Pharmacophoric Evaluation of Compounds Isolated from GC-MS Analytical Method of Aqueous Extract of Azadirachta indica Leaves

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.

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 diseases 1 . 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 cancer 2 . As evidenced by numerous research studies, every part of the plant has been examined for its pharmacological activity 3 , and it is wellestablished that this plant is used to treat a variety of diseases in numerous countries, including the Indian subcontinent 4 . 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 limonoids 6 . 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 repellent 7 . Some of the well-established secondary metabolites, including nimbin, azadirachtin, nimbidiol, quercetin, and nimbidin 1 , are responsible for their pharmacological actions 8 , 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 extract 10 . Previous research has documented the presence of countless secondary metabolites with potent antibacterial, antifungal, insecticidal, anti-inflammatory, antiviral, antioxidant, anticancer, and antimutagenic properties 11 . 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/z 12 .

P re p a r a t i o n o f l i g a n d t o k n o w t h e 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.
Table1 depicts the availability of various compounds in the aqueous extract of A.indicawhich 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.
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 A o , which indicates that the compounds are lipid soluble.
The Log p Octanol-Water partition coefficient 14 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-2hexadecen-1-ol" and "Phytol". All the compounds show solubility in water except the last three compounds which are moderately soluble according to their hydrophilicity.
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.
A swiss target prediction is a web tool used to predict the protein that causes to modulate, the compound "Ethanone, 1-(2-hydroxy-5methylphenyl)" 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.
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.
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.

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.
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.

Conflict of Interest
There are no conflict of interest.

Funding sources
There is no funding sources.