Nagesh S. V. S. D. N. A, Kannan I, Bairagi K. K. Pharmacophoric Evaluation of Compounds Isolated from GC-MS Analytical Method of Aqueous Extract of Azadirachta indica Leaves. Biomed Pharmacol J 2023;16(1).
Manuscript received on :06-03-2022
Manuscript accepted on :07-11-2022
Published online on: 20-01-2023
Plagiarism Check: Yes
Reviewed by: Dr. Abdalla A. Elbashir
Second Review by: Dr. Randa Salah Gomaa
Final Approval by: Dr. Patorn Piromchai

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Simhadri V. S. D. N. A. Nagesh1*, Kannan Iand Bairagi K. K.3

1Department of Pharmacology, Shri Ram Murti Smarak Institute of Medical Sciences, Bareilly.

2Department of Microbiology, Tagore Medical College and Hospital, Chennai.

3Department of Forensic Medicine, Shri Ram Murti Smarak Institute of Medical Sciences, Bareilly.

Corresponding Author E-mail: nageshsai117@gmail.com

DOI : https://dx.doi.org/10.13005/bpj/2626

Abstract

The majority of current pharmaceuticals are derived from traditional plants; one of these, Azadirachta indica, also known as neem, has a variety of therapeutic applications ranging from simple infections to cancer. All of these pharmacological effects are due to the secondary metabolites present in the various plant parts. Diverse researchers made numerous attempts to identify the active ingredients using techniques such as Gas Chromatography-Mass Spectrometry (GC-MS), High-performance liquid chromatography (HPLC), and High performance thin-layer chromatography (HPTLC), among others. The GC-MS technique is used to isolate various secondary metabolites from the leaves of an aqueous extract of A.indica. The isolated compounds were analysed for their pharmacokinetics and pharmacodynamics properties using software such as SWISSADME, OPENBABEL, Swiss target prediction, etc. The aqueous extract of A.indica yielded 13 compounds, but only 5 compounds showed the highest number of hits; those with the highest concentration were chosen to obtain the pharmacodynamic, pharmacokinetic, and toxicological profiles. All five compounds are non-toxic and can be administered orally, and molecules with specific properties are capable of modulating a variety of proteins, including some enzymes. Based on this information, we can assume that these molecules can be used as "hit" or "lead" molecules in preclinical studies.

Keywords

Azadirachta indica; GC-MS; Pharmacokinetics; Pharmacodynamic; Secondary Metabolites; SWISSADME; Swiss target prediction

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Nagesh S. V. S. D. N. A, Kannan I, Bairagi K. K. Pharmacophoric Evaluation of Compounds Isolated from GC-MS Analytical Method of Aqueous Extract of Azadirachta indica Leaves. Biomed Pharmacol J 2023;16(1).

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Nagesh S. V. S. D. N. A, Kannan I, Bairagi K. K. Pharmacophoric Evaluation of Compounds Isolated from GC-MS Analytical Method of Aqueous Extract of Azadirachta indica Leaves. Biomed Pharmacol J 2023;16(1). Available from: https://bit.ly/3GRxMlr

Introduction

Since ancient times, the use of medicinal plants to treat both common and uncommon ailments has been documented. Azadirachta indica, commonly known as Neem, is a plant that has been used traditionally to treat a variety of human diseases. It is a member of the Meliaceae family and is native to Burma and the Indian subcontinent. Melia azadirachta Linn is an alternative name for this plant. Indian lilac (English), neeb (Arabic), Azadirakhta (Persian), Margosa, Dogon yaro (certain Nigerian languages), Pokoksemambu (Malaysia), Kohomba (Sinhala), Tamar (Burmese), Nimba (Sanskrit), Vepa (Telugu), and neem are all names for the neem tree (Hindi and Bangla). It is known as Mwarobaini (Swahili) in east Africa, which literally translates to “tree of the 40” due to its ability to treat 40 different diseases1. Active components of the neem plant have been used medicinally by the AYUSH department, and modern medicine is currently employing this “divine tree” to treat a wide range of ailments, including infections, metabolic disorders, and cancer2. As evidenced by numerous research studies, every part of the plant has been examined for its pharmacological activity3, and it is well-established that this plant is used to treat a variety of diseases in numerous countries, including the Indian subcontinent4. In 1992, the United States National Academy of Sciences published a paper on “Neem”5. The chemical and biological analysis of neem discovered the existence of more than 300 bioactive substances in various plant parts, including at least 50 limonoids6. Bark, leaves, and roots contain antimicrobial, antifungal, insecticidal, antiviral, anti-malarial, antiperiodic, mosquito larvicidal, anti-inflammatory, antifertility, spermicidal, and hypoglycemic properties; they are also effective against periodontitis, gingivitis, boils, sores, splenomegaly, malaria, hyperpyrexia at childbirth, smallpox, and measles. Neem oil is employed as an intravaginal contraceptive, a treatment for vaginal infections, and a mosquito repellent7. Some of the well-established secondary metabolites, including nimbin, azadirachtin, nimbidiol, quercetin, and nimbidin1, are responsible for their pharmacological actions8, which is why, according to the World Health Organization, 80% of people rely on ethnomedicine (WHO)9. The purpose of Gas Chromatography-Mass Spectrometry (GC-MS) is to isolate various substances within a given sample, which is then used to retrieve the accessible compounds from the plant extract10. Previous research has documented the presence of countless secondary metabolites with potent antibacterial, antifungal, insecticidal, anti-inflammatory, antiviral, antioxidant, anti-cancer, and antimutagenic properties11. The objective of this study is to investigate the pharmacophoric properties of an aqueous extract of A. indica leaves.

Objective

To evaluate the various compounds present in the aqueous extract of A.indica by GC-MS analytical method.

To know the properties of Absorption, Distribution, Metabolism, Elimination and Toxicology of the major compounds obtained by analytical method

To obtain the pharmacodynamic properties for the major compounds obtained in GC-MS analysis.

Materials and Methods

The A.indica leaves were collected identified and authenticated by an expert botanist. The collected fresh leaves from the Rathinamangalam area of Chennai, Tamil Nadu, India were cleaned with fresh running tap water followed by distilled water, and dried in a shaded sunlight area after authentication which were later finely powdered. The powdered leaves were subjected to aqueous extraction by maceration. The obtained extract was subjected to quantitative chemical analysis with GC-MS to evaluate the compounds present. We further attempted to obtain from those compounds to know their pharmacokinetic and toxicological properties and their pharmacodynamic activity.

Gas chromatography-Mass Spectrometry

Analysis of A. indica‘s aqueous extract was carried out using GC-MS equipment. The GC-MS system used a TR 5MS capillary standard non-polar column with a diameter of 30 Mts, an ID of 0.25 mm, and a film thickness of 0.25 m. The flow rate of the mobile phase was set to 1.0 mL/min from the start. In the gas chromatography section, the temperature was raised from 40°C to 250°C at a rate of 5°C/min, with an injection volume of 1 microliter. The Wiley Spectral library search tool was used to analyze the outcomes of the samples immersed in chloroform over a mass spectrum of 50650 m/z12.

Preparation of ligand to know the pharmacological properties

The compounds which were retrieved from GC-MS analysis were taken up to find out their International Union of Pure and Applied Chemistry (IUPAC) names. Using the Chemicalize software and/or Pubmed compound NCBI website, we downloaded the .sdf file; by using the .sdf file, the Simplified Molecular Input Line Entry System (SMILES) for all the compounds were obtained by using an online SMILES translator. By using the same SMILES, with the help of SwissADME web tool, wherein we procured the data of physicochemical parameters, nature of solubility, pharmacokinetic parameters, druglikeliness, and medicinal properties. By using admetSAR which is an interface that is simple to utilize to search the ADME/T (Absorption, Distribution, Metabolism, Excretion, and/ Toxicity) properties of any molecule, we retrieved the toxicity profile. Predicting the most prospective macromolecular targets of a small molecule that is believed to be bioactive is done using the Swiss Target Prediction Interface, which compares small molecules to over 3000 distinct proteins from various species to find molecules that are comparable in 2D, and 3D structure.

Results

A total of 74 compounds were retrieved from the GC-MS analysis, out of which 13 compounds are showing significance (2 compounds having two peaks) and out of 13 compounds, 5 compounds had more hits, the obtained chromatogram was presented in the figure 1a and 1b. The compounds having a greater number of hits were subjected to evaluation of the pharmacodynamic properties.

Vol16No1_Pha_Sim_fig1 Figure 1a: Chromatogram of the compounds present in the aqueous extract image of A. indica obtained from GC-MS analysis.

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Vol16No1_Pha_Sim_fig2 Figure 1b: Chromatogram of the individual 13 compounds obtained from the aqueous extract image of A. indica obtained by GC-MS analysis.

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Vol16No1_Pha_Sim_tab1 Table 1: General Properties of the compounds retrieved from GC-MS analysis of aqueous extract of A.indica.

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Table 1 depicts the availability of various compounds in the aqueous extract of A. indica which may be important for the pharmacodynamic and pharmacokinetic potency and their general physicochemical properties. A total of 13 compounds are seen in the chromatogram but only 5 compounds are predominantly observed as productive based on the area and peak obtained in the chromatogram and may be responsible for pharmacological actions of aqueous extract of A.indica.

Table 2: Physicochemical Properties of the compounds retrieved from GC-MS analysis of aqueous extract of A.indica.

S. No. Name of the compound No. of heavy atoms No. of arom. heavy atoms Fraction CSP3 No. rotatable bonds No. of
H-bond acceptors
No. of
H-bond donors
Molar Refractivity Topological Polar Surface Area
(TPSA) 0A2
1. Benzaldehyde,
4-methyl
9 6 0.12 1 1 0 36.80 17.07
2. Ethanone,
1-(2-hydroxy-
5-methylphenyl)
11 6 0.22 1 2 1 43.63 37.30
3. Phenol,
2,6-dimethoxy
11 6 0.25 2 3 1 41.45 38.69
4. Eugenol 12 6 0.20 3 2 1 49.06 29.46
5. gamma-Elemene 15 0 0.60 2 0 0 70.42 0.00
6. 2(4H)-Benzofuranone,
5,6,7,7atetrahydro
-4,4,7a-trimethyl-, (R)
13 0 0.73 0 2 0 51.35 26.30
7. Cyclohexane,
1-ethenyl-1-methyl-2
-(1 methylethenyl)
-4-(1-methylethylidene)
15 0 0.60 2 0 0 70.42 0.00
8. 1H-Cycloprop[e] azulen-7-ol,
decahydro-1,1,7
-trimethyl-4-methylene-,
[1ar-(1a.alpha.,
4a.alpha.,
7.beta.,7a.beta.,
7b.alpha.)]-
16 0 0.87 0 1 1 68.34 20.23
9. Caryophyllene oxide 16 0 0.87 0 1 1 68.27 12.53
10. Caryophyllene oxide 16 0 0.87 0 1 1 68.27 12.53
11. 3,7,11,15-Tetramethyl-2-hexadecen-1-ol 21 0 0.90 13 1 1 98.94 20.23
12. Hexadecanoic
acid,
methyl ester
19 0 0.94 15 2 0 85.12 26.30
13. Phytol 21 0 0.90 13 1 1 98.94 20.23

Extracted compounds are shown in Table 2 with their, number of heavy atoms, aromatic heavy atoms (AHA), proportion CSP3, number of rotatable bonds, molar refractivity, and Topological Polar Surface Area (TPSA)13. The number of atoms is in the permissible range, molar refractivity is maintaining the range 40-130 except for compound one “Benzaldehyde, 4-methyl-” as 36.80, the polar surface area of all the compounds is also less than 140 Ao, which indicates that the compounds are lipid soluble.

The Log p Octanol-Water partition coefficient14 values of the small molecules/compounds obtained are in the range of permissible -0.4 to +5.6 range implies a good lipophilic compound except the “3,7,11,15-Tetramethyl-2-hexadecen-1-ol” and “Phytol”. All the compounds show solubility in water except the last three compounds which are moderately soluble according to their hydrophilicity.

Only “gamma-Elemene,” “Cyclohexane, 1-ethenyl-1-methyl-2-(1 methylethyl)-4-(1-methylethyliden),” and “Phytol” have a low oral bioavailability, based on the GC-MS analysis of an aqueous extract of A.indica pharmacokinetic property15

All these compounds cross BBB15 except 4 compounds which are “gamma-Elemene”, “Cyclohexane, 1-ethenyl-1-methyl-2-(1 methylethenyl)-4-(1-methylethylidene”, “3,7,11,15-Tetramethyl-2-hexadecen-1-ol” and “Phytol”.

These compounds are not a substrate for p-glycoprotein16 which means they do not act as an efflux pump except “3,7,11,15-Tetramethyl-2-hexadecen-1-ol” and “Phytol”.

These compounds are not inhibitors of OATP2B1, MATE1, OCT2, BSEP transporter but inhibitor to OATP1B1 and OATP1B3 transporter.

All the compounds present are not inhibitors of CYP2D6 and CYP3A4 but compounds “Benzaldehyde, 4-methyl-”, “Ethanone, 1-(2-hydroxy-5-methylphenyl)”, “Eugenol”, and “Hexadecanoic acid, methyl ester” are inhibitors of CYP1A2; compound “Benzaldehyde, 4-methyl-”, “gamma-Elemene”, “Cyclohexane, 1-ethenyl-1-methyl-2-(1 methylethenyl)-4-(1-methylethylidene)”, “1H-Cycloprop[e]azulen-7-ol, decahydro-1,1,7-trimethyl-4-methylene-, [1ar-(1a.alpha.,4a.alpha.,7.beta.,7a.beta.,7b.alpha.)]-”, and “Caryophyllene oxide” are inhibitors of CYP2C19; the compounds “gamma-Elemene”, “Cyclohexane, 1-ethenyl-1-methyl-2-(1 methylethenyl)-4-(1-methylethylidene)”, “Caryophyllene oxide”, “3,7,11,15-Tetramethyl-2-hexadecen-1-ol”, and “Phytol” are inhibitors of CYP2C9.

The druglikeliness and lead likeliness of the compounds retrieved from GC-MS analysis of an aqueous extract of A.indica is that compounds follow Lipinski’s rule17of 5; the Ghose rule is not followed for the compounds “Benzaldehyde, 4-methyl-”, “Ethanone, 1-(2-hydroxy-5-methylphenyl)”, “Phenol, 2,6-dimethoxy-”, “3,7,11,15-Tetramethyl-2-hexadecen-1-ol”, “Hexadecanoic acid, methyl ester”, and “Phytol”; Veberrule18is not followed for the compounds “3,7,11,15-Tetramethyl-2-hexadecen-1-ol”, “Hexadecanoic acid, methyl ester”, and “Phytol”; the egan rule is not followed for the compounds “3,7,11,15-Tetramethyl-2-hexadecen-1-ol”, and “Phytol”; but no compound is following the muegge rule19. The bioavailability score20 for all the compounds is 0.55 and the synthetic accessibility score is 1.00 to 4.35.

Using the free admetSAR21 programme, the GC-MS analysis of an aqueous extract of A.indica yielded information on the compounds’ toxicity profiles, the compounds “gamma-Elemene” and “Cyclohexane, 1-ethenyl-1-methyl-2-(1 methylethenyl)-4-(1-methylethylidene)” shows hERG inhibition which leads to Q-T prolongation; “Cyclohexane, 1-ethenyl-1-methyl-2-(1 methylethenyl)-4-(1-methylethylidene)” has a high risk of carcinogenicity; all the compounds except “1H-Cycloprop[e]azulen-7-ol, decahydro-1,1,7-trimethyl-4-methylene-, [1ar-(1a.alpha.,4a.alpha.,7.beta.,7a.beta.,7b.alpha.)]-” cause eye irritation; and no compound showed hepatotoxicity and AMES toxicity.

Table 3: Table showing the target proteins or macromolecules for a small compound “Benzaldehyde, 4-methyl-”

S. No. Target Uniprot ID ChEMBL ID Target Class Probability
1. D-amino-acid oxidase P14920 CHEMBL5485 Enzyme 0.044308319
2. Alcohol dehydrogenase alpha chain P07327 CHEMBL1970 Oxidoreductase 0.023832743
3. Muscarinic acetylcholine receptor M4 P08173 CHEMBL1821 Family A G protein-coupled receptor 0.023832743
4. Neuronal acetylcholine receptor; alpha4/beta2 P43681 P17787 CHEMBL1907589 Ligand-gated ion channel 0.023832743
5. Muscarinic acetylcholine receptor M5 P08912 CHEMBL2035 Family A G protein-coupled receptor 0.023832743
6. Muscarinic acetylcholine receptor M2 P08172 CHEMBL211 Family A G protein-coupled receptor 0.023832743
7. Muscarinic acetylcholine receptor M1 P11229 CHEMBL216 Family A G protein-coupled receptor 0.023832743
8. Muscarinic acetylcholine receptor M3 P20309 CHEMBL245 Family A G protein-coupled receptor 0.023832743
9. Neuronal acetylcholine receptor protein alpha-7 subunit P36544 CHEMBL2492 Ligand-gated ion channel 0.023832743
10. Alcohol dehydrogenase beta chain P00325 CHEMBL3284 Oxidoreductase 0.023832743

A swiss target prediction is a web tool, which was used to predict the protein that modulates by the compound “4-methylbenzaldehyde”. It is a small molecule that acts as a ligand shows its activity on a totally of 94 proteins/targets which are 26.7 % on oxidoreductase, 13.3 % on enzymes and 33.3 % on G-protein coupled receptor, 13.3 % on ligand-gated ion channel, 6.7 % on voltage-gated ion-channel and 6.7 % on other cytosolic proteins. Table 3 shows the first 10 proteins/receptor with high probability to target the ligand, obtained from the Uniprot database.

Table 4: Table showing the target proteins or macromolecules for a small compound “Ethanone, 1-(2-hydroxy-5-methylphenyl)”

S. No. Target Uniprot ID ChEMBL ID Target Class Probability
1. Serine/threonine-protein kinase/endoribonuclease IRE1 O75460 CHEMBL1163101 Enzyme 0.063026
2. Adenosine A1 receptor P30542 CHEMBL226 Family A G protein-coupled receptor 0.053518
3. Adenosine A2a receptor P29274 CHEMBL251 Family A G protein-coupled receptor 0.053518
4. Serum albumin P02768 CHEMBL3253 Secreted protein 0.053518
5. Carbonic anhydrase II P00918 CHEMBL205 Lyase 0.053518
6. Macrophage migration inhibitory factor P14174 CHEMBL2085 Enzyme 0.043919
7. Tyrosinase P14679 CHEMBL1973 Oxidoreductase 0.043919
8. Mannose-6-phosphate isomerase P34949 CHEMBL2758 Isomerase 0.043919
9. Estradiol 17-beta-dehydrogenase 1 P14061 CHEMBL3181 Enzyme 0.043919
10. Serotonin 2b (5-HT2b) receptor P41595 CHEMBL1833 Family A G protein-coupled receptor 0.043919

A swiss target prediction is a web tool used to predict the protein that causes to modulate, the compound “Ethanone, 1-(2-hydroxy-5-methylphenyl)” which is a small molecule that acts as a ligand and shows its activity on a totally of 100 proteins which 20 % on enzymes, 26.7 % on G-protein coupled receptor, 6.7% on secreted protein, 6.7 % on lyase, 13.3 % on oxidoreductase, 6.7% on ligand-gated ion channel, 6.7 % on isomerase, 6.7% on transferase and 6.7 % on other miscellaneous proteins. Table 4 shows the first 10 proteins with high probability to target the protein which is obtained from the Uniprot database.

Table 5: Table showing the target proteins or macromolecules for a small compound “Eugenol”

S. No. Target Uniprot ID ChEMBL ID Target Class Probability
1. Adenosine A1 receptor P30542 CHEMBL226 Family A G protein-coupled receptor 0.133391
2. Adenosine A2a receptor P29274 CHEMBL251 Family A G protein-coupled receptor 0.133391
3. Vascular endothelial growth factor A P15692 CHEMBL1783 Secreted protein 0.133391
4. Egl nine homolog 1 Q9GZT9 CHEMBL5697 Oxidoreductase 0.133391
5. Fatty acid desaturase 1 O60427 CHEMBL5840 Enzyme 0.125076
6. Histone deacetylase 6 Q9UBN7 CHEMBL1865 Eraser 0.125076
7. Carbonyl reductase [NADPH] 1 P16152 CHEMBL5586 Enzyme 0.125076
8. D-amino-acid oxidase P14920 CHEMBL5485 Enzyme 0.125076
9. Cyclooxygenase-1 P23219 CHEMBL221 Oxidoreductase 0.125076
10. Carbonic anhydrase II P00918 CHEMBL205 Lyase 0.125076

A swiss target prediction is a web tool used to predict the protein that causes to modulate, the compound “Eugenol” which is a small molecule that acts as a ligand shows its activity on total of 100 proteins which 20 % on Family A G-protein coupled receptor, 6.7 % on secreted protein, 20 % on oxidoreductase, 33.3 % on the enzyme, 6.7% on lyase, 6.7% on Family C G-protein coupled receptor and 6.7 % other miscellaneous proteins. Table 5 shows the first 10 proteins/receptors with a high probability to target the ligand obtained from the Uniprot database.

Table 6: Shows the target proteins or macromolecules for a small compound “gamma-Elemene”

S. No. Target Uniprot ID ChEMBL ID Target Class Probability
1. Peroxisome proliferator-activated receptor alpha Q07869 CHEMBL239 Nuclear receptor 0.052424
2. Cannabinoid receptor 2 P34972 CHEMBL253 Family A G protein-coupled receptor 0.052424
3. C-X-C chemokine receptor type 3 P49682 CHEMBL4441 Family A G protein-coupled receptor 0.042894
4. LXR-alpha Q13133 CHEMBL2808 Nuclear receptor 0.042894
5. Serotonin 2a (5-HT2a) receptor P28223 CHEMBL224 Family A G protein-coupled receptor 0
6. Monoamine oxidase B P27338 CHEMBL2039 Oxidoreductase 0
7. UDP-glucuronosyltransferase 2B7 P16662 CHEMBL4370 Enzyme 0
8. Monoglyceride lipase Q99685 CHEMBL4191 Enzyme 0
9. Cytochrome P450 19A1 P11511 CHEMBL1978 Cytochrome P450 0
10. Nuclear receptor subfamily 1 group I member 3 (by homology) Q14994 CHEMBL5503 Nuclear receptor 0

The swiss target prediction is a web tool used to predict the protein that causes to modulate, the compound “gamma-Elemene” which is a small molecule that acts as a ligand shows its activity on totally of 68 proteins which 33.3 % on nuclear receptor, 20 % on Family A G-protein coupled receptor, 6.7 % on oxidoreductase, 20 % on the enzyme, 13.3 % on Cytochrome P 450, and 6.7% on Voltage-gated ion channel. Table 6 shows the first 10 proteins/receptor with high probability to target the ligand which is obtained from the Uniprot database.

The last and fifth compound which shows maximum hits in GC-MS is “Cyclohexane, 1-ethenyl-1-methyl-2-(1 methylethenyl)-4-(1-methylethylidene)” which is also called “gamma-Elemene” this means that it has same properties as like “gamma-Elemene”.

Discussion

Azadirachta indica is acknowledged for a wide array of many medicinal properties for many years. The objective of this research was to detect the active bio-compounds, present in the extract which shows the pharmacological actions. In this study, we obtained 13 different compounds from the aqueous extract.

According to Saleem22et. al, A. indica contains a variety of phytochemicals for medicines, including alkaloids, steroids, flavonoids, terpenoids, fatty acids, and carbohydrates. The presence of azadirachtin and nimbin in the tree gives it fungicidal properties. In a study by Lu23 et. al, Salannin, 1-detigloyl-1-isobutylsalannin, salannol-3-acetate, salannol, spirosendan, 1-detigloyloxy-3-deacetylsalannin-1-en-3-one, nimbin, and 6-deacetylnimbin were identified from 95 percent ethanol extracts of neem (Azadirachta indica) seeds. In another study by Babatunde24et. al.,the major constituents were Eicosane (9.7662%), Diacenaphtho[1,2-j:1 _ ,2 _ -l]fluoranthene (11.301%), Phenol, 4-[[(4-methoxyphenyl)methylene]amino]- (11.84%) and (3Ar,6S,9ar)-1,2,3,4,5,6,7,9a- octahydro-8-methyl-3a,6-methano-3ah-cyclopentacycloocten-10-one (36.883%) in steam extracted oil; Eicosane (10.259%), Diacenaphtho[1,2-j:1 _ ,2 _ -l]fluoranthene (13.51%) and Butanamide, N-(2-methoxyphenyl)-3-oxo- (16.615%) in the ethanol extracted oil, and (3Ar,6S,9ar)-1,2,3,4,5,6,7,9a-octahydro-8-methyl-3a,6-methano-3ah-cyclopentacycloocten- 10-one (10.72%), n-Hexadecanoic acid (14.688%) and 9,12,15-Octadecatrienoic acid, (Z,Z,Z)- (34.719%) in the hexane extracted A. indica essential oil. Some studies done by Bolade25 et.al., disclosed many numbers of compounds that are bioactive phytoconstituents such as polyphenols and tannins by their GC-MS characterization. The study conducted by Akpuaka26, et.al., identified various phthalates like Diisobutyl phthalate, Dibutyl phthalate, Ethylhexyl phthalate, Heptyl methyl phthalate, Mono(n-octyl) phthalate, Mono(2-ethylhexyl) phthalate.In another research conducted by Shafie27et. al., revealed the presence of seven major compounds in the ethanolic leaf extract of A.excelsa which are 9, 12, 15-octadecatrienoic acid (42.34%), pentadecanoic acid, 14-methyl-, methyl ester (28.99%), phytol (10.63%), 9, 12, 15-octadecatrien-1-ol (5.37%), octadecanoic acid, methyl ester (4.36%), 9, 12-octadecadienoic acid, methyl ester (4.24%) and hexadecanoic acid, ethyl ester (4.06%).The other study done by Swapna sonale28 et. al., elicited twenty-five volatile compounds in hydro-distillate and in another extraction process called Supercritical fluid carbon dioxide (SCF) isolates forty volatile compounds with neem seed.

In another research conducted by Oshiobugie29 et. al., ten chemical constituents were identified in the leaf, six were found in the stem, and seven were identified in the root of A. indica. In a study conducted by Siddiqui11et. al., the researchers detected compounds like sixteen n-alkanes; three aromatics 2,6-bis-(1,1-dimethylethyl)-4-methyl phenol, 2-(phenylmethylene)-octanal, 1,2,4-trimethoxy-5-(1Z-propenyl)-benzene; three benzopyranoids 3,4-dihydro-4,4,5,8-tetramethylcoumarin, 3,4-dihydro-4,4,7,8-tetramethylcoumarin-6-ol, 1,3,4,6,7,8-hexahydro-4,6,6,7,8,8-hexamethyl-cyclopenta[g]-2-benzopyran; one sesquiterpene methyl-3,7,11-trimethyl-2E,6E,10-dodecatrienoate; three esters of fatty acids methyl 14-methyl-pentadecanoate, ethyl hexadecanoate, ethyl 9Z-octadecenoate and one monoterpene 3,7-dimethyl-1-octen-7-ol. According to Altayb30 et al., the GC-MS analysis of a methanolic extract of neem leaves revealed 30 peaks, which corresponded to 30 phytochemical compounds including 11 – fatty acids, 9- hydrocarbons, 2-pyridine derivatives, and 2 -aldehydes, 1- phenol group, 1-aromatic substances, 1-coumarins, and 1-monoterpenes, among these the compound 1,5-Anhydro-2-deoxy-L-arabino-hex-1-enitol was the most abundant. In another study by Hossain31 et.al.,, Hexane crude extract contains 33 different organic compounds, accounting for 7.12 % of the total extract; ethyl acetate extract contains 58 different organic compounds, accounting for 13.98 % of the total extract; chloroform extract contains 65 organic compounds, accounting for 29.12 % of the total extract; and butanol extract contains 49 different compounds, accounting for 19.56 % of the total extractbut in this study we observed 13 compounds (2 compounds are having two peaks)  such as “4-methylbenzaldehyde”, “1-(2-hydroxy-5-methylphenyl)ethan-1-one”,“2,6-dimethoxyphenol”, “2-methoxy-4-(prop-2-en-1-yl)phenol”, “(1S,2S)-1-ethenyl-1-methyl-4-propan-2-ylidene-2-prop-1-en-2-ylcyclohexane”, “4,4,7a-trimethyl-6,7-dihydro-5H-1-benzofuran-2-one”, “1-ethenyl-1-methyl-2-(prop-1-en-2-yl)-4-(propan-2-ylidene)cyclohexane”, “(7S)-1,1,7-trimethyl-4-methylidene-1a,2,3,4a,5,6,7a,7b-octahydrocyclopropa[h]azulen-7-ol”, “4,12,12-trimethyl-9-methylidene-5-oxatricyclo[8.2.0.0.4,6]dodecane”, “3,7,11,15-tetramethylhexadec-2-en-1-ol”, “methyl hexadecanoate”, and “(2E)-3,7,11,15-tetramethylhexadec-2-en-1-ol” and we retrieved the potent drug targets that modify the pharmacological actions by these major compounds obtained through GC-MS.

The research findings observed in this study have few similarities and are vastly different from those observed by other researchers, which may be due to variation in plant ethnicity or variation in the GC-MS analytical method.

Conclusion

The medicinal plant A.indica is of prime importance since ancient days as it shows helpful in the treatment of a myriad of diseases but the real active principle, which is the basis of its pharmacological actions is not yet known completely. In this attempt of the research by GC-MS analytical technique, we isolated some 13 compounds (2 compounds having two peaks) that are present in this aqueous extract. The various compounds are “4-methylbenzaldehyde”, “1-(2-hydroxy-5-methylphenyl)ethan-1-one”, “2,6-dimethoxyphenol”, “2-methoxy-4-(prop-2-en-1-yl)phenol”, “(1S,2S)-1-ethenyl-1-methyl-4-propan-2-ylidene-2-prop-1-en-2-ylcyclohexane”, “4,4,7a-trimethyl-6,7-dihydro-5H-1-benzofuran-2-one”, “1-ethenyl-1-methyl-2-(prop-1-en-2-yl)-4-(propan-2-ylidene)cyclohexane”, “(7S)-1,1,7-trimethyl-4-methylidene-1a,2,3,4a,5,6,7a,7b-octahydrocyclopropa[h]azulen-7-ol”, “4,12,12-trimethyl-9-methylidene-5-oxatricyclo[8.2.0.0.4,⁶]dodecane”, “3,7,11,15-tetramethylhexadec-2-en-1-ol”, “methyl hexadecanoate”, and “(2E)-3,7,11,15-tetramethylhexadec-2-en-1-ol” which were successfully attempted to retrieve the drug targets for these compounds that can modulate the pharmacological actions that may conducive in re-establish the diseased condition after pre-clinical and clinical trials by using these as a “Hit” molecule or “Lead” molecule.

Limitations

In this research we were able to retrieve the compounds by GC-MS and able to know the pharmacokinetic and pharmacodynamic properties, but it is required to evaluate these for pre-clinical studies and clinical trials.

Acknowledgement

We, the authors of this article are very thankful to Dr. King Shuk Lahon, Professor & Head, Department of Pharmacology, VCSGG Institute of Medical & Research, Srinagar, Uttarkhand, India for his peer review at our request. Also we are thankful to Mr. M.J.Prasad a renowned botanist for helpful in identification and authenticated the neem leaves for this study.

Conflict of Interest

There are no conflict of interest.

Funding Sources

There is no funding sources.

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