square deviations (RMSDs) of protein-ligand structures were examined in detail. The RMSD was measured as the mean distance between the backbone atoms of the protein-ligand structures, and it was derived from the following equation:

large

Where, N = total number of atoms applicable in the calculation

δ = the distance between the N pairs of equivalent atoms.


2.7. Analysis of Docked Results

The docked ligands with both the receptors, namely, ERα (PDB ID: 3ERT) and EGFR tyrosine kinase (PDB ID: 1M17) were analyzed in PyMOLv0.99 [27]. The interaction analyses were performed by LigPlot+ software to visualize the active amino acid residues involved in the binding of the atoms of top-hit phytocompounds (ligands) from P. polyphylla rhizome. They were compared with the binding of amino acid residues of natural ligands with respective receptors [31]. The amino acids forming hydrogen bonds and those forming hydrophobic interactions were noted.


2.8. Druglikeness Calculations

A Lipinski’s rule of five was applied by obtaining the chemical properties and bioactivity prediction provided by the Swiss ADME server to determine if the compounds presented drug-like properties (http://www.swissadme.ch/index.php). The druglikeness was examined with the help of the following attributes: Hydrogen donors (not more than 5), hydrogen bond acceptors (not more than 10), partition coefficient (not more than 5), rotatable bonds (less than 10), total polar surface area (not more than 140), and molecular weight (less than 500 g/mol).


3. RESULTS

3.1. LC–MS Characterization of Phytocompounds

A total of 79 phytocompounds, mostly (non-volatile), were identified from the EEPPR during LC-MS characterization. The LC–MS chromatograms are shown in Figure 2, and the list of compounds obtained is presented in Table 1.

Figure 2: LC–MS chromatogram of phytocompounds obtained from EEPPR. The X-axis represents the time of sample (EEPPR) run while Y-axis shows the area percentage of the phytocompounds. S3 = Sample code for ethanolic extract of P. polyphylla rhizome.



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3.2. Selection of Top Hit, Probable Anti-Breast Cancer Phytocompounds, and Binding Energy of Ligands-Receptor Complexes

Our findings in the docking study revealed that the binding energy of the natural ligand erlotinib docked with receptor EGFR tyrosine kinase was −7.1 Kcal/mol and estradiol docked with receptor ERα was −8.1 Kcal/mol [Table 2]. The docking results of top-hit phytocompounds docked from 116 compounds characterized from EEPPR against EGFR tyrosine kinase receptors are presented in Supplementary Table 1a and b. In contrast, that of ERα (PDB ID 3ERT) receptor is given in Supplementary Table 2a and b. It was found that, of the total 116 phytocompounds docked against two breast cancer receptors EGFR tyrosine kinase and ERα, only three phytocompounds (steroidal saponins), namely, diosgenin, pennogenin, and 7-ketodiosgenin acetate, have demonstrated the best binding affinity for the target receptors EGFR tyrosine kinase and ERα which are presented in Table 2 and Figure 3. The binding affinities of the top-hit three phytocompounds (ligands) were found higher when compared with natural ligands (erlotinib and estradiol). These top-hit three phytocompounds (ligands) with higher binding affinities (indicated by lower docking score) were selected and analyzed further. The docking studies of the top hit 03 phytocompounds, namely, diosgenin, pennogenin and 7-ketodiosgenin acetate identified from EEPPR revealed that these phytocompounds (ligands) were strongly bonded to the ligand-binding pocket of each receptor. These docking studies have confirmed that the top-hit three steroidal saponins (diosgenin, pennogenin, and 7-ketodiosgenin acetate) identified from EEPPR could block the natural ligand from binding its target receptor sites which can be used for suppressing the genes that trigger the onset of metastasis.

Table 2: Docking score of the top-hit three selected phytocompounds (ligands) of steroidal saponin from EEPPR and natural ligands docked against two receptors – EGFR tyrosine kinase and ERα.

Target protein receptors PDB IDsDocking score of natural ligands (Kcal/mol)Docking score of selected top-hit phytocompounds (ligands) (Kcal/mol)
1M17Erlotinib (A)DiosgeninPennogenin7-ketodiosgenin acetate
−7.1−9.9−10.1−11.2
3ERTEstradiol (E)DiosgeninPennogenin7-ketodiosgenin acetate
−8.1−10.1−9.1−10.4
Figure 3: Structure of top-hit three phytocompounds (steroidal saponins) (a) diosgenin (b) pennogenin, and (c) 7-Ketodiosgenin acetate characterized, identified, and docked from ethanolic extract of EEPPR that has demonstrated the highest binding affinity toward the target receptors – EGFR tyrosine kinase and Era.



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3.3. Binding Affinity of the Top-Hit Phytocompounds of EEPPR to EGFR Tyrosine Kinase and ERα Receptors

In the present study, diosgenin has demonstrated an excellent binding affinity with target receptor EGFR tyrosine kinase and ERα with a docking score of −9.9 Kcal/mol and −10.1 Kcal/mol, respectively [Table 2]. Diosgenin has already been reported as a significant phytocompounds from P. polyphylla of the Eastern Himalayan Region [19]. Meanwhile, pennogenin has shown good binding affinity with receptor protein EGFR tyrosine kinase with a docking score of −10.1 Kcal/mol and also against receptor ERα (3ERT) with a docking score of −9.1 Kcal/mol. The ligand 7-ketodiosgenin acetate showed the highest binding affinity with receptor EGFR tyrosine kinase with a docking score of −11.2 Kcal/mol. It showed a good binding affinity with receptor ERα with a docking score of −10.4 Kcal/mol. The docking score (−11.2 Kcal/mol) of the 7-ketodiosgenin acetate with receptor EGFR tyrosine kinase (1M17) was found to be the best among the docking scores recorded for all the three selected phytocompounds (ligands) binds toward target receptor EGFR tyrosine kinase [Table 2]. All the three steroidal saponins were found to have a higher binding affinity with a low docking score when compared with the docking score (−7.1 Kcal/mol) of the natural ligand – erlotinib when binds with receptor EGFR tyrosine kinase and when compared with docking score (−8.1 Kcal/mol) of another natural ligand – estradiol (E) when binds with receptor ERα.


3.4. Interactions of the Top-Hit Phytocompounds (Steroidal Saponins) of P. polyphylla with Amino Acid Residues of the Two Receptors – EGFR Tyrosine Kinase and Erα

LigPlot+ software was used to visualize the active amino acid residues involved in binding of the atoms of top-hit phytocompounds (ligands) from EEPPR and was compared with the binding of amino acid residues of natural ligands with respective receptors (EGFR tyrosine kinase and ERα) and was compared with the amino acids involved when the natural ligand (erlotinib) was used [Table 3]. It was found that among the 17 amino acids involved in the natural ligand (Erlotinib)-receptor interaction, only Met 769 was found to form hydrogen bonding with the receptor Era. In comparison, the other 14 amino acids, namely, Ala719, Asp831, Gln767, Glu738, Gly695, Gly772, Ile765, Leu764, Leu768, Leu694, Leu820, Lys721, Pro770, Thr766, Thr830, and Val702, were found to form hydrophobic interactions with receptor ERα [Table 3 and Supplementary Figure 1a-c]. In the case of phytocompounds diosgenin and pennogenin, two amino acids, namely, Glu738 and Met742, were found to form hydrogen bonding with receptor EGFR tyrosine kinase. In comparison, 12 amino acids, namely, Ala719, Asp831, Cys773, Gly772, Leu694, Leu764, Leu820, Lys721, Pro770, Thr766, Thr830, and Val702, were formed hydrophobic interactions with the same receptor EGFR tyrosine kinase. However, in the case of 7-ketodiosgenin acetate, only Met769 formed a hydrogen bond with the EGFR tyrosine kinase receptor. At the same time, the other 15 amino acids, namely, Ala719, Cys773, Gln767, Glu738, Gly772, Leu694, Leu764, Leu768, Leu820, Lys721, Met742, Phe771, Pro770, Thr766, and Val702, were found to form hydrophobic interactions with receptor EGFR tyrosine kinase. The detailed interaction analysis of the top-hit phytoconstituents from EEPPR with the amino acid residues of receptor – EGFR tyrosine kinase is summarized in Table 3 and Figure 4a-d.

Table 3: Amino acids interaction (hydrophobic binding and polar H binding) of top-hit selected ligands – phytocompounds (diosgenin, pennogenin, and 7-ketodiosgenin acetate) of EEPPR docked with the specific receptors – EGFR tyrosine kinase and ERα. The values were compared with natural ligands (drugs), that is, erlotinib for receptor EGFR and estradiol for receptor ERα.

Target protein receptors PDB IDsTop-hit phytocompounds (ligands) from P. polyphylla and natural ligandsAmino acids with hydrophobic interactionsHydrogen bonding residues
EGFR tyrosine kinase (1M17)DiosgeninAla719, Asp831, Cys773, Gly772, Leu694, Leu764, Leu820, Lys721, Pro770, Thr766, Thr830, Val702Glu738, Met742
PennogeninAla719, Asp831, Cys773, Gly772, Leu694, Leu764, Leu820, Lys721, Pro770, Thr766, Thr830, Val702,Glu738 Met742
7-ketodiosgenin acetateAla719, Cys773, Gln767, Glu738, Gly772, Leu694, Leu764, Leu768, Leu820, Lys721, Met742, Phe771, Pro770, Thr766, Val702Met769
Erlotinib (natural ligand)Ala719, Asp831, Gln767, Glu738, Gly695, Gly772, Ile765, Leu764, Leu768, Leu694, Leu820, Lys721, Pro770, Thr766, Thr830, Val702Met769
ERa (3ERT)DiosgeninAla350, Asp351, Cys530, Leu384, Leu346, Leu525, Met343, Phe404, Thr347, Trp383, Val533ND
PennogeninAla350, Arg394, Leu391, Leu346, Leu525, Leu384, Leu387, Met343, Met388, Thr347, Trp383ND
7-ketodiosgenin acetateAla350, Arg394, Leu384, Leu387, Leu346, Leu391, Leu525, Lys529, Met343, Met528, Thr347, Trp383Cys530
Estradiol (natural ligand)Ala350, Gly420, Ile424, Leu346, Leu387, Leu391, Leu525, Met343, Met421, Phe404Arg394, Glu353, and His524
Figure 4: Docking scores of natural ligands (erlotinib and estradiol) and top-hit three phytocompounds (ligands) of EEPPR with selected receptors – EGFR tyrosine kinase and ERα. (a) Erlotinib + EGFR tyrosine kinase, (b) diosgenin + EGFR tyrosine kinase, (c) pennogenin + EGFR tyrosine kinase, (d) 7-ketodiosgenin acetate + EGFR tyrosine kinase, (e) estradiol + ERα, (f) diosgenin + ERα, (g) pennogenin + ERα, and (h) 7-ketodiosgenin acetate + ERα.



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Similarly, analysis of active amino acid residues involved in ligand-receptor docking in the case of receptor – ERα was also done [Table 3]. It was found that when the natural ligand (estradiol) was docked with the receptor, a total of 13 amino acids were found actively involved. The three amino acids residues, namely, Arg394, Glu353, and His524, were found to form hydrogen bonding with ERα receptor while the rest 10 amino acids, namely, Ala350, Gly420, Ile424, Leu346, Leu387, Leu391, Leu525, Met343, Met421, and Phe404, have formed hydrophobic interactions with the ERα receptor [Table 3 and Supplementary Figure 1d-f]. In the case of diosgenin, 11 amino acids, namely, Ala350, Asp351, Cys530, Leu384, Leu346, Leu525, Met343, Phe404, Thr347, Trp383, and Val533, were found to form hydrophobic interactions with ERα receptor while in the case of pennogenin, 11 amino acids, namely, Ala350, Arg394, Leu391, Leu346, Leu525, Leu384, Leu387, Met343, Met388, Thr347, and Trp383, were found to form hydrophobic interactions with the ERα receptor while no hydrogen bonding for any of the amino acids with the same receptor. However, in the case of 7-ketodiosgenin acetate, only one amino acid, namely, Cys 530, formed a hydrogen bond with the ERα receptor while other 12 amino acids, namely, Ala350, Arg394, Leu384, Leu387, Leu346, Leu391, Leu525, Lys529, Met343, Met528, Thr347, and Trp383, were found to form hydrophobic interactions with the ERα receptor. The detailed interaction analysis of the top-hit phytoconstituents (diosgenin, pennogenin, and 7-ketodiosgenin acetate) from EEPPR with the amino acid residues of the ERα receptor is summarized in Table 3 and Figure 4e-g.

It was also found that the top-hit phytocompounds – steroidal saponins (diosgenin, pennogenin, and 7-ketodiosgenin acetate) of EEPPR utilized a combination of hydrogen bonding and hydrophobic interactions to align themselves more efficiently for binding to the ligand-binding pocket of the target receptors. This strategy ultimately results in an optimal reduction of the system’s free energy, which is relatively indicated by the docking scores predicted by Autodock software. The interaction analysis of the top-hit three phytocompounds (steroidal saponins) – diosgenin, pennogenin, and 7-ketodiosgenin acetate with respective EGFR tyrosine kinase and ERα receptors is summarized in Figure 4.


3.5. Comparison of In silico Docking of Natural Ligand-Receptor with the Top-Hit Phytocompounds (Steroidal Saponins) of EEPPR

The analysis of docked ligand-receptor complexes revealed that all the top-hit three phytocompounds (of steroidal saponins), namely, diosgenin, pennogenin, and 7-ketodiosgenin acetate from EEPPR, bind at the same junction of the ligand-binding domain of the EGFR tyrosine kinase and ERα receptor kinase domain almost in the same orientation. This was found when the target phytocompounds – diosgenin, pennogenin, and 7-ketodiosgenin acetate were redocked with the complexes of the target receptor with that of its natural ligand. The top-hit three phytocompounds (diosgenin, pennogenin, and 7-ketodiosgenin acetate) as ligand has demonstrated a similar area of interaction despite the presence of the natural ligand albeit with high binding affinity, as shown in Figure 5a-f. It shows that these steroidal saponins (diosgenin, pennogenin, and 7-ketodiosgenin acetate) have a more specific binding affinity with the natural ligand-binding domain of the target receptors which can be used as a potent anti-breast cancer drug. This shows that the diosgenin, pennogenin, and 7-ketodiosgenin acetate present in P. polyphylla mimic the binding characteristics of the natural ligands – erlotinib and estradiol with the receptors EGFR tyrosine kinase and ERα, respectively.

Figure 5: Comparison of natural ligand binding with selected receptors EGFR tyrosine kinase and ERα with that of top-hit three phytocompounds (diosgenin, pennogenin, and 7-ketodiosgenin acetate) from EEPPR (a) EGFR tyrosine kinase + diosgenin + erlotinib, (b) EGFR tyrosine kinase + pennogenin + erlotinib, (c) EGFR tyrosine kinase + 7-ketodiosgenin acetate + erlotinib, (d) ERα + diosgenin + estradiol, (e) ERα + pennogenin + estradiol, and (f) ERα + 7-ketodiosgenin acetate + estradiol. It was found that compared to the natural ligand (shown in yellow), the selected three top-hit phytocompounds (shown in pink) have demonstrated higher affinity (as indicated by docking score) for the target protein receptors which could be used as an anti-breast cancer drug.



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3.6. Results of Molecular Simulation Studies for EGFR Tyrosine Kinase and ERα Receptors with the Bonded Ligands

The result of molecular simulation analysis demonstrated a stable and robust binding affinity of all the steroidal saponins, namely, diosgenin, pennogenin, and 7-ketodiosgenin acetate with EGFR tyrosine kinase and ERα receptors. The RMSF curve was found lower than that of natural ligand (denoted in black) in the case of all the three steroidal saponins, namely, diosgenin (green), and pennogenin (red) and 7-ketodiosgenin acetate (blue) at amino acids positions Ala719, Leu694, Lys721, and Thr830. However, it was also found that in addition to these amino acid residues, the RMSF curve of the steroidal saponin 7-ketodiosgenin acetate was found lower in positions Glu738, Gln767, Gly772, Leu764, Leu768, and Leu820 [Figure 6a]. This probably accounts for a more binding affinity of the steroidal saponin 7-ketodiosgenin acetate with the EGFR tyrosine kinase receptor.

Figure 6: Molecular simulation studies of the top-hit three phytocompounds, namely, diosgenin, pennogenin, and 7-ketodiosgenin acetate of EEPPR using CABS-flex 2.0 for selected proteins receptor (a) ERα receptor and (b) EGFR tyrosine kinase receptor. The curves on the plots were marked with colors: Natural ligand = black, diosgenin (L1) = green, pennogenin (L2) = red, and 7-ketodiosgenin acetate (L3) = blue. The X-axis denotes the position of active amino acids, while the Y-axis denotes RMSF values.



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Similarly, for the ERα receptor, the RMSF curve was found lower in the case of the top hit 03 phytocompounds, namely, diosgenin, pennogenin, and 7-ketodiosgenin acetate at positions Asp351, Glu353, Gly420, Gly521, Leu346, Leu387, Met343, Phe404, and Trp383. In the case of diosgenin (green) and 7-ketodiosgenin acetate (blue), additional amino acid positions were found to possess lower RMSF values for amino acids Arg394, Glu419, Leu428, Leu525, and Met421 when compared with that of natural ligand estradiol [Figure 6b]. The lower docking scores observed in the case of diosgenin (−10.1 Kcal/mol) and 7-ketodiosgenin acetate (−10.4 Kcal/mol) further supported the present findings [Table 2]. The lower RMSF value shown by a dip in the curves suggested a more stable interaction between the three steroidal saponins (diosgenin, pennogenin, and 7-ketodiosgenin acetate) and the target protein receptors. The RMSD average values for EGFR tyrosine kinase and ERα receptors were found at 4.5 ± 0.02 Å and 4.5 ± 0.02 Å, respectively. The ligand-receptor binding complexes were stable throughout the 100 ns of molecular simulation.


3.7. Drug Likeness Calculations for the Top-Hit Phytocompounds (Diosgenin, Pennogenin, and 7-Ketodiosgenin acetate) of P. polyphylla

On calculating Lipinski rule of 5 using SWISS-ADME server for the top-hit three steroidal saponins (phytocompounds), namely, diosgenin, pennogenin, and 7-ketodiosgenin acetate of EEPPR, it has been confirmed that pennogenin fulfilled all the required eligibility criteria for rational drug design for oral use. Diosgenin and 7-ketodiosgenin acetate have shown one violation each. The individual molecular weight of the three steroidal saponins and the natural ligands are presented in Table 4.

Table 4: In silico bioactivity details of the top-hit ligands (anti-breast cancer phytocompounds) – diosgenin, pennogenin, and 7-ketodiosgenin acetate identified from EEPPR along with the two natural ligands (erlotinib and estradiol) of the target receptors – EGFR tyrosine kinase and ERα.

Top-hit ligandsHBDHBAMlogPRBTPSAMWLipinski violation
Diosgenin134.94038.69414.621
Pennogenin244.09058.92430.620
7-Ketodiosgenin acetate054.26261.83470.641
Erlotinib161.481074.73393.440
Estradiol223.53040.46272.380

HBD: Hydrogen bond donors (not more than 5), HBA: Hydrogen bond acceptors (not more than 10), MlogP: Partition coefficient (Mlog P < 4.15), RB: Rotatable bonds (less than 10), TPSA: Topological polar surface area (not more than 140), MW: Molecular weight (less than 500 g/mol)


4. DISCUSSION

The present docking study of 116 phytocompounds selected and docked from P. polyphylla rhizome has revealed top hit three steroidal saponins, namely, diosgenin, pennogenin, and 7-Ketodiosgenin acetate as potential anti-breast cancer compounds, which successfully bind with ligand binding sites of their respective two breast cancer receptors – EGFR tyrosine kinase and ERα. Earlier, P. polyphylla rhizome from the Eastern Himalayan region of India and China has been reported as a rich source of diosgenin, pennogenin, and polyphyllin (major constituents of steroidal saponins) and has been reported as a potential anti-cancer agent [19,20].

Breast cancer is the most prevalent cancer type and is reported to be responsible for high mortality among the women population across the globe [3,32], with a total global population of 2.3 million in 2020 which represents 11.7% of the global cancer population [33]. The upregulated levels of sex hormones such as estrogen and progesterone may trigger the progression of breast cancer. Hence, checking the overexpression of these sex hormones by replacing them with drug analogues (ligand) that could bind to the receptor sites is fundamental for checking the onset of metabolic pathways that lead to the progression of breast cancer cells [4]. ERα and EGFR tyrosine kinase receptors play a critical role in breast cancer development. Studies have also demonstrated that PRs are significantly elevated if ER is overexpressed because PR is the end product resulting from estrogenic stimulation [6]. On the other hand, EGFR receptors are reported to play a critical role in triple-negative breast cancer cells, that is, cells that are phenotypical ER negative, PR negative, as well as HER-2 negative which limit these cells to be effective against a wide variety of drugs. The current FDA-approved anti-breast cancer drugs, namely, the neratinib, lapatinib, tucatinib, pyrotinib, sunitinib, apatinib, lenvatinib, cabozantinib, pazopanib, axitinib, sorafenib, anlotinib, fruquintinib, cediranib, donafenib, and famitinib which are available in the market are reported with several side effects. Therefore, anti-hormone therapy using phytocompounds from traditional medicinal plants is a promising approach for the treatment of breast cancer [34,35]. In the recent decade, bioinformatics tools and techniques such as molecular docking and molecular simulation studies help in the correct identification of phytochemicals as potential receptor TKIs from traditional medicinal plants which can be used for effective treatment of breast and stomach cancer [19,36]. In the present study, diosgenin, pennogenin, and 7-ketodiosgenin acetate docked and identified from EEPPR are found to block the natural ligands (erlotinib and estradiol) from binding the two target receptors (EGFR tyrosine kinase and ERα) sites and thus prevent the overexpression of two breast cancer receptors which can be used for suppressing the genes that trigger the onset of metastasis. However, among the three phytocompounds identified from EEPPR, 7-ketodiosgenin acetate has demonstrated the highest binding affinity with receptor EGFR tyrosine kinase with the lowest docking score of −11.2 Kcal/mol but also demonstrated good binding affinity with receptor ERα with a docking score of −10.4 Kcal/mol.

The interaction analysis of diosgenin, pennogenin, and 7-ketodiosgenin acetate from EEPPR with the amino acid residues of EGFR tyrosine kinase and ERα receptors has revealed that these top-hit three phytocompounds utilized a combination of hydrogen bonding and hydrophobic interactions to align and bind themselves efficiently to the ligand-binding pocket of the target breast cancer receptors. The molecular simulation study further confirmed that the lower RMSF value demonstrated by a dip in the curves indicated stable interaction between the diosgenin, pennogenin, and 7-ketodiosgenin acetate and the target protein receptors. The ligand-receptor binding complexes were found stable throughout the 100 ns of molecular simulation. Results of the present molecular docking and molecular simulation study confirmed that diosgenin, pennogenin, and 7-ketodiosgenin acetate have a more specific binding affinity with the natural ligand-binding domain of the target receptors and they can be used as a potent anti-breast cancer drug. They could also be a potent inhibitors for viral proteases of SARS-CoV-2 [37,38], of this also implies that these three phytocompounds (diosgenin, pennogenin, and 7-ketodiosgenin acetate) from P. polyphylla mimic the binding characteristics of the natural ligands – erlotinib and estradiol with the receptors EGFR tyrosine kinase and ERα. A study on Lipinski’s rule of 5 has confirmed pennogenin as the best ligand which satisfied all the required eligibility criteria for a rational drug design for oral use, however, diosgenin and 7-ketodiosgenin acetate have demonstrated one violation each but they could also be used for the development of anti-breast cancer drug. Earlier, diosgenin from P. polyphylla rhizome has proven effective against some breast cancer cell lines such as MCF7, T47D, and MDA-MB-231 by exerting its anticancer effect following multiple pathways such as apoptosis and inhibition of cancer cells [39], and by inhibiting the overexpressed Vav 2 proteins of breast cancer cells [40]. The diosgenin was also reported to inhibit HER2 positive breast cancer cells by inhibiting the Akt signaling pathway [41,42]. However, in silico- and in vitro-based anticancer activities of pennogenin and 7-ketodisogenin acetate are not available to date. The present in silico-based study confirmed that the three steroidal saponins docked and identified from P. polyphylla rhizome have the potential to be developed as novel anti-breast cancer drugs. This has paved the way for further isolation of these three bioactive compounds for in vitro and in vivo evaluation of their anti-cancer properties.


5. CONCLUSION

Of the total 116 phytocompounds screened and characterized from EEPPR and docked against two breast cancer receptors EGFR tyrosine kinase and ERα, only three phytocompounds (steroidal saponins), namely, diosgenin, pennogenin, and 7-ketodiosgenin acetate, have demonstrated higher binding affinity toward the target breast cancer receptors. Diosgenin has shown the highest binding affinity with receptor ERα with a docking score of −10.1 Kcal/mol and pennogenin has shown the highest binding affinity with receptor EGFR tyrosine kinase with a docking score of −10.1 Kcal/mol. The binding affinity of all the three steroidal saponins was found higher with a low docking score when compared with the docking score (−7.1 Kcal/mol) of the natural ligand (erlotinib) when binding with receptor EGFR tyrosine kinase and docking score (−8.1 Kcal/mol) of another natural ligand (estradiol) when binds with receptor ERα. The interaction analyses of amino acid residues of ligand-receptor complexes revealed that the selected three steroidal saponins utilized a combination of hydrogen bonding and hydrophobic interactions. The molecular simulation analysis confirmed that the lower RMSF value shown by a dip in the curves indicated stable interaction between diosgenin, pennogenin, and 7-ketodiosgenin acetate their respective target receptors while the ligand-receptor complexes were found stable throughout the 100 ns of molecular simulation. Application of Lipinski rule of 5 using Swiss-ADME server has confirmed pennogenin as the best phytocompound (ligand) which fulfilled all the required eligibility criteria for rational drug design for oral use while diosgenin and 7-ketodiosgenin acetate have demonstrated one violation each. The present findings suggested that these steroidal saponins identified and docked from P. polyphylla rhizome could be used as potential ligands (inhibitors) against the EGFR tyrosine kinase and ERα receptors. This has conferred further opportunities for isolation, in vivo and in vitro study of the pennogenin from P. polyphylla rhizome for the development of alternative anti-breast cancer drugs.


6. STATEMENT OF DISCLOSURE

The authors hereby declare that they have no conflicts of interest.


7. ACKNOWLEDGMENTS

The corresponding author (PKH) is thankful to Science and Engineering Research Board (SERB), Department of Science and Technology (DST), New Delhi, Ministry of Science and Technology, Govt. of India, for funding support to the present work through the ECR scheme vide grant No. ECR/2016/001626 dated March 22, 2017. The authors are thankful to Mr. Arshad Khan and Mr. Satyam Sangeet for helping in carrying out the ADME and molecular simulation studies. The much needed logistic support extended by the Director of NIT Arunachal Pradesh, Yupia, and Vice-Chancellor of Rajiv Gandhi University, Rono Hills, Doimukh, Arunachal Pradesh, are deeply acknowledged.


8. AUTHORS’ CONTRIBUTIONS

All authors made substantial contributions to conception and design, acquisition of data, or analysis and interpretation of data; took part in drafting the article or revising it critically for important intellectual content; agreed to submit to the current journal; gave final approval of the version to be published; and agreed to be accountable for all aspects of the work. All the authors are eligible to be an author as per the International Committee of Medical Journal Editors (ICMJE) requirements/guidelines.


9. FUNDING

The corresponding author Pallabi Kalita Hui is deeply thankful to Science and Engineering Research Board (SERB), Department of Science & Technology (DST), New Delhi, Ministry of Science and Technology, Govt. of India for supporting this study through grant No. ECR/2016/001626 Dated 22.03.2017.


10. CONFLICTS OF INTEREST

The authors report no financial or any other conflicts of interest in this work.


11. ETHICAL APPROVALS

This study did not involve animal experiment; therefore, approval of institutional animal ethical committee (IAEC) was not required.


12. DATA AVAILABILITY

All the vital findings related to this study has been provided as both main and supplementary data.


13. PUBLISHER’S NOTE

This journal remains neutral with regard to jurisdictional claims in published institutional affiliation.

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SUPPLEMENTARY DATA

Supplementary Figure 1: (a-f) Interactions of the ligands with the receptors.



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Supplementary Table 1a: Docking results of phytoconstituents obtained from GC–MS characterization of EEPPR docked with EGFR tyrosine kinase receptor.

S. No.Compound NameBinding energy (Kcal/mol)Binding residuesHydrogen bonding residues
1.1,1-Dimethoxypropane−3.8Met742, Thr830, Leu820, Glu738, Thr766, Lys721, Leu764, Asp831ND
2.3-(2-Methoxyethoxymethoxy)-2-methylpentan-1-ol−4.9Leu768, Leu820, Val702, Leu694, Glu738, Asp831, Lys721, Thr830, Ala719, Thr766, Met742, Met769Met769
3.1,3-Diethoxy-2-propanol−4.3Thr766, Met742, leu764, Phe699, Thr830, Asp831, Lys721Thr830, Asp831, Lys721
4.2-(1-Ethoxyethoxy)-2-(2-oxiranyl) ethanol−4.7Ala719, Leu964, Leu820, Val702, Cys773, Arg817, Phe699, Asn818, Leu834, Gly833, Lys721, Asp831ND
5.Diethoxymethane−3.6Lys721, Ala719, Thr830, Leu764, Met742, Thr766, Val720ND
6.1,1,3-Triethoxypropane−4.4Lys721, Thr766, Thr830, Leu694, Ala719, Leu768, Leu820, Gln767, Val702, Met769Met769
7.1,1,3-triethoxybutane−4.4Met742, Lys721, Thr830, Asp831, Val702, Leu820, Ala719, Leu764, Thr766ND
8.D-allose−5.8Met743, Leu840, Val702, Lys731, Ile765, Leu764, Glu738, Thr830, Asp831, Ala719, Thr766Leu764, Glu738, Thr830, Asp831, Ala719, Thr766
9.Methyl palmitate−4.8Ala719, Leu820, Met742, Thr766, Thr830, Asp831, Arg817, Cys773, Val702, Met769, Leu764ND
10.Palmitic acid−5.1Ala719, Val702, Gly772, Leu820, Met769, Leu764, Thr766, Glu738, Thr830, Asp831, Lys721Asp831, Lys721
11.Ethyl palmitate−5.2Leu694, Val702, Thr830, Ala719, Glu738, Leu764, Met742, Lys721, Thr766, Leu820, Met769, Asp831Asp831
12.Trimethylsilyl palmitate−5.2Leu82076, Asp831, Phe699, Gly833, Glu734, Glu738, Ile735, Lys721, Leu723, Thr766, Val702ND
13.Methyl linoleate−5.4Ala719, Thr766, Glu738, Lys721, Phe699, Met742, Asp831, Gly695, Leu694, Leu820, Val702, Gln767, Gly772, Met769Met769
14.3,6-Octadecadienoic acid, methyl ester−5.2Val702, Leu694, Leu820, Gly772, Thr766, Thr830, Glu738, Lys721, Phe669, Asp831, Gly695ND
15.Linoleic acid−5.6Ala719, Met742, Thr766, Thr830, Asp831, Phe699, Leu694, Leu820, Val702, Glu738, Lys721Glu738, Lys721
16.(R)-(-)-14-Methyl-8-hexadecyn-1-ol−5.4Leu764, Lys721, Asp831, Leu820, Val702, Leu694, Leu768, Ala719, Thr766, Met769Met769
17.trans, trans-9,12-Octadecadienoic acid, propyl esterNAConformer generation is disallowed since too flexibleNA
18.Dichloroacetic acid, tridec-2-ynyl ester−5.2Met742, Thr530, Leu320, Thr766, Met769, Leu764, Lys738, Val732, Leu694, Asp831ND
19.Ethyl stearate−5.3Phe699, Leu723, Lys721, Glu738, Leu764, Met742, Ile720, Ala719, Val702, Thr766, Asp831ND
20.Trimethylsilyl (9Z,12Z)-9,12-octadecadienoate−5.0Phe699, Asp831, Val702, Thr830, Lys721, Thr766, Ala719, Leu820, Met769, Cys773, Arg817ND
21.Trimethylsilyl (5Z,8Z,11Z)-5,8,11-icosatrienoate−6.1Leu834, Phe699, Leu694, Val702, Leu820, Thr766, Asp831, Met742, Leu764, Lys721Lys721
22.Stearoxytrimethylsilane−5.2Val702, Asp831, Phe699, Glu738, Thr766, Ala719, Leu820, Lys721Lys721
23.2-Oxiranylmethyl palmitate−5.0Gly695, Val702, Lys721, Asp831, Met742, Glu738, Thr830, Thr766, Ile720, Ala719, Leu820, Leu694ND
24.Trimethylsilyl (5Z,8Z)-7,7-dimethyl-5,8-icosadienoate−5.5Gly695, Gly772, Leu820, Ala719, Lys721, Asp831, Arg817, Phe699, Leu768, Val702, Leu694, Met769ND
25.Trimethylsilyl tetracosanoate−5.6Leu768, Gly772, Met769, Lys721, Val702, Asp813, Lys851, Leu834, Phe699, Asp831, Ala719, Thr766, Leu694, Leu820, Arg817Arg817
26Stigmasta-4,7,22-trien-3-a-ol−9.0Leu694, Gly772, Cys773, Met769, Lys721, Phe699, Asp831, Val702, Ala719, Leu820, Asp831Asp831
277b-DehydrodiosgeninNAConformer generation is disallowed since too flexibleNA
28.Stigmast-5-en-3-ol−8.1Leu723, Lys730, Lys851, Asn818, Cys773, Arg817, Leu694, Leu820, Asp831, Met769, Ala719, Glu738, Thr766, Thr830, Val702, Lys721, Phe699, Ala698, Ala731, Glu734ND
29.Stigmast-5-en-3-yl (9Z)-9-octadecenoate−8.1Leu723, Lys730, Lys851, Asn818, Cys773, Arg817, Leu694, Leu820, Asp831, Met769, Ala719, Glu738, Thr766, Thr830, Val702, Lys721, Phe699, Ala698, Ala731, Glu734ND
30.Trimethyl (octacosyloxy) silane−5.5Ala719, val720, Met769, Gly722, Leu764, Phe699, Leu834, Asp813, Lys851, Arg817, Asp831, Thr830, Glu738, Lys721, Met742, Thr766, Leu764, Leu820ND
31.3b -Acetoxystigmasta-4,6,22-triene−9.1Ala719, Thr830, Val702, Lys721, Asp813, Pro853, Leu834, Lys851, Arg817, Phe699, Asp831, Leu820, Thr766ND
32.Silane, trimethyl (stigmasta-5,22-dien-3beta-yloxy)−9.0Thr766, Ala719, Val702, Lys721, Phe699, Lys851, Pro853, Asp813, Asp831, Thr830, Leu820ND
33.Diosgenin−9.9Ala719, Asp831, Cys773, Gly772, Leu694, Leu764, Leu820, Lys721, Pro770, Thr766, Thr830, Val702Glu738, Met742
34.Stigmast-5-ene, 3 beta-(trimethylsiloxy), (24S)−9.0Thr766, Leu820, Thr830, Lys721, Phe699, Asp813, Lys851, Pro853, Asp831, Val702, Ala719ND
35.7-Ketodiosgenin acetate−11.2Pro770, Gly772, Cys773, Leu768, Ala719, Thr766, Leu820, Leu764, Met742, Lys721, Thr830, Glu738, Val702, Phe771, Leu694, Met769Met769
36.7 b-hydroxydiosgeninNAConformer generation is disallowed since too flexibleNA
37.Pennogenin−10.1Ala719, Asp831, Cys773, Gly772, Leu694, Leu764, Leu820, Lys721, Pro770, Thr766, Thr830, Val702Glu738 Met742

Supplementary Table 1b: Docking results of phytoconstituents obtained from LC–MS characterization of EEPPR docked with EGFR tyrosine kinase receptor.

S. No.Compound nameBinding energy (Kcal/mol)Binding residuesHydrogen bonding residues
1.2,5-Dimethoxycinnamic acid−6.3Leu820, Met769, Ile765, Leu764, Thr766, Lys721, Val702, Asp831, Ala719Ala719
2.Kaempferol−6.1Leu768, Gly772, Leu820, Leu694, Thr766, Thr830, Asp831, Glu738, Ala719, Met769, Lys721Met769, Lys721
3.2-Benzylsuccinic acid−6.6Leu764, Met742, Thr830, Leu820, Val702, Thr766, Ile765, Ile720, Ala719, Glu738, Lys721Ala719, Glu738, Lys721
4.Sinapyl aldehyde−6.2Thr766, Thr830, Lys721, Phe699, Asn818, Asp831, Val702, Met742ND
5.6-Methoxymellein−7.0Thr766, Ala719, Lys721, Val702, Leu694, Gly772, Leu820, Leu768, Gln767, Met769Gln767, Met769
6.2-Benzylsuccinate−6.7Met742, Thr766, Leu764, Leu820, Val702, Thr830, Asp831, Glu738, Lys721Asp831, Glu738, Lys721
7.5-[(3,4-Dihydroxyphenyl) methyl] oxolan-2-one−6.9Glu738, Thr766, Met742, Thr830, Leu764, Val702, Leu820, Ala719, Leu768, Met769, Gln767Met769, Gln767
8.Furapiole−6.7Leu820, Glu738, Asp831, Thr830, Thr766, Lys721, Ala719, Val702ND
9.1-(2-Methoxy-3,4-methylenedioxyphenyl)-1-propanone−5.7Glu738, Lys721, Thr766, Leu694, Ala719, Val702, Leu820, Asp831, Thr830ND
10.4-Methyl-4-aza-5-pregnene-3,20-dione-7.8Gly772, Met769, Cys773, Val702, Asp831, Thr830, Glu738, Ala719, Leu820, Pro770, Leu694, Lys721Lys721
11.Butanedioic acid−5.8Thr530, Leu620, Thr766, Thr764, Lys721ND
12.Gallic acid−6.2Glu738, Lys721, Thr766, Leu694, Ala719, Val702, Leu820, Asp831, Thr830Leu820
13Chlorogenic acid−6.5Thr766, Thr766, Thr830, Lys721, Phe699, Asp831, Val702, Met742Met742,
14.Sumatriptan−6.7Met769, Gly772, Asp831, Leu694, Leu820, Val702, Lys721, Thr830, Met742, Thr766ND
15.4-(8, 9-Dihydro-8-methyl-7H-1, 3-dioxolo (4,5-H) (2,3) benzodiazepin-5-yl) benzenamine−4.9Thr830, Leu820, Leu820, Val702, Glu738, Ala719Glu738
16.Tetrahydrothiophene-2-carboxylic acid−4.4Met742, Thr766, Thr830, Asp831, Lys721Thr830, Asp831, Lys721
17.3-methyl sulfolene−4.8Thr830, Leu820, Thr766, Leu764, Lys721ND
18.3-Oxo-3-ureidopropanoate−5.2Leu820, Thr830, Lys721, Val702, Thr766, Ala719, Leu764Thr766, Ala719, Leu764
19.5-N-Methyloxaluric acid−5.1Leu820, Ala719, Asp831, Met742, Thr830, Thr766, Val702, Lys721, Glu738Lys721, Glu738
20.3-Hydroxy-3-methyl-glutaric acid−5.4Lys721, Ile765, Thr830, Leu764, Thr766, Ala719, Asp831, Glu738Ala719, Asp831, Glu738
21.Levoglucosan−5.3Thr830, Ala719, Leu820, Val702, Lys721, Thr766Thr766
22.2-Hydroxyadipic acid−5.1Asp831, Met742, Val702, Lys721, Thr766, Ala719, Leu764Lys721, Thr766, Ala719, Leu764
23.3,3-diethoxy-1-propanol−4.8Thr830, Ala719, Ile720, Lys721, Met742, Asp831, Thr766, Leu764, Glu738Asp831, Thr766, Leu764, Glu738
24.2S-Hydroxy-hexanedioic acid−5.1Ile720, Val702, Leu820, Met742, Thr766, Ala719, Asp831, Thr830, Lys721, Glu738Asp831, Thr830, Lys721, Glu738
25.3-Hydroxymethyl-glutaric acid−5.4Asp831, Met742, Thr830, Val702, Ile765, Glu738, Lys721, Thr766, Ala719, Leu764Glu738, Lys721, Thr766, Ala719, Leu764
26.L-Rhamnono-1,4-lactone−5.2Ala719, Leu820, Thr830, Met742, Asp831, Lys721, Glu738, Thr766, Gln767Lys721, Glu738, Thr766, Gln767
27.2-Dehydro-3-deoxy-L-rhamnonate−5.5Ile765, Glu738, Met742, Thr830, Leu764, Ala719, Asp831, Lys721, Thr766Ala719, Asp831, Lys721, Thr766
28.2-Dehydro-3-deoxy-D-fuconate−4.8Leu820, Thr830, Thr766, Lys721, Asp831Lys721, Asp831
29.(R)-2-Ethylmalate−5.2Leu820, Met742, Leu764, Thr766, Lys721, Thr830, Asp831Lys721, Thr830, Asp831
30.5-Ureido-4-imidazole carboxylate−5.8Val720, Ile720, Leu764, Leu820, Ala719, Asp831, Thr830, Thr766, Lys721Asp831, Thr830, Thr766, Lys721
31.Magnesium propionate−1.4Asn818, Asp831, His811, Asp813ND
32.1-Naphthoic acid−7.3Leu764, Val702, Ala719, Thr830, Met742, Thr766, Lys721, Glu738, Asp831Lys721, Glu738, Asp831
33.Menadoine−7.1Leu764, Lys721, Ala719, Val702, Leu820, Thr830, Glu738, Thr766, Asp831Asp831
34.Dehydromatricaria ester−4.7Thr766, Thr830, Leu820, Val702, Phe699, Gly695ND
35.Methyl (Z)-dec-2-en-4,6,8-triynoate−5.2Met769, Thr766, Gly772, Leu820, Ala719, Leu764, Met742, Thr830, Lys721, Asp831, Val702, Leu694, Glu738Glu738
36.1-Hydroxy-2-naphthaldehyde−6.7Met742, Thr766, Leu764, Val702, Lys721, Thr830, Leu820, Glu738, Asp831Asp831
37.2-Naphthoic acid−6.7Leu820, Val702, Ala719, Thr766, Thr830, Asp831, Lys721Asp831, Lys721
38.3Z-Undecene-5,7,10-triynoic acid−5.7Val702, Thr766, Leu764, Ala719, Ile720, Lys721, Asp831, Phe699ND
39.4E-Undecene-6,8,10-triynoic acid−5.8Lys721, Val702, Ala719, Leu768, Asp831, Phe699, Leu820, Met769Met769
40.L-Ascorbic acid−5.6Leu764, Thr830, Ala719, Leu820, Met742, Asp831, Glu738, Gln737, Thr766, Lys721Asp831, Glu738, Gln737, Thr766, Lys721
41.2-Ketogulonolactone−5.1Leu820, Ala719, Asp831, Met742, Thr830, Thr766, Val702, Lys721, Glu738Lys721, Glu738
42.Glucuronolactone−5.1Val702, Leu820, Thr766, Thr830, Asp831, Lys721Thr830, Asp831, Lys721
43.5-Dehydro-4-deoxy-D-glucuronate−4.6Leu820, Val702, Glu738, Leu764, Met742, Thr766, Thr830, Asp831, Lys721Thr830, Asp831, Lys721
44.(4S)-4,6-Dihydroxy-2,5-dioxohexanoate−5.3Ile765, Val702, Ile720, Glu738, Met742, Asp831, Thr830, Leu820, Ala719, Thr766, Leu764, Lys721Ala719, Thr766, Leu764, Lys721
45.2-Hydroxy-3-oxoadipate−5.4Thr766, Val702, Leu820, Met742, Ala719, Leu764, Glu738, Lys721, Asp831, Thr830Ala719, Leu764, Glu738, Lys721, Asp831, Thr830
46.2-Hydroxydibenzofuran−7.5Ala719, Leu820, Thr766, Thr830, Asp831, Lys721, Glu738Lys721, Glu738
47.Dibenzo-p-dioxin−6.9Glu738, Lys721, Met742, Thr830, Thr766, Asp831, Leu820, Ala719, Met769, Gln767ND
48.4-Hydroxy-4-methyl-2-oxoglutaric acid−5.1Asp831, Met742, Thr766, Leu820, Lys721, Thr830Lys721, Thr830
49.D-Glucurono-6,2-lactone−5.5Leu820, Ala719, Lys721, Asp831, Thr830, Thr766Lys721, Asp831, Thr830, Thr766
50.(4S,5S)-4,5-Dihydroxy-2,6-dioxohexanoate−6.2Val702, Leu820, Met742, Thr830, Thr766, Asp831, Ala719, Met769, Gln767ND
51.D-Galacturonolactone−5.3Ala719, Met742, Thr830, Asp831, Lys721, Thr766Thr830, Asp831, Lys721, Thr766
52.4-Hydroxybenzophenone−7.3Leu764, Ile720, Lys721, Phe699, Asp831, Val702, Thr830, Thr766, Ile765, Ala719Ala719
53.Splitomicin−7.7Gln767, Ala719, Met769, Leu820, Leu694, Val702, Thr766ND
54.3,4-Dihydroxyfluorene−7.8Asp831, Glu738, Leu820, Val702, Ala719, Thr766, Thr830, Lys721Lys721
55.1,2-Dihydroxyfluorene−7.7Leu694, Leu820, Val702, Ala719, Thr830, Thr766, Asp831, Lys721Asp831, Lys721
56.Dehydrosafynol−5.6Phe699, Val702, Leu820, Ala719, Gly772, Asp831, Lys721, Met769Met769
57.Capillarin−7.7Leu764, Val702, Lys721, Met742, Thr766, Glu738, Thr830, Leu820, Met769, Asp831Asp831
58.2-Phenyl-3-(2-furyl) prop-2-enal−6.2Leu820, Asp831, Val702, Thr830, Lys721, Thr766, Ala719, Met769Met769
59.4 N-Acetyl-D-glucosamine−5.4Lys721, Thr830, Asp831, Gln767, Leu820, Met769, Ala719, Leu764, Met742, Thr766Thr766
60.2-Phenyl-3-(2-furyl) prop-2-enal!!−5.1Leu820, Ala719, Asp831, Met742, Thr830, Thr766, Val702, Lys721, Glu738Lys721, Glu738
61.Porphobilinogen−6.1Gly772, Leu768, Leu820, Val702, Ala719, Asp831, Lys721, Met769, Thr766, Thr830Asp831, Lys721, Met769, Thr766, Thr830
62.Carbidopa−6.7Ala719, Leu768, Leu820, Val702, Lys721, Asp831, Thr830, Met742, Thr766, Gln767, Met769Thr766, Gln767, Met769
63.2-(2,4-Hexadiynylidene)-1,6-dioxaspiro[4.4]non-3-ene−5.6Gly772, Leu694, Thr766, Lys721, Leu764, Thr830, Met742, Ala719, Met769, Pro770ND
64.D-Erythro-Biopterin−7Thr830, Asp831, Leu694, Val702, Gly772, Ala719, Leu820, Leu768, Thr766, Glu738Glu738
65.Orinapterin−6.5Leu694, Leu820, Asp831, Lys721, Glu738, Val702, Thr766, Ala719, Met769, Thr830Thr830
66.Dyspropterin−6.7Leu764, Met742, Thr766, Ala719, Val702, Leu820, Asp831, Lys721Lys721
67.Primapterin−6.7Lys721, Ala719, Val702, Thr766, Met742, Thr830, Asp831, Leu820, Leu764Leu764
68.Sepiapterin−6.3Arg817, Val702, Thr830, Ala719, Leu764, Thr766, Glu738, Met742, Leu820, Asp831Asp831
69.N-Acetyl-D-glucosamine−4.6Leu764, Thr766, Trp393, Gly390, Asp831, Leu820, Phe445, Glu353, Pro325Glu323, Trp393
70.Glycolyl-D-mannosamine−5.5Leu723, Phe699, Gly833, Leu834, Asp831, Lys721, Glu738Asp831, Lys721, Glu738
71.Deoxyeritadenine−6.5Ala719, Gln767, Val702, Met742, Thr830, Leu820, Thr766, Asp831, Glu738, Lys721, Met760Asp831, Glu738, Lys721, Met760
72.2-(7’-Methylthio) heptylmalic acid−5.7Leu764, Met742, Thr830, Val702, Leu820, Ala719, Lys721, Asp831, Thr766Lys721, Asp831, Thr766
73.3-(7’-Methylthio) heptylmalic acid−5.5Leu764, Met742, Thr766, Ala719, Val702, Leu820, Leu694, Lys721, Glu738, Asp831, Thr830Lys721, Glu738, Asp831, Thr830
74.Purpuritenin B−7.5Met769, Ala719, Val702, Phe699, Lys721, Asp831, Cys773, Gly772, Leu820ND
75.Purpuritenin A−7.2Leu820, Gly695, Leu694, Thr830, Arg831, Thr766, Met742, Leu764, Lys721, Val702, Phe699ND
76.Coumatetralyl−4.8Leu694, Thr766, Thr830, Arg831, Met769, Gly772, Pro770Lys720
77.N-gamma-Glutamyl-S-propylcysteine−5.4Phe699, Leu820, Thr830, Leu764, Glu738, Met742, Thr766, Val702, Lys721, Asp831Lys721, Asp831
78.(all-E)-1,7-bis (4-hydroxyphenyl)-1,4,6-heptatrien-3-one−7.4Met742, Asp831, Thr830, Lys721, Leu820, Val702, Leu768, Leu694, Met769, Gly772, Thr766, Pro770Thr766, Pro770
79.(2S,4S)-Monatin−7.7Met742, Leu764, Ile765, Thr766, Met769, Leu820, Asp831, Ala719, Lys721, Thr830Lys721, Thr830

Supplementary Table 2a: Docking results of phytoconstituents obtained from GC–MS characterization of EEPPR docked with ERα receptor.

S. No.Compound nameBinding energy (Kcal/mol)Binding residuesHydrogen bonding residues
1.1,1-Dimethoxypropane−3.9Lys449, Glu353, Gly390, Leu387, Met357, Ile386, Trp360, Pro324ND
2.3-(2-Methoxyethoxymethoxy)-2-methylpentan-1-ol−4.1Leu536, Trp383, Met522, Leu525, Glu523, Tyr526ND
3.1,3-Diethoxy-2-propanol−4.3Glu353, Met357, Pro324, Ile386, Trp360, Glu323, Lys449, Gly390, Pro325ND
4.2-(1-Ethoxyethoxy)-2-(2-oxiranyl) ethanol−4.4Glu353, Leu346, Leu349, Ala350, Leu384, Leu525, Leu391, Leu387Glu353, Leu346
5.Diethoxymethane−3.3Met357, Trp360, Leu387, Ile386, Pro325, Arg394, Glu353, Pro324, Lys449ND
6.1,1,3-Triethoxypropane−4.2Arg394, Leu387, Leu391, Leu384, Leu525, Phe404, Met421, Met388ND
7.1,1,3-triethoxybutane−4.6Leu387, Met388, Ile424, Met421, His524, Gly521, Gly420, Leu384, Leu525, Met343, Leu346ND
8.D-allose−5.0Glu353, Ile386, Lys449, Leu387, Gly390, Arg394, Pro325, Pro324, Met357Glu353, Ile386, Lys449, Pro325
9.Methyl palmitate−5.2Leu391, leu387, Gku353, Ala350, Leu525, Thr347, Leu346ND
10.Palmitic acid−5.6Leu349, Leu391, Leu387, Met421, Leu384, Ile424, Gly420, Gly521, His524, Met343, Leu346, Leu525, Glu353, Ala350, Met388ND
11.Ethyl palmitate−5.5Leu391, Phe404, Met388, Trp383, Leu384, Leu525, Gly521, Gly420, Met343, Ile424, Met421, Leu346, Ala350, Leu349, Glu353, Leu387ND
12.Trimethylsilyl palmitate−5.6Leu354, Leu536, Trp383, Asp351, Ala350, Leu384, Phe404, Met421, Leu346, Met343, Leu525ND
13.Methyl linoleate−6.0Asp351, Thr347, Leu525, Leu391, Leu387, Ile427, Met388, Leu384, Leu349, Leu346, Phe404, Glu353, Trp383, Ala350ND
14.3,6-Octadecadienoic acid, methyl ester−5.4Tyr526, Thr347, Trp383, His524, Leu384, Met343, Ile424, Gly521, Ala350, Met388, Met522, Leu525ND
15.Linoleic acid−5.0Leu536, Val533, Pro535, Val534, Trp383, Met522, Leu525, Tyr526Val534
16.(R)-(-)-14-Methyl-8-hexadecyn-1-ol−6.0Leu384, Leu525, Leu391, Met421, Ile424, Phe404, Leu387, Met388, Glu353, Leu346, Leu349, Ala350Glu353, Leu346
17.trans, trans-9,12-Octadecadienoic acid, propyl esterNAConformer generation is disallowed since too flexibleNA
18.Dichloroacetic acid, tridec-2-ynyl ester−6.1Met421, Phe404, Ile424, Leu387, Leu391, Leu384, Gly521, Met388, Met421, Met343, Leu525, Ala350, Leu349, Leu346ND
19.Ethyl stearate−5.4Leu346, Leu387, Phe404, Asp351, Leu536, Trp383, Ala350, Leu525ND
20.Trimethylsilyl (9Z,12Z)-9,12-octadecadienoate−6.2Leu536, Ala350, Leu525, Met388, Leu384, Gly521, Leu346, Phe404, Leu387, Trp383, Met522,ND
21.Trimethylsilyl (5Z,8Z,11Z)-5,8,11-icosatrienoate−6.3Leu391, Phe404, Met388, Met422, Leu525, Trp383, Met522, Tyr526, Thr347, Glu353, Ala350, Leu346, Leu387, Leu384ND
22.Stearoxytrimethylsilane−5.8Leu391, Ala350, Phe404, Glu353, Leu346, Met343, Thr347, Trp383, Met528, Leu536, Met522, Leu525, Met388, Leu384, Ile424ND
23.2-Oxiranylmethyl palmitate−5.7Trp383, Thr347, Ala350, Leu525, Met528, Gly521, His524, Met421, Gly420, Ile424, Phe404, Leu384, Leu391, Leu346, Met388, Leu387ND
24.Trimethylsilyl (5Z,8Z)-7,7-dimethyl-5,8-icosadienoate−6.3Met421, Leu346, Leu384, Asp351, Leu354, Ala350, Trp383, Met522 Tyr526, Lys529, Leu525, Leu536, Thr347, Phe404ND
25.Trimethylsilyl tetracosanoate−6.0Met388, Phe404, Thr347, Leu346, Leu384, Leu391, Ala350, Trp383, Asp351, Lys529, Tyr526, Leu525, Leu536, Met421, Gly521, His524ND
26.Stigmasta-4,7,22-trien-3-a-ol
27.7b-DehydrodiosgeninNAConformer generation is disallowed since too many undefined stereo centersNA
28.Stigmast-5-en-3-ol−7.4Leu387, Met343, Trp383, Leu384, Leu525, Met522, Tyr526, Pro535, Val534, Val533, Leu536, Asp351, Thr347, Ala350ND
29.Stigmast-5-en-3-yl (9Z)-9-octadecenoate−7.4Leu387, Met343, Trp383, Leu384, Leu525, Met522, Tyr526, Pro535, Val534, Val533, Leu536, Asp351, Thr347, Ala350ND
30.Trimethyl (octacosyloxy) silane−6.2Gly521, Met388, Leu391, Met343, Leu387, Leu346, Ala350, Thr347, Glu353, Trp383, Leu536, Tyr526, leu525, Leu384, His524, Gly420ND
31.3b -Acetoxystigmasta-4,6,22-triene−8.6Glu523, Tyr526, Leu536, Asp351, Leu539, Trp383, Leu525, Met522ND
32.Silane, trimethyl (stigmasta-5,22-dien-3beta-yloxy)−8.8Leu384, Ala350, Met343, Leu525, Met528, Lys529, Leu536, Trp383, Leu387, Asp351ND
33.Diosgenin−10.1Met522, Tyr526, Leu539, Leu536, Asp351, Trp383ND
34.Stigmast-5-ene, 3 beta-(trimethylsiloxy), (24S)−8.5Met522, Glu523, Leu525, Lys529, Val533, Val534, Leu539, Leu536, Tyr526ND
35.7-Ketodiosgenin acetate−10.4Val533, Lys531, Pro535, Leu536, Asp351, Trp383, Leu525, Leu346, Met343, Thr347, Met528, Lys529, Cys530ND
36.7 b-hydroxydiosgeninNAConformer generation is disallowed since too many undefined stereo centersNA
37.Pennogenin−9.1Met522, Tyr526, Leu536, Val534, Asp351, Leu539, Trp383ND

Supplementary Table 2b: Docking results of phytoconstituents obtained from LC–MS characterization of EEPPR docked with ERα receptor.

S. No.Compound nameBinding energy (Kcal/mol)Binding residuesHydrogen bonding residues
1.2,5-Dimethoxycinnamic acid−5Gly366, Leu306, Leu310, Gln314, Ala318, Arg363, Ala307, Lys362, Val364, Pro365, Asp369Gly366
2.3,4-Dimethoxycinnamic acid−5.2Glu423, Met421, Ile424, Val422, Ser527, His524, Glu523, Gly420, Lys520Glu423, Ser527, Gly420
3.2-Benzylsuccinic acid−5Val364, Asp369, Gly366, Ala307, Leu310, Leu306, Ala318, Pro365, Val368, Arg363Val364, Asp369, Gly366
4.Sinapyl aldehyde−4.3Gly390, Ile386, His356, Pro324, Met357, Glu353ND
5.6-Methoxymellein−5.3Leu525, Met522, Tyr526Met522
6.2-Benzylsuccinate−5.7Met421, Ile424, Leu387, Ala350, Leu391, Phe404, Glu353, Leu346, Leu525, Met343ND
7.4-Methyl-4-aza-5-pregnene-3,20-dione−4.6Asp480, Thr483, Leu479, Leu508, Leu511, Asn455, Ile451Asp480, Thr483, Leu479
8.Furapiole−5.1Leu525, Met522, Tyr526, Glu380, leu536, Trp383ND
9.1-(2-Methoxy-3,4-methylenedioxyphenyl)-1-propanone−5.2Gly521, Leu384, Met388, Leu391, Arg394, Phe404, Ala350, Leu387, Leu346, Leu525ND
10.4-Methyl-4-aza-5-pregnene-3,20-dione−7.0Pro365, Gly366, Val368, Ala307, Leu310, Gln314, Ser317, Asp 321, Ala318, Arg363, Lys362, Val364Gly266
11.Butanedioic acid−6.0Ala307, Pro365, Val368, Leu310, Gln314, Ser317, Asp 321ND
12.Gallic acid−4.0Ala318, Arg363, Phe461, Leu462, Lys467, Asp374, Thr371Tyr525
13.Chlorogenic acid−4.8His373, Ser468, Phe461, Leu462, Lys467, Asp374, Thr371Met357
14.Sumatriptan−5.6Glu523, Asn519, Lys529, leu525, Tyr525, Met522ND
15.4-(8, 9-Dihydro-8-methyl-7H-1, 3-dioxolo (4,5-H) (2,3) benzodiazepin-5-yl) benzenamine−4.9Glu523, Asn519, Leu820, Val702, Met357, Glu353Gly390
16.Tetrahydrothiophene-2-carboxylic acid−4His373, Sre468, Phe461, Leu462, Lys467, Asp374, Thr371ND
17.3-methyl sulfolene−4.3Gly390, Ile386, His356, Pro324, Met357, Glu353Leu320
18.3-Oxo-3-ureidopropanoate−5Met357, Leu387, Pro324, Lys449, Gly390, Arg394, Glu353, Ile386Glu353
19.5-N-Methyloxaluric acid−4.5Arg503, Leu495, Leu489, Glu444, Gln441, Glu443, Ala493ND
20.3-Hydroxy-3-methyl-glutaric acid−4.2Leu308, Ala312, Asp484, Thr485, Lys481, Leu310Asp484, Thr485, Lys481, Leu310
21.Levoglucosan−4.6Ser488, Thr465, Leu462, His373, Asp374, Thr371, Lys467Thr465, His373, Asp374, Thr371
22.2-Hydroxyadipic acid−4.3Pro324, Gly390, Glu323, Ile386, Lys449, Glu353, Pro325Glu323
23.3,3-diethoxy-1-propanol−4.9Leu386, Ile386, Arg394, Gly390, Glu323, Pro324, Pro325, Glu353, Lys449, His356, Met357Glu323, Pro324, Glu353,
24.2S-Hydroxy-hexanedioic acid−3.7Ala430, Ile510, His513, Thr431, Arg434His513
25.3-Hydroxymethyl-glutaric acid−4.5Leu387, Ile386, Lys449, Glu353, Phe445, Gly390, Pro324, Arg394, Met357Ile386
26.L-Rhamnono-1,4-lactone−4.7Ile386, Gly390, Arg394, Ile326, Pro325, Leu387, Pro324, Glu353, MetIle386
27.2-Dehydro-3-deoxy-L-rhamnonate−3.9His373, Ser468, Lys467, Thr371, Asp374, Glu471His373, Thr371
28.2-Dehydro-3-deoxy-D-fuconate−4Thr485, Lys481, Asp484, Ala312, Leu310, Thr311, Met315Thr485, Lys481
29.(R)-2-Ethylmalate−3.8Ile510, Thr431, Ala430, Arg434, His513ND
30.5-Ureido-4-imidazole carboxylate−5.4Ser463, Phe461, Ser468, His373, Asp374, Lys467, Leu462, Thr465Ser463 Ser468
31.Magnesium propionate−1.6Ser432, Leu429, Ser433, Arg436ND
32.1-Naphthoic acid−6Arg434, Thr431, Ala430, His513, Ile510Ala430
33.Menadoine−5.6Arg434, Ala430, Thr431, Ile510, His513ND
34.Dehydromatricaria ester−4.1Met522, Leu525, Tyr526ND
35.Methyl (Z)-dec-2-en-4,6,8-triynoate−4.2Leu820, Ala719, Leu764, Met742, Asp831, Val702, Leu694, Glu738Leu820
36.1-Hydroxy-2-naphthaldehyde−6.4Leu346, Phe404, Ile424, Gly521, Leu384, Leu525, Ala350ND
37.2-Naphthoic acid−6.7Ala430, Ile510, His513, Gln506, Leu509, Arg434, Thr431ND
38.3Z-Undecene-5,7,10-triynoic acid−4.2Gln541, Leu489, Val316, Ser317, Asp313, Glu443, Glu444Asp313
39.4E-Undecene-6,8,10-triynoic acid−5.1Ile368, Gly390, Lys449, Met357, Pro324, Leu387, Glue353, His356, Glu323, Ile326ND
40.L-Ascorbic acid−4.7Val422, Glu423, Ile424, Met421, Gly423, Lys520, Glu523, His524Glu423, Gly423
41.2-Ketogulonolactone−4.5Ala348, Lys481, His488, Met315, Thr863, Thr485, Asp484Lys420
42.Glucuronolactone−4.3Leu310, Lys481, His488, Ala312, Met315, Thr311, Thr485, Asp484Ala312
43.5-Dehydro-4-deoxy-D-glucuronate−3.9Leu370, Glu470, Glu471, Lys467, Thr371, his474, Asp369Glu471, Asp369
44.(4S)-4,6-Dihydroxy-2,5-dioxohexanoate−4.4Trp393, Ile326, Gly390, Pro324, Glu353, Lys449, Phe445, Glu323Lys449, Glu323
45.2-Hydroxy-3-oxoadipate−3.9Ile451, Thr483, Leu508, Asp480, His476, Leu479Thr483, Asp480, His476, Leu479
46.2-Hydroxydibenzofuran−7.3Leu525, Leu346, Leu391, Phe404, Leu387, Glu353, Ala350, Leu384ND
47.Dibenzo-p-dioxin−7.7Met357, Ile386, Gly390, Lys449, Ile326, Phe445, Trp393, Arg394, Glu353, Pro324Lys449
48.4-Hydroxy-4-methyl-2-oxoglutaric acid−4.6Pro325, Ile326, Gly390, Lys449, Phe445, Arg394, Glu353, Pro324, Glu323Pro324, Glu323
49.D-Glucurono-6,2-lactone−4.5Ser463, Ser468, leu462, Lys467, His373, Asp374, Thr371, Thr465Lys467, His373, Asp374, Thr371, Thr465
50.(4S,5S)-4,5-Dihydroxy-2,6-dioxohexanoate−4.6Ile386, Lys449, Pro324, Ile326, Arg349, Glu353, Gly390, Met357Ile386, Glu353
51.D-Galacturonolactone−4.2Leu462, Ser463, Ser468, Thr465, Lys467, Thr371, His373, Asp374Ser463, Thr371, His373, Asp374
52.4-Hydroxybenzophenone−5.9Ala430, Arg434, His513, Ile510, Thr431, Ser433Ser433
53.Splitomicin−7.8Gly521, Met434, Leu436, Phe404, Ala350, Leu384, Leu525, Met421ND
54.3,4-Dihydroxyfluorene−7.3Ile424, Leu346, Met421, Phe404, Glu353, Ala350, Leu387, Leu384, Leu525ND
55.1,2-Dihydroxyfluorene−7.5Gly390, Lys449, Leu387, Ile386, Met357, Pro324, Gle353, Pro325, Phe445, Ile326, Trp393ND
56.Dehydrosafynol−5.2His513, Arg434, Gln506, Gln502, Ala505, Leu509, Ile510, Thr431Thr431
57.Capillarin−5.7Met522, Glu523, Asn519, Tyr526, Leu525ND
58.2-Phenyl-3-(2-furyl) prop-2-enal−5.3Ala430, Arg434, Thr431, Ile510, His513ND
59.4 N-Acetyl-D-glucosamine−5.9Arg394, Leu387, Phe445, ile386, Trp393, Glu327, Pro325, pro324, Gly390, Lys449, Glu353Arg394
60.2-Phenyl-3-(2-furyl) prop-2-enal!!−6.5Met522, Glu523, Tyr526ND
61.Porphobilinogen−4.3His513, Leu509, Ile510, Arg434ND
62.Carbidopa−5.1Arg477, Asp473, Glue471, Asp369, Glu470, His474Arg477, Asp473, Glue471, Asp369
63.2-(2,4-Hexadiynylidene)-1,6-dioxaspiro[4.4]non-3-ene−6.3Ala312, Asp484, Arg394, Leu387, Phe445, Trp393, Glu327, Pro325, Gly390, Lys449, Glu353Leu420
64.D-Erythro-Biopterin−5.2Ala312, Asp484, Leu310, Lys481, Arg477, Asp480, Leu308, Thr311ND
65.Orinapterin−5.5Ala318, Pro365, Ala307, Asp369, Val368, Gly366, Arg363,Ala307, Asp369, Gly366
66.Dyspropterin−5.2Ile510, His513, Arg434, Thr431, Ala430Ala430
67.Primapterin−5.6His513, Thr431, Arg434, Ser433, Ala430, Ile510Ser433
68.Sepiapterin−4.7Ala430, Ile510, Leu509, Ile510, His513, Ala369ND
69.N-Acetyl-D-glucosamine−4.2Glu323, Pro324, Trp393, Gly390, Ile326, Arg394, Phe445, Glu353, Pro325Glu323, Pro324, Trp393
70.Glycolyl-D-mannosamine−4.9Arg394, Glu323, Phe445, Pro324, Ile386, Gly390, trp360, Lys449, Met357, Glu353, Leu387, Pro325, Ile326Lys449, Glu353
71.Deoxyeritadenine−5.5Ile510, Arg343, Met347, Ser433, Ala430, Thr431, His513Ser433
72.2-(7’-Methylthio) heptylmalic acid−4.4Ale312, Leu310, Asp484, Lys481, Asp480, Arg477, Leu308, Thr485, Thr311Thr485
73.3-(7’-Methylthio) heptylmalic acid−5.2Ile386, Gly390, Lys449, Phe445, Trp393, Glu323, Ile326, Pro325, pro324, Glu353, Leu387Pro325, pro324, Glu353
74.Purpuritenin B−6.9Met522, Tyr526, Leu525, Glu523ND
75.Purpuritenin A−5.2Pro535, Tyr526, Met522, Leu536Leu536
76.Coumatetralyl−4.5Leu694, Thr523, Thr630, Arg431, Met769, Gly772, Pro770ND
77.N-gamma-Glutamyl-S-propylcysteine−4.9Glu523, Tyr526, Lleu525, Met522, Leu536, Trp383Glu523, Met522
78.(all-E)-1,7-bis (4-hydroxyphenyl)-1,4,6-heptatrien-3-one−5.9Thr431, Arg434, Ser433, Arg412, Leu429, Ala430, Ile510, His513ND
79.(2S,4S)-Monatin−5.9Leu346, Met421, Met343, Gly420, Glu419, Gly521, Thr347, Leu525, Asp351, Trp383, Ala350, Phe404, Glu353, Arg394, Leu428, Leu387Arg394
Reference

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