Unfolding the Pharmacological Potentialities and Phytochemical Characterization of Pajanelia longifolia (Wild) Leaves: A Multidimensional Study via GC‐MS/MS, In Vitro, In Vivo, and In Silico Approaches

ABSTRACT

Pajanelia longifolia (Willd.) is a traditionally used medicinal plant with limited scientific evidence regarding its phytochemical composition and pharmacological properties. This study aimed to characterize the phytochemical constituents of P. longifolia leaves and to evaluate their antioxidant, hypoglycemic, antidiarrheal, and analgesic potentials using the DPPH radical‐scavenging assay, oral glucose tolerance test, castor oil‐induced diarrhea, tail immersion, and acetic acid‐induced writhing models, respectively. Methanolic leaf extract was subjected to GC–MS/MS analysis for phytochemical profiling. Molecular docking, drug‐likeness, pharmacokinetic, and toxicity analyses were performed to explore potential interactions between identified phytochemicals and target proteins. GC–MS/MS analysis identified 76 phytochemical constituents, including γ‐sitosterol, squalene, loliolide, and various fatty acid derivatives. Among the tested fractions, the chloroform fraction demonstrated the maximum hypoglycemic and antidiarrheal activities. In contrast, the n‐hexane and ethyl acetate fractions showed notable central and peripheral analgesic effects, respectively. The aqueous fraction exhibited the strongest antioxidant activity. Molecular docking revealed favorable interactions of several identified compounds, particularly γ‐sitosterol and phthalazine derivatives, with human pancreatic α‐amylase, M1 muscarinic acetylcholine receptor, μ‐opioid receptor, and cyclooxygenase‐2. Drug‐likeness, ADMET, and QSAR analyses further supported the pharmacological relevance of selected compounds. The combined findings suggest that the plant is a promising source of bioactive molecules.

This graphical abstract illustrates the integrated workflow performed for the investigations of Pajanelia longifolia (Willd.) leaves. Plant extracts obtained through extraction and fractionation were subjected to antioxidant, hypoglycemic, antidiarrheal, and analgesic activities using in vitro and in vivo approaches. Concurrently, GC‐MS based phytochemical profiling was employed to identify major constituents and screened Lipinski, ADMET, QSAR, and molecular docking, which further supported their pharmacological relevance. Overall, the combined experimental and computational findings suggest that the leaf extracts possess significant antioxidant, hypoglycemic, antidiarrheal, and analgesic potential, with a promising source of bioactive molecules.

Abbreviations

µg

micrograms

AQF

aqueous fraction

CF

chloroform fraction

DPPH

2,2′‐diphenyl‐1‐picrylhydrazyl

EAF

ethyl acetate fraction

GC–MS

gas chromatography–mass spectrometry

gm/kg

grams/kilogram

IC50

half‐maximal inhibitory concentration

mL

milliliters

MLR

multiple linear regression

NHF

n‐hexane fraction

NIST

National Institute of Standards and Technology

QSAR

quantitative structure‐activity relationship

WHO

World Health Organization

1. Introduction

Medicinal plants are vital sources of bioactive compounds and significantly contribute to both traditional healthcare and modern drug discovery [1]. Since traditional medicine is the major source of healthcare for over 80% of the world's population, medicinal plants are of great importance to the healthcare system [2]. Primary and secondary metabolites in plants, such as alkaloids, steroids, tannins, phenolic compounds, and flavonoids, influence physiological effects on the body. Medicinal plants with secondary metabolites and essential oils cure many ailments safely, cost‐effectively, and for treating various diseases [3]. Even today, treatments of various fatal and serious ailments such as cancer, diabetes, thrombosis, oxidative stress, and so forth, involve the use of compounds derived from medicinal plants due to the presence of pharmaceutical properties such as anticancer, antidiabetic, antibacterial, antifungal, and anti‐inflammatory properties [4].

Pajanelia longifolia (Wild.) K. Schuman, a member of the Bignoniaceae family, is commonly found in India's Western Ghats and Eastern Bengal areas, as well as in other tropical countries such as Bangladesh and Myanmar [5]. In Bangladesh, P. longifolia is distributed mainly in hilly regions around the coastal area. The plant is the primary source of numerous chemically active substances with significant historical usage in traditional medicine. The plant extract was traditionally used throughout the Indian subcontinent to treat jaundice, skin and nail infections, and eczema [6, 7, 8]. The plant contains compounds such as flavonoids (e.g., quercetin, kaempferol) and phenolic acids (e.g., gallic acid) that are known for their potent antioxidant properties [9]. The plant root extract showed effective bacterial and fungal properties against numerous species of bacteria and fungi, which could make it a useful herb in treating minor wounds, infections, and skin conditions [10]. It may have anti‐inflammatory properties that accelerate the healing of wounds by reducing inflammation, which is a key barrier to wound healing [11]. Some previously reported studies verified the presence of a few bioactive phytochemicals, such as 2,3,6‐trimethyloct‐6‐enal with hepatoprotective activity [12]. Furthermore, an earlier study revealed an intriguing discovery suggesting that the methanol extract of the plant could be effective in eliminating Anopheles stephensi mosquitoes, in addition to its pharmacological properties [13]. Previous reports and the phytochemical composition of P. longifolia suggest the existence of bioactive compounds potentially linked to antioxidant and anti‐inflammatory properties. Evaluation of antioxidant, analgesic, antidiarrheal, and hypoglycemic activities may offer a scientific foundation for investigating the therapeutic potential of the plant because oxidative stress and inflammatory mediators are involved in pain, diarrhea, and metabolic disorders, including diabetes mellitus [14, 15, 16]. So, P. longifolia is an intriguing candidate for further pharmacological investigation due to its ethnomedical applications.

Diabetes mellitus is a prevalent endocrine disorder marked by persistent high blood sugar levels [17]. It results from low pancreatic insulin synthesis or impaired cell insulin sensitivity [18]. It can result in severe complications that affect the heart, kidneys, eyes, and nerves if not managed appropriately [19]. The current antidiabetic medications are often costly for long‐term use and can produce side effects. This encouraged researchers to concentrate on the identification of plant‐based compounds that possess antidiabetic properties.

Oxidative stress, arising from an imbalance between the production of reactive oxygen species (ROS) and antioxidant defense mechanisms, is crucial in the onset and advancement of numerous chronic diseases, including diabetes, cardiovascular disorders, neurodegeneration, and cancer [20]. Natural antioxidants, specifically polyphenols and flavonoids derived from plants, function through various mechanisms: neutralization of free radicals, suppression of lipid peroxidation, augmentation of endogenous antioxidant enzyme activity, and modification of cellular signaling pathways [21].

Pain management is a crucial sector in which phytomedicines have shown significant potential. Central analgesia entails the manipulation of pain perception within the brain and spinal cord, generally via the activation of opioid receptors or the modification of neurotransmitter release [22]. Conversely, peripheral analgesia arises from the suppression of pain mediators at the locus of injury or inflammation, including prostaglandins, bradykinins, and cytokines [23]. Numerous plant extracts exhibit central and peripheral analgesic properties, facilitated by various mechanisms such as cyclooxygenase (COX) inhibition, nitric oxide reduction, and regulation of calcium ion channels [24, 25]. Phototherapeutic analgesics offer a viable alternative to NSAIDs and opioids, as they are associated with fewer side effects, especially concerning the safety issues related to prolonged use of traditional medications.

Diarrheal disorders continue to be a primary cause of morbidity and mortality globally, particularly among children under five years old [26]. Medicinal plants have historically been utilized to treat diarrhea owing to their antispasmodic, antibacterial, and electrolyte‐regulating properties. Specific phytochemicals, including tannins, flavonoids, alkaloids, and terpenoids, may diminish gastrointestinal motility, suppress intestinal secretion, or obstruct chloride channels, therefore normalizing stool consistency [27].

Docking analysis was performed using specific target proteins that were pertinent to the pharmacological actions under investigation in order to provide molecular support for the experimental results. Human pancreatic α‐amylase (PDB: 5E0F) was chosen as a significant target for hypoglycemic activity because inhibition of this enzyme can lower postprandial hyperglycemia and carbohydrate digestion [28]. To investigate antidiarrheal potential, the M1 muscarinic acetylcholine receptor (PDB: 5CXV), which controls intestinal motility and secretion, was selected [29]. While cyclooxygenase‐2 (COX‐2; PDB: 1CX2), a significant enzyme involved in prostaglandin synthesis and inflammatory pain, was targeted to examine peripheral analgesic mechanisms [30], the μ‐opioid receptor (PDB: 5C1M), a principal mediator of central pain modulation, was chosen to assess central analgesic activity [31].

Although previous studies have highlighted the ethnomedicinal uses and certain pharmacological effects of P. longifolia, a comprehensive link between its phytochemical composition and pharmacological assessment remains unestablished. This research is the first effort to combine GC‐MS/MS‐based phytochemical characterization with multiple evaluations, encompassing in vivo hypoglycemic, antidiarrheal, and analgesic effects, in vitro antioxidant assessment, and in silico analyses including molecular docking and ADMET studies of the methanolic leaf extract of P. longifolia. Thus, the main aim of this study is to characterize the phytochemical components of the methanolic leaf extract of P. longifolia and assess its hypoglycemic, antidiarrheal, analgesic, and antioxidant properties using experimental and computational techniques.

2. Materials and Methods

2.1. Preparation of Plant Material

The leaves of P. longifolia were collected from Chattogram district, Bangladesh, in March 2024. A taxonomist, Mohammad Abdhur Rahim, determined the authenticity of the plant sample with the accession number JUH‐10258. The collected leaves were carefully washed with purified water and shade‐dried in a well‐ventilated laboratory environment at ambient temperature (about 25°C–30°C) for approximately 7 days, avoiding direct sunlight to reduce the degradation of thermolabile phytoconstituents. The relative humidity during the drying process was around 40% to 60%. Upon complete drying, the leaves were crushed into coarse powder via a mechanical grinder. The powdered substance was preserved in an airtight amber container at ambient temperature in a dry, dark setting until further extraction and analysis.

2.2. Extraction and Fractionation

The dried fragments of the leaves of P. longifolia were crushed into coarse powder, and 500 g of the powder was placed in a clean, round‐bottom flask and immersed in about 3 L of methanol for 15 days, with intermittent agitation and mixing. The filtrate was obtained upon filtering and then concentrated into a dry crude extract by completely evaporating the solvent using a rotary evaporator at low temperature (50°C) and pressure. The percentage yield of the crude methanolic extract was calculated based on the initial dried plant powder weighing 500 g. The yields of different solvent fractions were evaluated in comparison to the crude extract. Five grams of the crude extract were progressively partitioned with n‐hexane, chloroform, ethyl acetate, and water to fractionate the extract based on polarity. The modified Kupchan partitioning method is employed in this fractionation technique. Each fraction was individually concentrated under reduced pressure utilizing a rotary evaporator and subsequently stored at 4°C for additional pharmacological and phytochemical analysis [32].

2.3. Drugs and Chemicals

All solvents and reagents used in this study were of analytical reagent (AR) grade. The reference drugs used for pharmacological evaluations were commercially available pharmaceutical products procured from the local market and utilized according to the manufacturers' recommended specifications. The chemicals have been used without additional purification.

2.4. Experimental Animals

Swiss albino mice aged 4 to 5 weeks and Wistar rats aged 8 to 10 weeks were kept in regulated laboratory conditions (25 ± 2°C, 50%–60% humidity, 12‐h light/dark cycle) with access to water and a normal diet. In order to reduce bias, the study's objective was to evaluate the hypoglycemic activity in rats and the analgesic and antidiarrheal activity in mice, with equal sex distribution among groups. Animals were kept in controlled environments and acclimated for 7 days before the experiment. The Institutional Animal Ethics Committee granted ethical permission for a systematic review of protocols (Ref. No. 270/Biol. Sci.) (File S1). To reduce selection bias, studies followed ARRIVE guideline 2.0 and randomly assigned participants to experimental groups (n = 6 per group). Efforts were made to minimize observational bias during data collection and processing, and the sample size reflected conventional procedures in initial pharmacological screens utilizing extracts from medicinal plants. The experimental mice were administered an intraperitoneal dosage of ketamine hydrochloride (100 mg/kg) and xylazine (7.5 mg/kg) for euthanasia once the tests were completed, thereby reducing the stress [33].

2.5. Acute Toxicity Test

The acute toxicity assessment of P. longifolia was conducted in accordance with OECD Test No. 423: Acute Oral Toxicity Acute Toxic Class Method (2002), with few modifications [34]. The extract was administered orally at doses of 200, 400, 800, 1600, and 3200 mg/kg [35]. Before the administration of the extract, all mice had a 16‐h fasting period. Following treatment, the mice were continuously observed for 1 h, followed by intermittent evaluations over the next 4 h, and were subsequently monitored for 24 h to identify any behavioral changes, signs of toxicity, or mortality. The mice were monitored until death for 14 days. The LD50 values for the fractions were ascertained.

2.6. Dose Preparation and Administration

For the in vivo studies, all experimental fractions and standard drugs (miglitol, loperamide, morphine, and diclofenac sodium) doses were prepared as suspensions by incorporating suspending agents and normal saline (0.9% NaCl). Based on previous studies of medicinal plant extracts, doses of 200 and 400 mg/kg body weight were selected due to tolerability observations. After administering these doses, no mortality or significant acute toxicity symptoms were observed in the animals. These dosages were designated as moderate and high for pharmacological assessments, where both dosages were used to evaluate specific pharmacological effects [36]. The standard drug Miglitol (10 mg/kg) and diclofenac sodium (5 mg/kg) served as positive controls [37].

2.7. Phytochemical Investigation Using GC–MS/MS and Identification of Phytochemicals

GC‐MS/MS analysis was carried out using the liquid extract injection method. P. longifolia leaf extract was dissolved in methanol, filtered using a 0.22 µm syringe filter, and injected into the GC‐MS/MS apparatus. This analysis employed no headspace or solid‐phase microextraction/SPME procedures. Phytochemicals from the leaves of P. longifolia were investigated with the help of an ionization detector using GC–MS/MS (Shimadzu, Japan; Model GC–MS TQ 8040) analysis, where a silica capillary column (Rxi5Sil MS, 30 m, 0.25 mm ID, and 0.25 µm) at 50°C was used. Helium was used as the carrier gas at a constant flow rate (1 mL/min), with the sample injected in split mode (10:1 ratio) at 250°C. Electron ionization occurred at 70 eV, with the ion source and interface temperatures set to 200°C and 250°C, respectively. Mass spectra were obtained between 40 and 600 m/z. The oven temperature program included an initial hold at 50°C for 2 min before increasing to a final temperature of 300°C for 7 min, for a total run time of 40 min and a solvent delay of 3.5 min. Compounds were identified by comparing mass spectra to NIST and Wiley libraries, with samples collected at 250°C. The electron multiplier was set to 900 V. Identification involved comparing spectra with approximately 62 000 patterns in the NIST database to ascertain compound names, molecular weights (MWs), and formulas [38, 39].

2.8. In Vivo Study Design

In the pharmacological investigations, animals were divided into three groups: control, standard, and treatment, each with six animals, ensuring a balanced distribution of body weight and genders. Whenever possible, each group had three male and three female animals. The sample size of six (n = 6) was determined based on previous pharmacological studies and preliminary screening methods.

2.8.1. Hypoglycemic Activity Test

The impact of the test sample on reducing the blood glucose level in diabetic mice was assessed using a modified version of the oral glucose tolerance test in mice [40]. During the experiment, the blood glucose levels of six rats in each group (negative control, positive control, and test groups) were initially measured using a glucometer by taking blood from the tail vein. Subsequently, all groups of animals were orally administered a 10% glucose solution at a 2 g/kg dose to increase their blood glucose levels. The blood glucose level of each rat was measured after a duration of 30 min. The negative control group received an oral dose of 0.1 mL/10 g of body weight of a 1% Tween 80 solution mixed with normal saline. The positive control group received an oral dose of miglitol at 10 mg/kg of body weight. The test group mice were orally treated with test fractions at doses of 200 and 400 mg/kg of body weight. Afterward, the blood glucose level of every rat in each group was monitored comparably at 60, 120, and 180 min. The percentage decrease in blood glucose level of the test sample was calculated to evaluate the hypoglycemic activity.

2.8.2. Antidiarrheal Activity Test

The current research aimed to examine the antidiarrheal properties of the methanolic extract of P. longifolia using the castor oil‐induced diarrheal method [41]. All mice were orally administered 1 mL of castor oil following a 30‐min waiting period to induce diarrhea. A negative control group was administered a 10 mL/kg of body weight oral solution of Tween 80, while a positive control group of mice was administered a 50 mg/kg of body weight oral solution of Loperamide. The experimental groups were treated with two distinct dosages (200 and 400 mg/kg of body weight) of test fractions. The total number of fecal movements produced by each animal was recorded for 4 h. The following formula was employed to determine the percentage of defecation inhibition:

$$\begin{array}{ccc}& & \%\mathrm{Inhibition}\hfill \\ & & =\frac{\begin{array}{c}(\mathrm{Average}\mathrm{number}\mathrm{of}\mathrm{diarrheal}\mathrm{stools}\mathrm{in}\mathrm{the}\mathrm{control}\mathrm{group}\hfill \\ -\mathrm{Average}\mathrm{number}\mathrm{of}\mathrm{diarrheal}\mathrm{stools}\mathrm{in}\mathrm{the}\mathrm{test}\mathrm{group})\hfill \end{array}}{\left(\mathrm{Average}\mathrm{number}\mathrm{of}\mathrm{diarrheal}\mathrm{stools}\mathrm{in}\mathrm{the}\mathrm{control}\mathrm{group}\right)}\hfill \\ & & \times 100\hfill \end{array}$$

2.8.3. Central Analgesic Activity Test

The tail‐flicking technique was used to assess the central analgesic activity of the different fractions of methanolic extracts of P. longifolia [42]. The mice were given two dosages (200 and 400 mg/kg of body weight) of the investigated samples. To elicit the experience of pain, the tail end (about 5 cm) was immersed in hot water. The duration of tail withdrawal from the water was recorded at 0, 30, 60, and 90 min. The negative control was an oral saline mixture of 1% Tween 80 (administered at a rate of 0.1 mL per 10 mg), while the positive control was a subcutaneous morphine injection at a dosage of 2 mg/kg of body weight.

2.8.4. Peripheral Analgesic Activity Test

The acetic acid‐induced pain sensitivity method was used to assess the peripheral analgesic efficacy of P. longifolia leaves [43]. The term “writhing” was used to describe the body's contractions resulting from pain caused by intraperitoneal administration of acetic acid (0.1 mL). The positive control group's mice were orally administered 5 mg/kg of diclofenac sodium, while the experimental groups were orally administered 200 and 400 mg/kg of the test fractions. The number of body movements that involved twisting was monitored for 5 min following the administration of the sample. Subsequently, the following formula was employed to determine the percentage of twisting inhibition:

$$\begin{array}{ccc}& & \mathrm{Percentage}\mathrm{of}\mathrm{inhibition}\hfill \\ & & =\frac{\begin{array}{c}(\mathrm{Writhing}\mathrm{response}\mathrm{of}\mathrm{control}\mathrm{group}\hfill \\ -\mathrm{Writhing}\mathrm{response}\mathrm{of}\mathrm{test}\mathrm{group})\hfill \end{array}}{\left(\mathrm{Writhing}\mathrm{response}\mathrm{of}\mathrm{control}\mathrm{group}\right)}\times 100\%\hfill \end{array}$$

2.9. In Vitro Antioxidant Activity Test

The antioxidant activity of the test samples was evaluated using the stable free radical, 2,2′‐diphenyl‐1‐picrylhydrazyl (DPPH). This test measures the ability of the samples to neutralize DPPH and compares their effectiveness to that of the natural antioxidant ascorbic acid (AA) [44]. The samples, including both extractives and controls, were prepared at concentrations between 500 and 1 µg/mL. Two milliliters of these solutions were mixed with 3.0 mL of a methanol solution containing DPPH at a concentration of 20 µg/mL. After thorough mixing, the solutions were left at room temperature for 30 min in the dark. The absorbance values of the resulting mixtures were then measured at 517 nm using a UV spectrophotometer. The percentage inhibition (I%) of DPPH free radicals was calculated using the following formula:

$$\mathrm{I}\%=\left(1-A_{\mathrm{sample}}/A_{\mathrm{blank}}\right)\times 100$$

where A _blank = absorbance of the control solution, A _sample absorbance of the samples.

2.10. Statistical Analysis

To accurately represent the results of the in vivo evaluations, the mean ± SEM was used to convey the average values and their corresponding standard errors of the mean. The p values of the assays were determined by an unpaired t‐test employing the Student t‐test calculator. Statistical significance was determined for any p values that were less than 0.05.

2.11. In Silico Study Design

2.11.1. Preparation of Ligand

The structures of 76 isolated compounds derived from the P. longifolia extract, along with miglitol (PubChem CID: 441314), loperamide (PubChem CID: 3955), diclofenac sodium (PubChem CID: 3033), and morphine (PubChem CID: 5288826), were retrieved from the PubChem database (https://pubchem.ncbi.nlm.nih.gov/) and are detailed in Table 1. To increase the hit rate against the indicated targets, the ligands were downloaded in 3D SDF format. The compounds were synthesized as ligands and minimized with the PyRx program for screening. The virtual screening method used PyRx with its default settings, as given by MGL Tools (https://ccsb.scripps.edu/mgltools/), to guarantee that the results were consistent and reliable [45].

TABLE 1.

Phytochemicals identified from GC‐MS/MS analysis of the methanolic leaves extract of P. longifolia.

S No.	CID	Compound name	m/z	MW (g/mol)	R. Time	Area %
1	33510	1,2,3‐Propanetriol, 1‐acetate	43	134.13	3.543	2.83
2	66774	Acetic acid, hydroxy‐, methyl ester	31	90.08	3.78	0.46
3	753	Glycerin	61	92.09	3.989	6.02
4	11040	Propanoic acid, 2‐hydroxy‐, methyl ester	45	104.10	4.063	0.37
5	6584	Acetic acid, methyl ester	43	74.08	4.364	0.16
6	8868	Ethyl acetoacetate	43	130.14	4.39	0.22
7	11748	Propanoic acid, 2‐oxo‐, methyl ester	43	102.09	4.527	2.85
8	25793	1‐Hexanol, 3‐methyl‐	43	116.20	4.955	0.13
9	18318716	Butyl 2‐(2‐methoxyethoxy) acetate	89	190.24	5.005	0.45
10	293276	2,2‐Dimethoxypropionamide	89	133.15	5.11	1.97
11	23294	Di‐sec‐Butyl ether	103	130.23	5.193	0.98
12	670	Dihydroxyacetone	31	90.08	5.865	0.87
13	7302	Butyrolactone	42	86.09	5.963	0.85
14	566657	1,2‐Cyclopentanedione	98	98.10	6.107	1.43
15	538757	2,4‐Dihydroxy‐2,5‐dimethyl‐3(2H)‐furan‐3‐one	101	144.12	6.814	0.13
16	139989	Octane, 3,5‐dimethyl‐	57	142.28	6.996	1.19
17	537332	Octane, 5‐ethyl‐2‐methyl‐	43	156.31	8.215	2.07
18	11006	Hexadecane	57	226.44	8.264	3.07
19	95652	2(3H)‐Furanone, dihydro‐4‐hydroxy‐	44	102.09	8.417	0.89
20	931	Naphthalene	128	128.17	9.368	1.81
21	9231	Azulene	128	128.17	9.452	2.34
22	10329	Benzofuran, 2,3‐dihydro‐	120	120.15	9.687	0.46
23	607204	Bicyclo[3.3.1]non‐2‐en‐9‐ol, syn‐	91	214.30	9.725	0.20
24	62453	4‐Vinylphenol	120	120.15	9.795	5.71
25	614380	Phosphorous acid, methyl bis(trimethylsilyl) ester	225	240.38	10.04	0.21
26	97391	1,4‐Methanonaphthalene, 1,4‐dihydro‐	141	142.20	10.667	0.37
27	332	2‐Methoxy‐4‐vinyl phenol	135	150.17	10.746	0.67
28	7002	Naphthalene, 1‐methyl‐	142	142.20	10.82	0.14
29	78182	4‐Cyclohexyl‐1‐butanol	73	156.26	11.057	0.13
30	5368925	Propanoic acid, 3‐(2‐hydroxycyclobutylidene)‐2‐methyl‐, [R*,R*‐(E)]‐	84	156.18	11.623	0.66
31	557446	1'‐Hydroxy‐4,3'‐dimethyl‐bicyclohexyl‐3,3'‐dien‐2‐one	82	220.31	11.775	0.35
32	98155	2‐(Isobutoxymethyl)‐oxirane	57	130.18	11.952	2.94
33	151398	4‐Vinylbenzene‐1,2‐diol	136	136.15	12.058	3.31
34	619737	2‐(4‐Ethyl‐phenyl)‐2,3‐dihydro‐phthalazine‐1,4‐dione	251	266.29	12.105	3.11
35	10012038	1H‐1,3‐Benzodiazole‐5‐carbaldehyde	145	146.15	12.194	5.99
36	91691498	Carbonic acid, decyl vinyl ester	57	228.33	12.395	0.99
37	2724705	beta‐D‐Glucopyranose, 1,6‐anhydro‐	60	162.14	12.48	2.44
38	87650	1‐Heptanol, 2,4‐dimethyl‐, (R,R)‐(+)‐	97	144.25	12.665	0.96
39	—	2(4H)‐Benzofuranone, 5,6,7,7a‐tetrahydro‐4,4,7a‐trimethyl‐	111	180.243	12.925	0.22
40	12401	Nonadecane	57	268.5	13.327	0.20
41	74956	Tetrahydro‐4H‐pyran‐4‐ol	44	102.13	13.535	0.68
42	5366075	3‐Hydroxy‐beta‐damascone	69	208.30	13.585	0.51
43	656894	Isopropyl‐beta‐D‐thiogalactopyranoside	91	238.30	13.664	1.02
44	600264	syn‐Tricyclo[5.1.0.0(2,4)]oct‐5‐ene, 3,3,5,6,8,8‐hexamethyl‐	57	190.32	13.776	0.62
45	—	(7‐Oxabicyclo[4.1.0]heptan‐3‐yl)methyl 7‐oxabicyclo[4.1.0]heptane‐3‐carboxylate (isomer 2)	95	—	13.892	2.82
46	66281	1‐Octadecanesulphonyl chloride	57	353.0	14.073	1.31
47	544115	2H‐Pyran, 2‐(2‐heptadecynyloxy)tetrahydro‐	55	336.6	14.231	2.48
48	8222	Eicosane	57	282.5	14.395	0.34
49	13860	Cyclohexanemethanol, 4‐methylene‐	55	126.20	15.328	0.16
50	100332	Loliolide	43	196.24	15.605	0.51
51	10446	Neophytadiene	68	278.5	16.181	0.39
52	23872	Oxirane, hexadecyl‐	57	268.5	16.266	0.38
53	3676	Lidocaine	86	234.34	17.16	0.12
54	23518	Pentadecanoic acid, methyl ester	74	256.42	17.478	2.41
55	985	n‐Hexadecanoic acid	73	256.42	18.014	3.15
56	43943	Nonane, 5‐(1‐methylpropyl)‐	57	184.36	18.19	0.26
57	5284421	9,12‐Octadecadienoic acid (Z, Z)‐, methyl ester	67	294.5	20.177	0.94
58	5319706	9,12,15‐Octadecatrienoic acid, methyl ester, (Z, Z, Z)‐	79	292.5	20.28	3.53
59	5280435	Phytol	71	296.5	20.432	1.10
60	15610	Nonadecanoic acid, methyl ester	74	312.5	20.704	0.49
61	5280450	9,12‐Octadecadienoic acid (Z,Z)‐	67	280.4	20.84	0.62
62	5364468	7‐Tetradecenal, (Z)‐	79	210.36	20.904	4.04
63	547888	Pentadecanamide, 15‐bromo‐	59	320.31	21.664	0.56
64	95337	1‐Decanol, 2‐hexyl‐	111	242.44	24.163	0.17
65	136909	Cyclododecyne	67	164.29	24.555	0.22
66	56936054	Palmitoleamide	59	253.42	24.64	4.25
67	69492	Tetradecanamide	59	227.39	25.08	0.39
68	23494	Tetratetracontane	57	619.2	25.332	0.10
69	12696145	Triacontane, 1‐iodo‐	57	548.7	26.926	0.13
70	123409	Hexadecanoic acid, 2‐hydroxy‐1‐(hydroxymethyl)ethyl ester	176	330.5	27.097	0.24
71	3681	Batilol	57	344.6	28.891	0.16
72	560155	Tridecanoic acid, 4,8,12‐trimethyl‐, methyl ester	57	270.5	30.404	0.20
73	5365374	cis‐11‐Eicosenamide	59	309.5	31.199	0.13
74	638072	Squalene	69	410.7	31.618	1.32
75	54670067	Vitamin E	165	176.12	36.121	1.53
76	457801	Gamma‐Sitosterol	43	414.7	39.473	2.52

2.11.2. Protein Preparation

To investigate their biological functions, three‐dimensional crystal structures were downloaded in PDB format from the RCBS Protein Data Bank (https://www.rcsb.org/structure). The proteins were selected based on their biological significance to the pharmacological actions assessed in this investigation. These structures included human pancreatic alpha‐amylase (PDB ID: 5E0F), given that α‐amylase inhibition correlates with delayed carbohydrate digestion and reduced postprandial glucose absorption; M1 muscarinic acetylcholine receptor (PDB ID: 5CXV) was chosen for its potential antidiarrheal effects, as cholinergic signaling via muscarinic receptors plays a role in intestinal motility and secretion; the mu‐opioid receptor (PDB ID: 5C1M), which plays a key role in central analgesic effects owing to its recognized function in central pain modulation; and cyclooxygenase‐2 (COX‐2; PDB ID: 1CX2) was chosen for its peripheral analgesic properties due to its role in prostaglandin synthesis, inflammation, and pain signaling [46, 47, 48, 49]. Water molecules and heteroatoms were removed from proteins using Discovery Studio 2020. Energy minimization was subsequently conducted using Swiss‐PdbViewer, which included nonpolar hydrogen atoms and optimized all biomolecules to produce the lowest energy configurations for later analysis.

2.11.3. Molecular Docking Analysis

A blind docking technique was used to make docking for the selected protein‐ligand complexes easier. PyRx Auto Dock Vina was used to optimize and minimize the size of the proteins and ligands (compounds), before converting them to PDBQT format [50]. In this study, both the stiffness of the protein and the flexibility of the ligand were maintained. The ligand molecule was given 10 degrees of freedom. AutoDock offered a complete methodology for converting molecules to PDBQT format, including specifications such as molecule type, box type, grid box construction, and so on. The values at axis X = − 8.4005, Y = 21.625, and Z = −18.966, and the dimensions were X = 56.7115, Y = 73.26, and Z = 54.874 for PDB‐ID: 5E0F with C34 ligand to do the docking experiment. The grid box was created around the whole protein of interest. The dock file was uploaded to BIOVIA Discovery Studio Visualizer to exhibit protein‐ligand pocket diagrams and the locations of active amino acids, subsequent to a PyMOL analysis that generated a complex structure. To validate the docking methodology, the co‐crystallized ligands were re‐docked into the active sites of their corresponding target proteins utilizing identical docking settings [51]. Furthermore, BIOVIA Discovery Studio Visualizer 2020 was used to quickly identify suitable docking spots [52].

2.11.4. Lipinski's Criteria and Drug Pharmacokinetics

The Swiss ADME online database (http://www.swissadme.ch) was utilized to assess the Lipinski Rule and pharmacokinetic properties of the specified compounds prior to conducting the molecular docking experiment [53]. The Lipinski rule and pharmacokinetics describe an intricate combination of chemical and structural factors that determine whether a novel substance behaves similarly to an established medicine. Hydrophobicity, drug‐like properties, hydrogen bonding capacity, molecular size and weight, bioavailability, and a variety of other characteristics are among them.

2.11.5. ADMET Profile Prediction

ADMET represents absorption, distribution, metabolism, excretion, and toxicity. The pkCSM online tool (https://biosig.lab.uq.edu.au/pkcsm/) can be utilized for related analyses [54], and http://lmmd.ecust.edu.cn/admetsar2/result/?tid = 742441 were utilized to assess and analyze the ADMET feature [ 55 ].

2.11.6. Quantitative Structure‐Activity Relationship (QSAR) and pIC₅₀ Determination

The pIC₅₀ and QSAR values were computed utilizing the Chemdes website and the multiple linear regression (MLR) standard equation. The necessary data (including Chiv5, MRVSA9, and PEOEVSA5) were obtained from the free database of Chemdes. Subsequently, an Excel spreadsheet was constructed utilizing MLR, and the QSAR and pIC₅₀ calculations for the reported ligand were finalized [56]. The dataset includes several descriptors: “bcutm1” signifies burden descriptors, while “MRVSA9,” “MRVSA6,” and “PEOEVSA5” are categorized as MOE‐type descriptors. “GATSv4” represents an autocorrelation descriptor. Additionally, the last two variables, “J” and “diameter,” are proposed as topological descriptors relevant to biological substances or drug molecules [57].

3. Results

3.1. Phytochemicals Identified From GC‐MS/MS Analysis

The extract generates 76 peaks on the GC‐MS/MS chromatogram that indicate 76 different phytochemicals, as shown in Figure S1 (File S2). After comparing the sample's mass spectra with the available database (NIST or Wiley Library), 76 compounds were identified and confirmed. These phytochemicals were listed along with their retention time (R. time), MW, PubChem ID, and percent concentration (% area) in Table 1. The highest peak area was observed for glycerin (6.02%); 1H‐1,3‐benzodiazole‐5‐carbaldehyde (5.99%); 4‐vinylphenol (5.71), palmitoleamide (4.25%); 7‐tetradecenal, (Z)‐ (4.04%); 9,12,15‐octadecatrienoic acid, methyl ester, (Z, Z, Z)‐(3.53%); 4‐vinylbenzene‐1,2‐diol (3.31%); n‐hexadecanoic acid (3.15%); 2‐(4‐ethyl‐phenyl)‐2,3‐dihydro‐phthalazine‐1,4‐dione (3.11%); hexadecane (3.07%); 2‐(isobutoxy methyl)‐oxirane (2.94%); propanoic acid, 2‐oxo‐, methyl ester (2.85%); 1,2,3‐propanetriol, 1‐acetate (2.83%); (7‐oxabicyclo[4.1.0]heptan‐3‐yl)methyl 7‐oxabicyclo[4.1.0]heptane‐3‐carboxylate (isomer 2) (2.82%); gamma‐Sitosterol (2.52%) and 2H‐pyran, 2‐(2‐heptadecynyloxy)‐tetrahydro‐ (2.48%).

3.2. The Amount of Extract Yield and Fraction Yield

The crude methanolic extract yielded 5.0% (w/w) of dried plant material. The aqueous fraction had the highest yield among the fractions, followed by the n‐hexane, chloroform, and ethyl acetate fractions (Table 2).

TABLE 2.

Yield of crude methanolic extract and fraction.

Sample	Weight (g)	Yield (%)
Crude extract	25	5.0
NHF	1.3	26
CF	1.2	24
EAF	0.9	18
AQF	1.6	32

3.3. Acute Toxicity Assessment

Crude methanolic extract administered orally at concentrations of 200, 400, 800, 1600, and 3200 mg/kg did not cause any noticeable poisoning symptoms or deaths within the first 48 h, indicating that the oral LD50 is higher than these dosages. The experimental mice showed no signs of acute poisoning, including vomiting, diarrhea, ataxia, piloerection, and unconsciousness, according to physical and behavioral evaluations.

3.4. Hypoglycemic Activity

The glucose tolerance test was performed to evaluate the ability of the plant extract to decrease blood glucose at various dosages, using miglitol as the standard, and plasma glucose levels were measured after 60, 120, and 180 min. The study found that both 200 and 400 mg/kg dosages of NHF, CF, and AQF exhibited significant (p < 0.05) outcomes (Table 3). After 180 min, blood glucose levels were reduced by 33.71%, 38.9%, and 39.32% for the 200 mg/kg body weight dosages of NHF, CF, and AQF, and 35.78%, 53.01%, and 32.16% for the 400 mg/kg doses, which were comparable to the 53.92% decrease seen with the positive control medication miglitol (Figure 1). Among the tested fractions, CF‐400 exhibited the most significant glucose‐lowering impact, which was equivalent to, yet slightly less effective than, the standard medication, suggesting a moderate hypoglycemic potential of the fraction.

TABLE 3.

Average glucose level (mmol/L) after loading the glucose sample.

Group	Average glucose level (mmol/L) after loading the glucose sample
	0 min	30 min	60 min	120 min	180 min
CTL	5.68 ± 0.08	10.63 ± 0.28	10.02 ± 0.23	9.58 ± 0.11	8.83 ± 0.15
STD	5.45 ± 0.11	10.98 ± 0.24	7.82 ± 0.13 ***	6.20 ± 0.16 ***	3.95 ± 0.06 ***
NHF‐200	5.18 ± 0.11	10.68 ± 0.08	9.38 ± 0.09 *	8.62 ± 0.09 ***	7.08 ± 0.15 ***
NHF‐400	5.33 ± 0.13	10.90 ± 0.12	8.82 ± 0.13 ***	8.38 ± 0.04 ***	7 ± 0.07 ***
CF‐200	5.63 ± 0.09	10.77 ± 0.09	10.28 ± 0.117	8.93 ± 0.08 ***	6.58 ± 0.14 ***
CF‐400	5.57 ± 0.13	10.83 ± 0.15	8.38 ± 0.08 ***	7.75 ± 0.096 ***	5.08 ± 0.08 ***
EAF‐200	5.88 ± 0.11	10.60 ± 0.14	9.93 ± 0.08	9.58 ± 0.12	8.97 ± 0.15
EAF‐400	5.57 ± 0.15	10.60 ± 0.11	9.98 ± 0.10	9.53 ± 0.11	8.82 ± 0.13
AQF‐200	5.68 ± 0.07	10.63 ± 0.17	9.37 ± 0.09 *	8.97 ± 0.21 *	6.45 ± 0.12 ***
AQF‐400	5.63 ± 0.07	10.51 ± 0.06	9.08 ± 0.11 **	8.95 ± 0.13 **	7.13 ± 0.15 ***

Note: Data are mentioned as mean ± SEM, n = 6. ^* p < 0.05; ^** p < 0.01; ^*** p < 0.001 versus negative control.

FIGURE 1.

Percent glucose level reduction for different fractions of P. longifolia leaves with time.

3.5. Antidiarrheal Activity

The results indicated that different doses of leaf extract concentrations had statistically significant antidiarrheal properties (p < 0.05). Among all groups, CF‐400 is the most effective extract, reducing fecal output by 54.79%, closely approaching the standard drug's efficacy mentioned in Table 4, while AQF‐400 and NHF‐400 show moderate reductions (40.27% and 30.59%, respectively). Both doses of EAF (200 and 400 mg) demonstrate weak antidiarrheal activity, with reductions of 9.68% and 14.52%, respectively. Despite CF‐400 exhibiting the greatest activity among the evaluated fractions, its efficacy was less effective than that of loperamide, a standard antidiarrheal medication.

TABLE 4.

The effect of the extract on stool count in castor oil‐induced diarrheal episode in mice.

Test group	Total no. of diarrheal feces after 4h	%Reduction of diarrhea
Control	10.33 ± 0.67	—
Loperamide	3.17 ± 0.31 ***	69.31
NHF‐200	8.50 ± 0.43 *	17.71
NHF‐400	7.17 ± 0.60 **	30.59
CF‐200	6.33 ± 0.49 ***	38.72
CF‐400	4.67 ± 0.56 ***	54.79
EAF‐200	9.33 ± 0.49	9.68
EAF‐400	8.83 ± 0.60	14.52
AQF‐200	6.67 ± 0.56 **	35.43
AQF‐400	6.17 ± 0.48 ***	40.27

Note: Data are represented as mean ± SEM for n = 6. ^* p < 0.05; ^** p < 0.01; ^*** p < 0.001.

3.6. Central Analgesic Activity

Statistically significant percentage (%) elongation times (p < 0.001) were observed at 30, 60, and 90 min after administration of medication samples in the albino mice. The study found that the n‐hexane and aqueous fraction of P. longifolia leaf extract showed moderate central analgesic activity at doses of 200 and 400 mg/kg body weight after 90 min, with the highest activity at 400 mg/kg of n‐hexane fraction, resulting in a 129.72 ± 4.25% tail immersion time (Table 5). On the contrary, the chloroform and ethyl acetate fractions do not show any central analgesic activity.

TABLE 5.

Central analgesic activities in mice by the tail immersion method.

Treatment	% Time elongation (Mean ± SEM)
	After 30 min	After 60 min	After 90 min
Standard	480.74 ± 9.3 ***	550 ± 11.70 ***	560 ± 12.21 ***
NHF‐200	47.82 ± 2.38 **	56.66 ± 2.82 *	50.81 ± 2.79 **
NHF‐400	152.7 ± 4.0 ***	139.44 ± 4.31 ***	129.72 ± 4.25 ***
CF‐200	8.07 ± 1.74	8.33 ± 1.95	11.35 ± 2.06
CF‐400	17.39 ± 1.89	22.77 ± 2.21	14.37 ± 2.16
EAF‐200	18.63 ± 1.93	19.44 ± 2.15	9.18 ± 2.02
EAF‐400	18.01 ± 1.90	27.22 ± 2.29	13.51 ± 2.10
AQF‐200	34.16 ± 2.16 *	53.88 ± 2.77 **	62.16 ± 3.00 ***
AQF‐400	70.80 ± 2.75 ***	70.55 ± 3.07 ***	73.71 ± 3.21 ***

Note: Data are mentioned as mean ± SEM, n = 6. ^* p < 0.05; ^** p < 0.01; ^*** p < 0.001 versus negative control.

3.7. Peripheral Analgesic Activity

In this recent analysis, statistical evaluation of the data confirmed that the extracts exhibited significant peripheral analgesic activity with percent inhibition of 24.80% and 19.39% at a dose of 400 mg/kg for EAF and AQF, respectively, and also significant peripheral analgesic activity with a percent inhibition of 17.07% and 15.49% at a dose of 200 mg/kg for EAF and AQF, respectively (Table 6). The EAF at a 400 mg/kg dose gave extremely statistically significant activity compared to others. On the contrary, 73.30% inhibition was shown with the standard drug (diclofenac sodium).

TABLE 6.

Peripheral analgesic activities in mice by acetic acid‐induced writhing method.

Groups	Mean writhing (Mean ± SEM)	%Inhibition of writhing
Control	21.5 ± 0.99	—
Standard	6.17 ± 0.48	71.30 ***
NHF‐200	20.50 ± 0.67	4.65
NHF‐400	20.67 ± 0.49	3.86
CF‐200	20.83 ± 0.60	3.12
CF‐400	20.50 ± 0.43	4.65
EAF‐200	17.83 ± 0.60	17.07 *
EAF‐400	16.17 ± 0.48	24.80 ***
AQF‐200	18.17 ± 0.49	15.49*
AQF‐400	17.33 ± 0.60	19.39 **

Note: Data are mentioned as mean ± SEM, n = 6. ^* p < 0.05; ^** p < 0.01; ^*** p < 0.001 versus negative control.

3.8. Antioxidant Activity

The investigation revealed that the methanolic leaf extract of P. longifolia may scavenge hydroxyl radicals, with an IC₅₀ value of 2.69 µg/mL for standard ascorbic acid and the different fractions scavenged DPPH radicals in the order: AQF (IC₅₀ = 31.81 µg/mL) > CF (IC₅₀ = 34.93 µg/mL) > EAF (IC₅₀ = 59.96 µg/mL) > NHF (IC₅₀ = 113.8 µg/mL). Figure 2 exhibits that AQF had the greatest free radical scavenging activity (IC₅₀ = 31.81 µg/mL), whereas NHF had the lowest (IC₅₀ = 113.8 µg/mL).

FIGURE 2.

IC50 values of DPPH radical scavenging activity of ascorbic acid and different fractions of methanolic leaf extract of P. longifolia.

3.9. In Silico Study

3.9.1. Binding Affinities of Identified Compounds

Molecular docking analysis determined the binding affinities of the 76 compounds and standards to four receptors involved in the hypoglycemic, antidiarrheal, central analgesic, and peripheral analgesic activity (File S2: Table S1). Table 7 shows the binding affinities of some selected compounds and standard drugs to these receptors. C34 (CID: 619737) had the highest binding affinity to all targets, particularly hypoglycemia (−8.2 kcal/mol) and peripheral analgesic (−8.8 kcal/mol) receptors. C76 (CID: 457801) showed strong binding to hypoglycemia (−9.4 kcal/mol) and central analgesic (−9.3 kcal/mol) receptors. Additionally, for hypoglycemic activity, co‐crystallized ligands such as methyl linoleate showed binding affinities for all targets, including the human pancreatic alpha‐amylase receptor (−9.2 kcal/mol) and the M1 muscarinic acetylcholine receptor (−8.6 kcal/mol). Additionally, it showed central and peripheral analgesic actions at the μ‐opioid receptor (−11.9 kcal/mol) and the COX‐2 receptor (−9.1 kcal/mol). The computational technique is supported by the expected strong interactions of common drugs like miglitol, loperamide, diclofenac, and morphine.

TABLE 7.

Some identified substances with the highest binding affinities and standards to four receptors, indicating hypoglycemic, antidiarrheal, central analgesic, and peripheral analgesic effects.

Compound	CID	Binding affinity (kcal/mol)
		Hypoglycemic	Antidiarrheal	Central analgesic	Peripheral analgesic
		Human pancreatic alpha‐amylase (PDB: 5E0F)	M1 muscarinic acetylcholine receptor (PDB: 5CXV)	μ‐opioid receptor (PDB: 5C1M)	COX‐2 receptor (PDB: 1CX2)
C23	607204	−7.7	−7.7	−7.5	−7.6
C28	7002	−6.3	−7.4	−6.4	−7.6
C31	557446	−7.5	−7.3	−7.6	−7.5
C34	619737	−8.2	−7.4	−8.5	−8.8
C44	600264	−7.2	−8.2	−7.2	−6.4
C65	136909	−6.4	−6.9	−6.8	−7.6
C76	457801	−9.4	−7.3	−9.3	−6.8
Methyl linoleate	14034277	−9.2	—	—	—
Cholesteryl hemisuccinate	65082		−8.6	—	—
BU72	155804574	—	—	−11.9	—
Protoporphyrin	4971	—	—	—	−9.1
Miglitol	441314	−5.8	—	—	—
Loperamide	3955	—	−8.8	—	—
Diclofenac	3033	—	—	—	−6.7
Morphine	5288826	—	—	−8.1	—

Lower binding affinity values (kcal/mol) indicate that predicted interactions between the ligand and protein are stronger. The selected compounds were favorable based on their relatively good docking scores, interactions with active site residues, drug‐likeness, ADMET prediction, QSAR analysis, and relative abundance in the GC‐MS/MS profile. Standard drugs were included so that docking performance could be compared and understood. However, these docking results are just preliminary computational evidence; they do not prove biological activity or therapeutic efficacy on their own.

3.9.2. Protein–Ligand Interaction

Biovia Discovery Studio and PyMOL software were used to create interaction diagrams for drug‐protein combinations, hydrogen bonding, and molecular docking pockets. The protein‐ligand interactions were investigated using key interactions such as conventional and non‐conventional hydrogen bonds, hydrophobic interactions (including pi‐sigma, alkyl, and pi‐alkyl interactions), and hydrogen bond donor and acceptor interactions. Notably, hydrogen bonding and hydrophobic interactions influence medication activity. Figures 3, 4, 5, 6 depict the binding engagements and energy between the chemicals and their target proteins. Different colors are used to indicate the distinct regions involved in hydrogen bonding: the acceptor region is represented by green, while the donor region is represented by violet. Furthermore, 2D depiction of the active amino acid residues is seen, showing that A: TRP59, A: LEU165, and A: TYR62 is generated for human pancreatic alpha‐amylase (PDB: 5E0F) with C23, whereases A: HIS388, A: TRP387, A: ALA199 A: LEU‐391, A: GLY‐48, and A: PHE200 is created during the creation of the PDB ID 1CX2 complex. In addition, the amino acid residues and the bond distances for all the compounds are provided in File S2 (Table S2).

FIGURE 3.

The optimal interactions between the identified ligands and receptors within the binding pocket are illustrated in both 3D and 2D formats. Panels (A–D) demonstrate the specific interactions of C23, C34, C76, and standard (miglitol) with the human pancreatic alpha‐amylase (PDB: 5E0F), respectively.

FIGURE 4.

The optimal interactions between the identified ligands and receptors within the binding pocket are illustrated in both 3D and 2D formats. Panels (A–D) demonstrate the specific interactions of C23, C28, C44, and standard (loperamide) with the M1 muscarinic acetylcholine receptor (PDB: 5CXV), respectively.

FIGURE 5.

The optimal interactions between the identified ligands and receptors within the binding pocket are illustrated in both 3D and 2D formats. Panels (A–D) demonstrate the specific interactions of C31, C34, C76, and standard (morphine) with the Mu (PDB: 5C1M), respectively.

FIGURE 6.

The optimal interactions between the identified ligands and receptors within the binding pocket are illustrated in both 3D and 2D formats. Panels (A–D) demonstrate the specific interactions of C26, C34, C65, and standard (diclofenac sodium) with the COX‐2 (PDB: 1CX2), respectively.

3.9.3. Drug‐Likeness and Lipinski Rule Assessment

The physicochemical characteristics of the selected compounds, as reported in Table 8, support Lipinski's rule of five. All compounds, including C23, C34, and C76, were classified as drug‐like possibilities, with no violations of Lipinski's standards. Most compounds had acceptable MWs and log P values, indicating drug‐likeness. Bioavailability scores for all substances were consistent, with the majority receiving a score of 0.55.

TABLE 8.

Lipinski rule characteristics and the drug‐likeness of selected compounds.

Compound	CID	TPSA (Å2)	Molecular weight (g/mol)	Hydrogen bond acceptor	Hydrogen bond donor	Consensus Log P o/ w	Lipinski rule		Bioavailability score
							Result	Violation
C20	931	0	128.17	0	0	3.10	Yes	1	0.55
C21	9231	0	128.17	0	0	3.04	Yes	0	0.55
C23	607204	20.23	214.30	1	1	3.12	Yes	0	0.55
C26	97391	0	142.20	0	0	3.02	Yes	1	0.55
C28	7002	0	142.20	0	0	3.46	Yes	1	0.55
C31	557446	37.30	220.31	2	1	2.39	Yes	0	0.55
C34	619737	54.86	266.29	2	1	3.01	Yes	0	0.55
C44	600264	0	190.32	0	0	3.86	Yes	1	0.55
C50	100332	46.53	196.24	3	1	1.55	Yes	0	0.55
C65	136909	0	164.29	0	0	4.21	Yes	1	0.55
C76	457801	20.23	414.71	1	1	7.24	Yes	1	0.55
Miglitol	441314	104.39	207.22	6	5	−1.94	Yes	0	0.55
Loperamide	3955	43.78	477.04	3	1	4.67	Yes	1	0.55
Diclofenac	3033	49.33	296.15	2	2	3.66	Yes	0	0.85
Morphine	5288826	52.93	285.34	4	2	1.44	Yes	0	0.55

3.9.4. Pharmacokinetics and Toxicity

Table 9 contains information on the pharmacokinetics and toxicity characteristics of the selected substances. Most compounds have high human intestinal absorption rates, with C76 and C34 exceeding 94%. Except for C34, none of the compounds exhibited Ames toxicity, and there was no hepatotoxicity among them. The renal clearance and distribution volumes indicated moderate systemic stability for the majority of applicants. Standard medicines, such as morphine, showed substantial permeability through the blood‐brain barrier, which is consistent with their therapeutic usage.

TABLE 9.

Data on pharmacokinetics and toxicity properties obtained from SwissADME, admetSAR, and pKCSM online servers.

Compound	Ames toxicity	Absorption		Distribution		Metabolism		Excretion		Toxicity
		Water solubility Log S	Human intestinal absorption (%)	VDss (log L/kg)	BBB Permeability	CYP450 1A2 Inhibitor	CYP450 2D6 Substrate	Total clearance (mL/min/kg)	Renal OCT2 substrate	Max. tolerated dose (log mg/kg/day)	Skin sensitization	Hepatotoxicity
C20	No	−3.496	95.157	0.488	0.434	No	No	0.198	No	0.703	Yes	No
C21	No	−3.654	95.451	0.519	0.77	No	No	0.208	No	0.507	Yes	No
C23	No	−3.378	95.876	0.572	0.269	No	No	0.184	No	0.219	No	Yes
C26	No	−3.724	96.537	0.784	0.455	Yes	No	0.207	No	0.441	Yes	Yes
C28	No	−4.006	96.813	0.728	0.481	Yes	No	0.221	No	0.609	Yes	No
C31	No	−2.602	95.152	0.228	0.127	No	No	1.25	No	0.512	Yes	No
C34	Yes	−3.441	97.256	0.349	0.369	Yes	No	0.227	No	0.05	No	No
C44	No	−5.293	95.107	0.745	0.817	No	No	−0.1	No	−0.015	No	No
C50	No	−1.641	95.691	0.086	−0.223	No	No	1.038	No	0.676	No	No
C65	No	−3.747	95.316	0.428	0.621	No	No	1.421	No	0.644	Yes	No
C76	No	−6.773	94.464	0.193	0.781	No	No	0.628	No	−0.621	No	No
Miglitol	No	−1.229	41.462	−0.607	−1.501	No	No	0.815	No	2.239	No	No
Loperamide	Yes	−4.805	91.456	0.746	0.054	No	Yes	0.692	Yes	0.014	No	No
Diclofenac	No	−3.863	91.923	−1.605	0.236	No	No	0.291	No	0.983	No	No
Morphine	No	−2.95	73.691	1.13	−0.1	No	No	0.858	No	−1.063	No	Yes

3.9.5. Analysis of QSAR and pIC₅₀

As shown in Table 10, analysis of QSAR revealed favorable structural attributes for C34 and C76, with high pIC₅₀ values of 4.80 and 6.49, respectively. The Chiv5 and GATSv4 indices highlighted aromatic and hydrophobic features, which contribute to their high receptor binding efficiency. C44 (CID: 600264) also demonstrated strong activity, with a pIC₅₀ of 5.33, suggesting its potential as a candidate compound for further development.

TABLE 10.

Quantitative structure‐activity relationship (QSAR) and pIC₅₀ properties of selected ligands.

S No.	Chiv5	bcutm1	MRVSA9	MRVSA6	PEOEVSA5	GATSv4	J	Diameter	pIC50
C20	0.757	3.985	10.772	48.531	48.531	0	1.925	5	4.46
C21	0.642	3.915	0	48.531	48.531	0	1.953	5	4.58
C23	2.576	3.93	0	48.047	48.905	1.455	1.819	7	4.77
C26	1.587	3.988	0	47.544	36.418	0	1.842	5	4.49
C28	0.881	4.005	10.772	48.028	42.465	0	1.993	5	4.48
C31	1.991	3.847	5.783	23.298	17.222	1.558	2.042	6	4.24
C34	1.516	4.155	10.772	74.802	31.189	1.706	1.646	11	4.80
C44	3.865	4.084	0	11.146	38.841	0	1.967	5	5.33
C50	1.424	3.902	5.969	11.649	13.847	1.313	2.275	6	4.34
C65	1.114	3.622	0	0	38.525	0	2.0	6	4.35
C76	6.927	3.972	0	11.649	66.033	0.566		15.0	6.49

4. Discussion

To relieve unwanted and uncomfortable body conditions, human civilization was always inclined to use natural resources like plants, herbs, animals, and even minerals from the oceans or mines from ancient times as their primary treatment weapons. Among the natural resources, plants and herbs comprehended vital evidence of medicinal values. Based on this evidence, various medicinal plants have been investigated further to find new therapeutic potentials and bioactive phytochemicals for exerting therapeutic properties. In our study, P. longifolia was investigated to ensure the pharmacological evidence and find some chemical entities responsible for its pharmacological effects.

The GC‐MS/MS analysis was performed for the methanolic leaf extract of P. longifolia to identify phytochemicals present in the plant part. A total of 76 phytochemicals of different categories, such as alcohol, aldehyde, ketone, carboxylic acids, and polyunsaturated oils, have been identified, and most of them are pharmacologically active. Among these compounds, 1H‐1,3‐benzodiazole‐5‐carbaldehyde (5.99%), 4‐vinylphenol (5.71%), 9,12,15‐octadecatrienoic acid, methyl ester, (Z, Z, Z)‐(3.53%), n‐hexadecanoic acid (3.15%), and hexadecane (3.07%) have antioxidant and anticancer activity [36, 37, 38, 39, 58, 59, 60, 61]. The anticonvulsant effect of synthetic 2‐(4‐ethyl‐phenyl)‐2,3‐dihydro‐phthalazine‐1,4‐dione (3.11%) has been reported previously [62]. Some compounds have evidence of effective antibacterial properties, for example, 2H‐pyran, 2‐(2‐heptadecynyloxy)‐tetrahydro‐ (2.48%), and dihydroxyacetone [41, 42, 63, 64]. Numerous compounds have anti‐inflammatory effects, such as 1,2‐cyclopentanedione, which downregulates the NF‐κB signaling cascade [43, 65]. The plant extract also contains lidocaine, which can show anesthetic effects. Our phytochemical evidence proves that P. longifolia is an enriched source of bioactive phytochemicals, and isolation of these bioactive chemicals can be very effective where there is a huge burden to synthesize these compounds.

To treat diabetes, a wide range of glucose‐lowering drugs have been established to increase glucose absorption from blood to muscles, delay glucose absorption from the stomach to systemic circulation, and slow down hepatic gluconeogenesis [44, 45, 66, 67]. Medicinal plants contain tannins, flavonoids, and vitamins that can treat oxidative stress and diabetes [46, 68]. In the study, a glucose tolerance test was performed to assess the hypoglycemic properties of the P. longifolia plant. An in vivo study ensures that the plant has a significant glucose‐lowering tendency. Both the doses (200 and 400 mg/kg) of NHF, CF, and AQF exert significant levels of glucose reduction. After 180 min, 35.78%, 53.01%, and 32.16% reductions were observed for 400 mg/kg of NHF, CF, and AQF, respectively. Compound C76 demonstrated strong binding affinity toward human pancreatic α‐amylase (−9.4 kcal/mol), exceeding the docking score of miglitol (−5.8 kcal/mol), suggesting possible inhibitory potential against carbohydrate‐metabolizing enzymes. Similar glucose‐lowering effects have been reported for several medicinal plants rich in phenolic compounds, flavonoids, fatty acid derivatives, and terpenoids, which are known to improve glucose utilization and suppress carbohydrate digestion [69]. The observed activity of P. longifolia is consistent with previous reports demonstrating that phytochemicals such as loliolide, n‐hexadecanoic acid, phytol, and phenolic derivatives can exert antidiabetic effects through multiple mechanisms, including inhibition of carbohydrate‐hydrolyzing enzymes, enhancement of peripheral glucose uptake, and attenuation of oxidative stress‐induced pancreatic β‐cell damage [70, 71]. The substantial activity observed in the chloroform and aqueous fractions may therefore be attributed to the synergistic action of these phytoconstituents.

Unfolding the antidiarrheal activity of P. longifolia was possible by the castor oil‐induced diarrheal method. The method targeted only secretory diarrhea that occurs due to alterations in the ion transport processes of intestinal epithelial cells, leading to the imbalance of water and electrolytes movement into and out of the intestinal lumen [72]. The findings highlighted that the different fractions of the methanolic leaf extract of P. longifolia exert statistically significant results. Both doses (200 and 400 mg/kg) of the NHF, CF, and AQF exerted a significant reduction in fecal count during the experiment. CF at a 400 mg/kg dose expressed the highest antidiarrheal activity with a 54.79% reduction in defecation count. The observed antidiarrheal activity is comparable to that reported for several medicinal plants traditionally used in the treatment of gastrointestinal disorders. Previous studies have shown that phenolic compounds, terpenoids, fatty acid derivatives, and heterocyclic compounds can reduce intestinal hypersecretion and suppress gastrointestinal motility, thereby alleviating diarrhea [73]. The notable activity of the chloroform and aqueous fractions observed in the present study may therefore be attributed to the synergistic action of multiple phytoconstituents identified through GC–MS/MS analysis, including neophytadiene, benzodiazole derivatives, and other bioactive metabolites that have previously been associated with gastrointestinal protective effects. A plausible mechanism underlying the antidiarrheal effect of P. longifolia may involve inhibition of intestinal secretion and reduction of gastrointestinal motility through modulation of muscarinic receptor‐mediated pathways [74].

The in vivo tail‐flicking method and acetic acid‐induced writhing method were applied to assess the central and peripheral analgesic activity of the leaves of P. longifolia. Both doses (200 and 400 mg/kg) of NHF and AQF expressed significant (p < 0.05) central and peripheral analgesic activity. EAF at a dose of 400 mg/kg exerted the highest percentage (129.72 ± 4.25%) of tail immersion time after 90 min of sample administration. Positive outcomes of the central analgesic activity test confirm that some phytochemicals, present in the plant extract, can pass the blood‐brain barrier and interact with opioid receptors. Besides, a few phytochemicals present in the leaf extract of P. longifolia show peripheral analgesic activity by targeting the cyclooxygenase enzyme of the prostaglandin synthetic pathway. The analgesic effects observed in the present study may also be partially attributed to the antioxidant constituents identified in the extract. Oxidative stress has been implicated in the sensitization of nociceptive pathways and amplification of inflammatory responses [75]. Polyphenolic compounds, phytol derivatives, vitamin E, γ‐sitosterol, and other antioxidant phytochemicals identified through GC–MS/MS analysis may contribute to pain reduction by suppressing ROS and inflammatory mediator production [76]. Consequently, the analgesic activity of P. longifolia is likely mediated through a combination of opioid receptor‐associated central mechanisms, inhibition of inflammatory mediators, and antioxidant effects [77].

The ability of natural products to donate electrons can be measured based on the scavenging of 2,2^′‐diphenyl‐1‐ picrylhydrazyl radical (DPPH) through the addition of a plant extract and standard antioxidants. The study confirmed the ability of the leaf extract of P. longifolia to scavenge the DPPH radicals with the lowest IC₅₀ values of 31.81 and 34.93 µg/mL for AQF and CF, respectively. The plant possesses many polyphenolic compounds such as 4‐vinylbenzene‐1,2‐diol, phytol, cis‐11‐eicosenamide, squalene, vitamin E, and gamma‐Sitosterol is responsible for the antioxidant potential of the crude plant extract. The antioxidant activity observed in the present study is comparable to previous reports on medicinal plants rich in polyphenols, flavonoids, terpenoids, phytosterols, and unsaturated fatty acid derivatives. Several studies have demonstrated that plant extracts exhibiting DPPH scavenging activity within a similar concentration range possess significant antioxidant potential and may contribute to the prevention of oxidative stress‐related disorders [78]. The stronger activity observed in the aqueous and chloroform fractions suggests that polar and moderately polar phytochemicals are likely responsible for the radical scavenging effects. A plausible mechanism underlying the phenolic hydroxyl groups and unsaturated phytochemicals identified in the extract may donate electrons or hydrogen atoms to DPPH radicals, converting them into stable non‐radical forms.

The molecular docking study supported the hypoglycemic activity observed in vivo. Among the selected compounds, C76 exhibited the highest binding affinity toward human pancreatic α‐amylase (−9.4 kcal/mol), followed by C34 (−8.2 kcal/mol), both of which showed stronger interactions than the standard drug miglitol (−5.8 kcal/mol). The formation of hydrogen bonds and hydrophobic interactions within the active site suggests that these compounds may interfere with carbohydrate digestion and subsequent glucose absorption. This observation is consistent with the significant reduction of blood glucose levels observed in the oral glucose tolerance test. However, the docking results represent only a predictive model and require further enzyme inhibition studies to confirm α‐amylase inhibitory activity. The docking analysis demonstrated favorable interactions between several identified compounds and the M1 muscarinic acetylcholine receptor, a target involved in regulating intestinal motility and secretion. Notably, C44 showed a binding affinity of −8.2 kcal/mol, approaching that of the standard drug loperamide (−8.8 kcal/mol). The interaction with key amino acid residues within the receptor‐binding pocket suggests a potential role in modulating gastrointestinal motility, which may partially explain the significant reduction in diarrheal episodes observed in vivo. Nevertheless, further pharmacological studies are necessary to verify the exact mechanism of action. For central analgesic activity, compounds C76 and C34 exhibited strong binding affinities toward the μ‐opioid receptor (−9.3 and −8.5 kcal/mol, respectively), exceeding or closely approaching the binding affinity of morphine (−8.1 kcal/mol). The identified hydrogen‐bonding and hydrophobic interactions indicate a favorable ligand–receptor association that may contribute to modulation of nociceptive signaling pathways. These findings correlate with the significant prolongation of tail immersion latency observed in the experimental animals. However, receptor‐binding studies are required to establish whether these compounds act as opioid receptor agonists or modulators.

The molecular docking results indicated that C34 exhibited the strongest interaction with COX‐2 (−8.8 kcal/mol), followed by several other compounds that demonstrated stable binding within the enzyme active site. Interestingly, the binding affinity of C34 was stronger than that of diclofenac sodium (−6.7 kcal/mol), suggesting a potential ability to interfere with prostaglandin biosynthesis. This observation is consistent with the reduction in acetic acid‐induced writhing responses observed experimentally. Nevertheless, docking results alone cannot confirm COX‐2 inhibition, and additional biochemical assays are required to validate this mechanism.

Although no specific antioxidant‐related receptor was investigated in the molecular docking study, the docking findings indirectly support the pharmacological potential of the identified phytochemicals. Several compounds that exhibited favorable binding affinities toward the investigated targets, particularly C34 and C76, also possess structural features associated with antioxidant activity. Together with the presence of known antioxidant constituents such as phytol, vitamin E, squalene, and γ‐sitosterol identified by GC–MS/MS, these findings suggest that the antioxidant activity of P. longifolia may contribute to its overall therapeutic effects. However, the antioxidant activity is primarily supported by the DPPH assay rather than the molecular docking analysis.

Lipinski's rule determines whether a biochemical molecule with a specific pharmacological or biological activity possesses molecular attributes and physical characteristics that make it a likely orally administered drug in mammals [79]. All selected compounds adhered to Lipinski's rule of five, confirming their drug‐like properties, with favorable MWs, hydrogen bonding profiles, and bioavailability scores. ADMET properties have a considerable impact on therapeutic absorption, distribution, metabolism, solubility, and oral bioavailability. Computational approaches are effective for anticipating these characteristics during medication development. Water solubility is particularly important for current oral medication administration since more soluble medicines have higher bioavailability and absorption rates [80, 81]. Pharmacokinetic analysis further revealed high intestinal absorption rates and low toxicity profiles for most compounds, although C34 exhibited Ames toxicity, suggesting a need for structural optimization. The quantitative structure‐activity relationship (QSAR) is a widely employed method in ligand‐based drug design [82]. The QSAR analysis underscored the importance of aromatic and hydrophobic features, as seen in C34 and C76, which also correlated with their strong binding affinities. Molecular interaction studies confirmed the stability and specificity of these compounds, with robust hydrogen bonding and π‐π stacking interactions.

Overall, compounds like C34 and C76 emerge as promising candidates for further experimental validation, combining high efficacy, drug‐likeness, and favorable pharmacokinetic profiles. Future studies should focus on optimizing their structures and validating their in vitro and in vivo pharmacological activities.

5. Limitations and Future Directions

There are some limitations in this study. The pharmacological evaluations were performed using crude plant extracts and not isolated bioactive components, and hence, it is difficult to identify the specific phytochemicals responsible for the reported effects. Also, the absence of bioassay‐guided fractionation and compound isolation prohibits the direct attribution of the pharmacological activity to individual ingredients, and the potential for synergistic interactions between several compounds cannot be eliminated. Furthermore, the in vivo studies were performed with a relatively small sample size (n = 6), which may impact the statistical power and reproducibility of the findings. Seasonal variation effects on phytochemical composition were not studied. Moreover, the use of these treatments on people is still questionable despite encouraging outcomes in animal models and requires further confirmation in clinical research. The study employed preliminary screening models, such as OGTT and acetic acid‐induced writhing, to offer a limited mechanistic understanding. Additionally, no exhaustive biochemical or molecular experiments were conducted to elucidate the underlying pathways associated with the observed pharmacological effects. The study assessed the impact of P. longifolia on glucose tolerance in normoglycemic mice, but it also recognized the significance of utilizing diabetic models to gain a more comprehensive understanding of diabetes. It emphasizes that future research should concentrate on diabetic animals that have been induced with streptozotocin or alloxan to investigate the antidiabetic properties of P. longifolia. Computational analyses, including molecular docking, ADMET, and QSAR studies, provided predictive evidence that lacked experimental validation. The study did not include additional methods such as molecular dynamics simulations, MM‐PBSA free energy calculations, enzyme inhibition assays, receptor‐binding studies, isolated compound testing, or in vivo pharmacokinetic evaluations. Consequently, docking scores and predicted interactions should not be viewed as conclusive evidence of pharmacological activity. The antioxidant assessment was confined to the DPPH assay without supporting docking studies against antioxidant‐related targets. Therefore, future research should focus on diabetic animal models, isolation, and characterization of active compounds, mechanistic studies, comprehensive toxicity assessments, molecular validation experiments, and ultimately human clinical investigations to confirm the therapeutic potential of the plant.

6. Conclusion

The present study provides a comprehensive evaluation of the phytochemical composition and pharmacological potential of P. longifolia leaves through integrated GC–MS/MS, in vitro, in vivo, and in silico approaches. GC–MS/MS analysis identified 76 phytochemical constituents, including several bioactive compounds such as phytol, loliolide, squalene, vitamin E, and γ‐sitosterol, which are known for diverse biological activities. The methanolic leaf extract and its fractions exhibited significant hypoglycemic, antidiarrheal, analgesic, and antioxidant activities, with the chloroform fraction showing the most prominent hypoglycemic and antidiarrheal effects, the n‐hexane fraction demonstrating notable central analgesic activity, the ethyl acetate fraction exhibiting moderate peripheral analgesic activity, and the aqueous fraction displaying the strongest antioxidant potential. Acute toxicity studies indicated a favorable safety profile at the tested doses.

Molecular docking analysis revealed favorable interactions of selected compounds with human pancreatic α‐amylase, M1 muscarinic acetylcholine receptor, μ‐opioid receptor, and COX‐2, supporting the experimentally observed pharmacological activities. Furthermore, drug‐likeness, ADMET, and QSAR analyses suggested that several identified compounds possess promising pharmacokinetic and safety characteristics. However, the computational findings should be regarded as predictive and require further experimental validation. Overall, the results suggest that P. longifolia is a promising source of bioactive phytochemicals with potential therapeutic applications against oxidative stress, hyperglycemia, diarrhea, and pain‐related disorders.

Author Contributions

Md. Rasul Karim: conceptualization, methodology, supervision. Md. Alfaz Hossain: methodology, validation, data curation, writing – original draft. Md. Shamim: writing – original draft, validation, data curation. Md. Riaz Hosen: methodology, visualization, validation. Md. Sabbir Hossain: visualization, modified the draft. Md. Tanvir Hossain: formal analysis and writing – original draft. Mst. Sumaya Akhter: visualization and writing – original draft. Khadija Tul Simran: validation, modified the draft. Md. Saiful Islam: conceptualization and supervision.

Funding

The authors have nothing to report.

Ethics Statement

The Animal Ethics Committee at the Faculty of Biological Science, University of Dhaka, conducted a panoramic assessment of the ethical guidelines and protocols of the investigation and generated their systematic review and approval (Ref. No. 270/Biol. Sci.) (File S1).

Conflicts of Interest

The authors declare no conflicts of interest.

Supporting information

Supporting File 1: cbdv71574‐sup‐0002‐SupMat‐File‐2.docx

Supporting File 2: cbdv71574‐sup‐0001‐SupMat‐File‐1.pdf

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.