Bombax ceiba extract and its metabolites as α-glucosidase inhibitors for diabetes

1 Introduction

Diabetes mellitus (DM) is among the swiftly burgeoning global health emergencies. In 2021, diabetes mellitus (DM) accounted for 537 million cases and resulted in 6.7 million fatalities. Projections indicate that these numbers will escalate to over 643 million cases by 2030 and reach a staggering 783 million cases by 2045 (Sun et al., 2022). Approximately 90 % individuals who have diabetes but remain undiagnosed lived in low and middle-income countries. Pakistan is the third most affected country with DM after China and India. About 33 million people in Pakistan are living with diabetes. This disease is not only an everyday health challenge but a financial one as well. The estimated global cost for diabetes is 825 billion USD annually (Febrian et al., 2023).

Currently available diabetes medications target various pathways and enzymes which take part in glucose homeostasis, with the aim of normalizing blood glucose levels. Among these, α-glucosidase inhibitors are an intriguing class of drugs. These enzymes assist in the digestion of dietary carbohydrates and breaking them down into glucose in small intestine. Consequently, this process results in an elevation of blood glucose levels. By reversibly inhibiting α-glucosidase enzymes postprandial hyperglycemia can be effectively reduced (Derosa and Maffioli, 2012). In contrast to other medications that maintain blood glucose levels, such as sulfonylureas, meglitinides, and insulin, α-glucosidase inhibitors do not cause obesity or hypoglycemia (Hossain et al., 2018). Moreover, urthermore, there are reports indicating that α-glucosidase inhibitors have the potential to reduce the risk of type II diabetes by 35.6 %. Importantly, this effect remains consistent across diverse patient populations, regardless of age, gender, or body mass index (BMI), thus highlighting their efficacy (Daou et al., 2022). Additionally, α-glucosidase inhibitors have also vaso-protective efficacy by lowering postprandial glucose levels, that is associated with endothelial abnormality, heart disease, and stroke (Matsui et al., 2001, Joshi et al., 2015). Although commercially available α-glucosidase inhibitors effectively lower blood sugar levels, they can potentially lead to gastrointestinal discomfort, diarrhea, and flatulence. (Akmal and Wadhwa, 2022). So, there is need to develop safer and novel natural inhibitors of α-glucosidase to manage diabetes mellitus.

Plants have thus long been one of the most reliable resources for medicines to treat diseases. Plant-based anti-diabetic medications have been used extensively from the earliest days since they are far more affordable and safer than synthetic drugs (Alam et al., 2022). To address the goals of this study, we have initially screened plant extracts library by using an in vitro based enzyme inhibitory assay for the α-glucosidase inhibitors identification. B. ceiba commonly known as red silk-cotton tree, belongs to the family Bombacaceae (Rameshwar et al., 2014). Approximately 250 species are found in this family (Rani et al., 2016). In Unani system of medicine, more emphasized to the use of gummy exudate known as mochras. This whole plant is used in different traditional medical systems. It has a number of therapeutic uses including Burning Micturition, Dysentry, Spermatorrhoea, Vaginal Discharge, Stomatitis, Diarrhoea, Haemoptysis, Dribbling of Urine, Bed Wetting, Menorrrhagia, Loosen Tooth, Bleeding Gums, and Blood Diseases. (Shukla et al., 2020).

B. ceiba showed different pharmacological activities such as anti-inflammatory, asthma, small-pox boils, wound healing, hypotensive, anti-oxidant, anti-pyretic, anti-analgesic and hepatoprotective activity (Rani et al., 2016).

In this study we explore first time anti-hyperglycemic properties of B. ceiba bark and its metabolites which showed significantly higher α-glucosidase inhibition than control (acarbose). Moreover, this work intends to investigate the enzyme kinetics and protein–ligand interactions of literature-based phytochemicals library of B. ceiba. We found nine potent hits including Pelargonin, Simalin B, Linarin, Rutin, Nicotiflorin, Simalin A, Mangiferin, Quercetin, and Apigenin on the base of lowest docking score (Joshi et al., 2014, Verma et al., 2015). Additionally, enzyme-based screening of commercially available potent hits was also carried out to validate their inhibitory efficacy against α-glucosidase. Through our computational and in vitro investigations, we have gathered substantial evidence demonstrating that B. ceiba and its metabolites exhibit remarkable ability to selectively target α-glucosidase. These findings may be useful for the development of new anti-diabetic drugs designed to effectively reduce hyperglycemia.

2 Materials and methods

3 Results

3.1

3.1 Screening of plant extracts library against α-glucosidase

A library of 51 extracts of different parts of 35 plants were initially screened against α-glucosidase at 50 µg/mL and obtained results has been presented in Table 1. From these extracts, 19.6 % (10 plant extracts) showed high (>80 %) inhibition against α-glucosidase, 25.4 % (13 plant extracts) exhibit moderate (41 %-70 %) and 54.9 % (28 plant extracts) represent insignificant and low (0–40 %) inhibitory activity. Potent plant extracts from first screening were further screened at lower concentration (10 µg/ml) to find the most effective plant against α-glucosidase. After secondary screening B. ceiba bark was found highly effective against α-glucosidase and further tested at different concentrations (0.5, 1, 2, 4, 8, 16, 32 µg/mL) against α-glucosidase by using PNPG substrate. B. ceiba exhibited higher inhibition with IC₅₀ 1.95 ± 0.29 µg/mL, as compared to acarbose control 3.14 ± 0.49 µg/mL which clearly indicated significant inhibitory potential of B. ceiba as compared to acarbose (Fig. 1).

Table 1 Identification of α-glucosidase inhibitors from a library of plant extracts.

Sr. No.	Scientific names	Common names	Family	Parts	Extract no.	α-glucosidase activity
1	Aloe barbadensis	Aloe vera	Asphodelaceae	Complete plant	1	+++
2	Azadirachta indica	Indian lilac	Meliaceae	Leaves	2	+++
3	Nerium oleander	Oleander	Apocynaceae	Leaves	3	_
4	Albizia lebbeck	Lebbeck	Fabaceae	Leaves	4	+
				Seed	5	+
				Flowers	6	+
				Seed coat	7	+
5	Momordica charantia	Bitter gourd	Cucurbitaceae	Seeds	8	++
				vegetable	9	+
6	Cyamopsis tetragonoloba	Guar gum	Fabaceae	Seeds	10	_
7	Oxalis corniculata	Wood-sorrel	Oxalidaceae	Whole plant	11	_
8	Cassia fistula	Golden shower	Fabaceae	Leaves	12	++
				Bark	13	+++
9	Ageratum conyzoides	Goat weed	Asteraceae	Complete plant	14	_
10	Dalbergia sissoo	Indian rosewood	Fabaceae	Seeds	15	_
				Bark	16	+
11	Chenopodium album	Lamb’s quarters	Amaranthaceae	Entire plant	17	_
12	Bombax ceiba	Cotton tree	Bombacaceae	Bark	18	+++
				Leaves	19	+++
13	Cicer arietinum	Chickpea (white)	Fabaceae	Seeds	20	+
		Chick pea (black)		Seeds	21	+
14	Smilax china L.	China root	Smilacaceae	Root	22	+
15	Helianthus annuus	Sun flower	Asteraceae	Seeds	23	+++
16	Peganum harmala	Wild Rue	Nitrariaceae	Whole Plant	24	_
17	Litchi chinensis Sonn.	Lychee	Sapindaceae	Seeds	25	++
				Bark	26	+++
				Leaves	27	++
18	Eucalyptus camaldulensis	Himalayan poplar	Myrtaceae	Bark	28	+++
19	Cyperus esculentus	Water grass	Cyperaceae	Flowers	29	+++
20	Artemisia absinthium	Common wormwood	Asteraceae	Whole plant	30	_
21	Ferula assa-foetida	Heng	Umbelliferae	Resin	31	_
22	Lawsonia inermis	Henna	Lythraceae	Leaves	32	_
23	Fagonia arabica	Dhamasa	Zygophyllaceae	Whole plant	33	_
24	Solanum nigrum	Black night shade	Solanaceae	Complete plant	34	++
25	Mangifera indica L.	Mango	Anacardiaceae	Pulp	35	+
				Seed coat	36	++
				Bark	37	+++
				Peels	38	++
				Seed	39	++
				Leaves	40	++
26	Asphodelus tenuifolius	Wild onion	Asphodelaceae	Whole plant	41	++
27	Linum usitatissimum	Flax seeds	Linaceae	Seeds	42	_
28	Coriandrum sativum	Coriander	Apiaceae	Seeds	43	_
29	Citrullus colocynthis	Desert bitter gourd	Cucurbitaceae	Fruit	44	_
30	Acacia farnesiana	Thorn Mimosa	Fabaceae	Seeds	45	_
31	Trigonella foenum-graecum L.	Fenugreek	Fabaceae	Seed	46	_
32	Punica granatum	Pomegranate	Lythraceae	Peels	47	++
				Seed	48	++
33	Cucumis melo agrestis	Wild melon	Cucurbitaceae	Leaves	49	_
34	Calotropis procera	Sodom apple	Apocynaceae	Leaves	50	_
35	Citrus maxima	Chinese grapefruit	Rutaceae	Bark	51	++

Here +++ indicating above 80 % inhibition, ++ for 61 %-79 % and + for below 40–60 % and – for below 40 %.

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Fig. 1

Percentage α-glucosidase inhibition with increased concentrations of B. ceiba extract and acarbose. The obtained IC50 was 1.95 ± 0.29 µg/mL for B. ceiba. The experiment is repeated in triplicates with mean ± standard deviation. Where (*) for p < 0.05, (**) for p < 0.005, (***) for p < 0.0005.

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3.2

3.2 Identification of α-glucosidase inhibitors from b. Ceiba via in silico-based screening

Docking studies on seventy-eight phytochemicals of B. ceiba was done to evaluate their affinities with substrate binding sites of α-glucosidase (ID: 3A4A). The binding sites and respective details for each compound using the Molegro Virtual Docker (MVD) program package at α-glucosidase binding site are exhibited in Fig. 2. Already reported inhibitor compound acarbose served as a control in this experiment. The docking scores obtained with the α-glucosidase binding site are shown in Table 2. Out of 78 phytochemicals nine compounds (Pelargonin, Simalin B, Linarin, Rutin, Nicotiflorin, Simalin A, Mangiferin, Quercetin, and Apigenin) were found highly potent with best binding score. Pelargonin, Simalin B, Linarin, Rutin, Nicotiflorin, Simalin A, Mangiferin, Quercetin, Apigenin and acarbose at the α-glucosidase cavity scored were found to be −174.28 Å, −161.08 Å, −146.68 Å, −142.24 Å, −134.14 Å, 125.94 Å, 110.57 Å, −102.5 Å, −102.45 Å and −107.89 Å respectively.

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Fig. 2

Three-dimensional representation depicting the selected docked complex with maltase-glucoamylase, an α-glucosidase enzyme.

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Table 2 MolDock score of top hit compounds at the binding sites of α-glucosidase.

Alpha-glucosidase binding activity
Compounds	PubChem CID	MolDock Score	HBond
Pelargonin	441,772	−174.28	−22.81
Simalin B	102,217,963	−161.08	−10.41
Linarin	5,317,025	−146.68	−16.15
Rutin	5,280,805	−142.24	−16.56
Nicotiflorin	5,318,767	−134.14	−12.29
Simalin A	102,217,962	−125.94	−15.39
Mangiferin	5,281,647	−110.57	−9.42
Quercetin	5,280,343	−102.50	−10.98
Apigenin	5,280,443	−102.45	−8.57
Acarbose	41,774	−107.89	−16.98

Table 3 illustrate the interaction details among nine hit phytochemicals and amino acids residues at binding cavity. The top hit compound, Pelargonin binds with the α-glucosidase binding complex through conventional hydrogen bond (GLN279, ARG442 and POS1), Carbon Hydrogen Bond (POS1) and Pi-doner hydrogen bond with ASP303. It also showed hydrophobic interactions, Pi-Pi Stacked and Pi-Alkyl with PHE303 and POS1 respectively. Second hit Simalin B, binds with the α-glucosidase binding complex through conventional hydrogen bond (ASP215, GLU411, ARG442 and POS2), Carbon Hydrogen Bond ARG315 and POS2. It also showed hydrophobic interactions Alkyl (POS2), and Pi alkyl (TYR72, TYR158, PHE314, TYR316, HIS351 and POS2).

Table 3 The amino acids and the types of interactions involved in the binding with α-glucosidase.

Pelargonin				Simalin B				Linarin				Rutin
T	C	Interacting residues	D	T	C	Interacting residues	D	T	C	Interacting residues	D	T	C	Interacting residues	D
Hydrogen Bond	Conventional Hydrogen Bond	GLN279	2.62	Hydrogen Bond	Conventional Hydrogen Bond	ASP215:OD1	2.65	Hydrogen Bond	Conventional Hydrogen Bond	THR306:HG1	2.51	Hydrogen Bond	Co. HB	GLN279	2.43
		GLN279	2.80			GLU411:OE2	2.55			ARG315:HN	1.74			GLN279	2.39
		ARG442	2.33			ARG442:HH21	2.36			POS4:H17	2.35			POS5	1.72
		ARG442	1.84			POS2:H20	2.26			POS4:H18	1.63			POS5	1.51
		ARG442	2.23			POS2:H20	2.87			POS4:H19	2.16			POS5	2.32
		POS1	2.09			POS2:H24	1.81			POS4:H20	2.37			POS5	2.13
		POS1	2.43			POS2:H25	1.67			POS4:H21	2.70			POS5	2.13
		POS1	2.41			POS2:H26	1.66			POS4:H25	1.59		Ca. HB	POS5:H6	2.87
		POS1	2.43			POS2:H27	2.03			POS4:H25	2.15			POS5:H8	2.80
		POS1	1.71			POS2:H28	2.42		Ca. HB	PHE314	2.51			POS5:H10	2.48
		POS1	2.33			POS2:H29	1.63			POS4	1.39			POS5:H11	2.78
	Ca. HB	POS1:H2	2.77		Ca. HB	ARG315:HD1	2.69			POS4	2.96	H	Pi -S	POS5:H5	2.45
		POS1:H3	2.29			POS2:H5	1.62			POS4	2.75		Alkyl	POS5:C12	4.16
		POS1:H10	2.28			POS2:H14	2.43	E	Pi- Anion	GLU277	3.81		Pi-Pi T-shaped	TYR158	4.19
		POS1:H14	3.06			POS2:H15	2.63				PHE178	5.06
	Pi-D HB	ASP307	3.51			POS2:H16	2.76
H	Pi-Pi S	PHE303	5.27			POS2:H18	2.97
		PHE303	4.44			POS2:H40	2.41	H	Pi-Pi S	PHE303	4.07	E	Pi-Cation	ARG442:NH1	3.49
	Pi-Alkyl	POS1	4.59	H	Alkyl	POS2:C25	3.65			PHE303	4.57		Pi-Anion	GLU277:OE2	4.61
				POS2:C26	4.39		Pi-Alkyl	TYR72	5.14			ASP352:OD1	4.75
			Pi-Alkyl	TYR72	3.32			TYR158	3.80			GLU411:OE2	4.83
				TYR158	3.70			PHE178	4.18
				PHE314	3.81			POS4	5.05	H	Pi-Pi T-shaped	TYR72	5.74
				TYR316	4.11
				HIS351	4.35
				POS2	4.85
Nicotiflorin				Simalin A				Mangiferin				Quercetin
T	C	Interacting residues	D	T	C	Interacting residues	D	T	C	Interacting residues	D	T	C	Interacting residues	D
Hydrogen Bond	Co. HB	ARG442:HH12	2.54	Hydrogen Bond	Conventional Hydrogen Bond	GLN279:HE22	1.76	Hydrogen Bond	Conventional Hydrogen Bond	ARG213:HH21	2.41	Hydrogen Bond	Conventional Hydrogen Bond	GLN279:HE21	2.66
		POS6:H17	2.67			ARG442:HH11	2.50			GLU411:OE2	3.35			GLN279:HE22	1.88
		POS6:H19	1.75			ARG442:HH12	2.59			POS3:H8	1.68			ARG315:HE	2.20
		POS6:H21	1.88			POS4:H15	1.84			POS3:H9	2.66			ARG442:HH12	2.62
		POS6:H29	2.30			POS4:H16	1.91			POS3:H13	1.94			POS2:H7	1.79
	Ca. HB	ARG315:HD2	2.39			POS4:H17	2.44			POS3:H17	2.76			POS2:H8	2.15
		POS6:H1	2.53			POS4:H25	2.24			POS3:H18	1.70			POS2:H9	1.65
		POS6:H8	2.67		Ca. HB	POS4:H2	2.37		Ca. HB	ARG315:HD1	2.29			POS2:H10	1.60
		POS6:H9	1.97			POS4:H6	1.48			POS3:H1	2.45	H	Pi-Pi T-shaped	TYR72	5.74
	Pi-Lone Pair	TYR158:O	2.91			POS4:H9	1.86			POS3:H1	2.81	E	Pi-Cation	ARG442:NH1	3.49
Others	Pi-Pi S	TYR158	5.35			POS4:H27	2.51			POS3:H4	2.18		Pi- Anion	GLU277:OE2	4.61
H	Pi-Alkyl	PHE178	4.88		Pi-D HB	GLU277:OE2	3.78	H	Pi-Pi T-shaped	TYR158	5.44			ASP352:OD1	4.75
		POS6	5.11	H	Pi-Pi Stacked	PHE178	5.07			TYR158	5.02			GLU411:OE2	4.83
		Pi-Alkyl	TYR72	3.54		Pi-Alkyl	POS3	5.46
			HIS351	4.73
			POS4	4.99

Apigenin				Acarbose
T	C	Interacting residues	D	T	C	Interacting residues	D
Hydrogen Bond	Conventional Hydrogen Bond	ARG442:HH12	2.52	Hydrogen Bond	Conventional Hydrogen Bond	GLN279:HE22	2.59
		POS3:H8	1.99			POS1:H11	2.25
		POS3:H9	1.87			POS1:H26	2.50
	Ca. HB	ARG315:HD2	2.39			POS1:H28	2.84
E	Pi-Cation	ARG442:NH1	1.82			POS1:H37	2.21
H	Pi-Pi S	PHE178	3.94			POS1:H38	1.58
	Pi-Pi T-shaped	TYR72	5.68			POS1:H39	1.66
	Pi-Alkyl	POS3	5.07			POS1:H40	1.68
			POS1:H41	2.17
			POS1:H42	2.15
			POS1:H43	1.69
		Ca. HB	POS1:H1	2.38
			POS1:H8	1.61
			POS1:H9	2.58
			POS1:H15	2.33
			POS1:H16	2.82
			POS1:H23	2.99
			POS1:H35	2.00
		Pi-D HB	POS1:H36	2.46
	H	Pi −S	POS1:H17	2.68

Here, T represent Types, C represents Category, D represents Distance (Å), H = Hydrophobic interactions E represents Electrostatic interactions, Pi-S: Pi Sigma, Pi-Pi S represents Pi-Pi Stacked, Pi-A = Pi-Alkyl, Pi-DHB = Pi-Donor Hydrogen Bond, Ca.HB = Carbon Hydrogen Bond, Pi-C = Pi-Cation

Linarin being third potent hit, binds with the α-glucosidase binding complex through conventional hydrogen bond (THR306, ARG315, and POS4), Carbon Hydrogen Bond (PHE314 and POS4). It also showed electrostatic interaction (Pi-anion) with GLU277 and hydrophobic interactions, Pi-Pi S and Pi-Alkyl with PHE303 and TYR72, TYR158, PHE178, POS4 respectively. The interaction detail between the nine selected compounds (Pelargonin, Simalin B, Linarin, Rutin, Nicotiflorin, Simalin A, Mangiferin, quercetin and apigenin) and amino acids residue at the substrate binding site of α-glucosidase are presented in Table 3.

3.3

3.3 Physicochemical properties of potent hits via computational analysis

Hit compounds were selected on the base of their lowest docking score values and significant binding interactions with α-glucosidase. The top hits were chosen for further evaluation of their physicochemical properties and drug-likeness. The radar plot depicted in Fig. 3 provides a clear indication that the hit compounds possess suitable physicochemical properties for oral provision. While some compounds deviated slightly from the rules, as shown in Table 4, all these phytochemicals obey Pfizer rule’s requirements. According to this rule, the molecular weight (MW) should be in range of 100 ∼ 600 g/mol, the logarithm of the partition coefficient (MlogP) should be < 5, the hydrogen bond acceptors number (nHA) should be < 10, and the number of hydrogen bond donors should be in range of 0 ∼ 7. Furthermore, these compounds demonstrated drug-like properties in terms of medicinal chemistry characteristics, as they complied with the drug rules of Pfizer criteria. This suggests that these phytochemicals have the potential to serve as viable drug candidates.

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Fig. 3

Showing the physicochemical properties of potent hits in radar plot. Brown area represents the upper limit, the blue area represents the compound's property, and the pink area represents the lower limit of the physicochemical property.

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Table 4 Physicochemical properties of potent hits.

Physicochemical properties	Optimal	Pelargonin	Simalin B	Linarin	Rutin	Nicotiflorin	Simalin A	Mangiferin	Quercetin	Apigenin	Acarbose
Molecular Weight (MW)	100 ∼ 600	595.17	624.23	592.18	610.15	594.16	492.15	422.08	302.040	270.050	645.250
nHA	0 ∼ 12	15	17	14	16	15	14	11	7	5	19
nHD	0 ∼ 7	10	8	7	10	9	8	8	5	3	14
nRot	0 ∼ 11	7	10	7	6	6	8	2	1	1	9
nRing	0 ∼ 6	5	4	5	5	5	3	4	3	3	4
MaxRing	0 ∼ 18	10	6	10	10	10	6	14	10	10	6
nHet	1 ∼ 15	15	17	14	16	15	14	11	7	5	19
nRig	0 ∼ 30	29	24	30	30	30	19	23	18	18	24
TPSA	0 ∼ 140	250.52	244.91	217.97	269.43	249.2	225.06	201.28	131.360	90.900	321.170
logS	−4 ∼ 0.5	−2.732	−0.687	−3.890	−3.928	−3.952	−1.085	−3.626	−3.671	−3.606	0.377
logP	<5	−0.921	−2.046	0.386	−0.763	−0.553	−1.977	−0.521	2.155	3.307	−4.370
logD	1 ∼ 3	0.748	−0.283	1.792	0.695	1.052	0.181	0.039	1.767	2.704	−2.523
Medicinal chemistry	Pfizer Rule	Accepted	Accepted	Accepted	Accepted	Accepted	Accepted	Accepted	Accepted	Accepted	Accepted

3.5

3.5 In vitro α-Glucosidase inhibition assay for bioactive compounds

Commercially available phytochemicals were further tested against α-glucosidase to validate our in silico results. For this purposes Apigenin, Quercetin and Mangiferin were used against α-glucosidase to determine their inhibitory activity. The inhibitory effect of the Apigenin, Quercetin and Mangiferin was compared with B. ceiba extract. B. ceiba showed IC₅₀ at a concentration of 1.95 ± 0.29 µg/mL, on the other hand Apigenin, Quercetin and Mangiferin showed higher inhibition against α-glucosidase with IC₅₀ values at a lower concentration of 0.83 ± 0.07 µg/mL, 0.96 ± 0.01 µg/mL and 1.47 ± 0.16 µg/mL respectively Fig. 4.

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Fig. 4

α-Glucosidase inhibition (%age) by increasing concentrations of Apigenin, Quercetin and Mangiferin as compared to acarbose. The resulting IC₅₀ values are 0.83 ± 0.07 µg/mL for Apigenin, 0.96 ± 0.01 µg/mL for Quercetin and 1.47 ± 0.16 µg/mL for Mangiferin. The experiment was repeated in triplicates (n = 3) mean values ± Standard deviation.

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4 Discussion

Plants and their derived compounds have long been used as a valuable source of medicines for the treatment of diseases. In particular, plant-based anti-diabetic medications have been widely utilized since ancient times due to their affordability and safety as compared to synthetic drugs. (Alam et al., 2022). In this study we screened 51 extracts of different parts of 35 plants against α-glucosidase. Glucosidases catalyze dietary carbohydrates from the small intestine and facilitate their absorption, specifically their glucose contents (Ahamad et al., 2011). From this screening, B. ceiba was found highly potent inhibitor of α-glucosidase. Different studies have shown that B. ceiba bark is a chief source of flavonoids, as compared to phenolic compounds where Apigenin and Quercetin are common flavonoids in B. ceiba extract and have anti-diabetic potential due to intestinal α-glucosidases inhibition (Vaghasiya et al., 2011, Hassan, 2018, Depani et al., 2019). PNPG substrate was used to investigate the inhibitory potential of B. ceiba against α-glucosidase. Similar results also reported by Hung et al.,2019 that, the isolated compounds from Root extract of Bombax malabarica showed alpha glucosidease activity of shorealactone with IC₅₀ values 224 μM, l-epicatechin 5-O-β-D-xyloside with IC₅₀ values 345 μM, and 2-C-[β-D-apiosyl-(1 → 6)]- β-D-glucosyl]-1,3,6-trihydroxy-7-methoxyxanthone with IC₅₀ values 285 μM (Lam et al., 2019).

Inhibitory concentration (IC₅₀) was 1.95 ± 0.29 µg/mL in B. ceiba, represent higher inhibition than already reported α-glucosidase inhibitor acarbose (IC₅₀: 3.14 ± 0.49 µg/mL). There are different plants such as Allium sativum (Eidi et al., 2006), Gymnema sylvestre (Spasov et al., 2008), Citrullus colocynthis (Gurudeeban and Ramanathan, 2010), Trigonella foenum greacum (Renuka et al., 2009), Momordica charantia (Chaturvedi, 2012), Ficus bengalensis (Gayathri and Kannabiran, 2008), Syzygium cumini (Kumar et al., 2008) etc. already have been reported showing better antidiabetic potential than commercially available medicines. The demand for novel drugs with enhanced effectiveness and reduced toxicity remains persistent. The drug discovery and development procedure is highly expensive and time killing. In addition to the obstacles encountered during target validation and hit identification, clinical trials frequently show a significant failure rate due to factors such as insufficient pharmacokinetics, limited efficacy, and high toxicity (Chang et al., 2023). The field of drug design has experienced a significant transformation with the introduction of in silico analysis, which has led to improved efficiency and cost reduction compared to traditional drug design methods. The integration of advanced databases, software, and tools in bioinformatics has played a crucial role in the exploration and dissemination of numerous novel therapies and applications (Musuamba et al., 2021). In this study, a collection of phytocompounds obtained from PubChem IDs was subjected to docking simulations with α-glucosidase to assess their potential as α-glucosidase inhibitors. Out of these compounds nine compounds were selected as α-glucosidase inhibitors by their minimum energy and top MolDock scores. Recent investigations have highlighted the potential interactions of these bioactive phytochemicals and their significant hydrophobic contact with α-glucosidase. The docking analysis revealed binding energies of Pelargonin, Simalin B, Linarin, Rutin, Nicotiflorin, Simalin A, Mangiferin, Quercetin, Apigenin at the α-glucosidase cavity scored were found to be −174.28 Å, −161.08 Å, −146.68 Å, −142.24 Å, −134.14 Å, 125.94 Å, 110.57 Å, −102.5 Å, and −102.45 Å respectively, along with the formation of several hydrogen bonds. These compounds exhibited binding interactions with residues such as HIS112, ASP69, ARG442, GLU277, and ARG213 of α-glucosidase, consistent with previous studies highlighting their strong inhibitory activity and binding capabilities of with α-glucosidase (Yan et al., 2014). Additionally, a comprehensive evaluation of these compounds based on the “Rule of Five” (Ro5) was conducted to check their drug-likeness and molecular properties (Chen et al., 2020). Advanced high-performance ADMET profiling analyses have emerged as valuable tools in early-stage drug discovery, facilitating the identification of active lead compounds (Ferreira and Andricopulo, 2019). The ADMET compound profiling conducted in this study confirmed the favorable absorption properties of all the compounds, without producing any adverse effects. Various models assessing P-glycoprotein substrates, blood–brain barrier (BBB) penetration, and gastrointestinal uptake were employed to evaluate the ADMET-related characteristics of these potential compounds. Notably, all these phytochemicals showed significant gastrointestinal absorption while showing limited BBB penetration except Simalin A, suggesting a reduced risk of harmful or adverse side effects compared to acarbose. It was observed that all these phytochemicals exhibited susceptibility with P-gp substrate except Quercetin. P-glycoproteins play a crucial role in transporting drugs to targeted organs (Elmeliegy et al., 2020). Furthermore, Apigenin and Quercetin exhibited positive inhibition against CYP1A2 and CYP2C9, indicating the potential for drug-drug interactions with these enzymes. Importantly, these phytochemicals didn’t exhibit toxicity, such as skin sensitization, mutagenesis and cardiotoxicity as non-inhibitors of hERG (Priest et al., 2008). Among potent compounds, commercially available phytochemicals, Apigenin, Quercetin, and Mangiferin, also accessed by in vitro enzyme inhibitory assay to validate in silico results. these compounds exhibited significant inhibitory activity with the IC₅₀ values 0.83 ± 0.07 µg/mL, 0.96 ± 0.01 µg/mL, and 1.47 ± 0.16 µg/mL respectively, which were notably less than acarbose. Li et al., (2009) also reported Quercetin and Rutin, that these compounds showed higher anti-diabetic results than acarbose (Li et al., 2009). There are chemically prepared inhibitors already reported with strong α-glucosidase inhibitory activity than standard drug (Rashid et al., 2022). Many α-glucosidase inhibitors have shown efficacy at lower concentrations (IC₅₀) compared to the positive control, indicating their potential therapeutic value (Yin et al., 2014). Previous studies have reported similar findings in Aegles marmelos and Syzygium cumini, where they demonstrated the ability to inhibit α-glucosidase and GLUT4 expression in adipocytes and contribute significantly to regulating blood glucose levels in individuals with diabetes (Anandharajan et al., 2006). In light of potential side effects and the higher costs associated with synthetic compounds, there is a preference for natural bioactive substances as potential candidates for drug development (Nisbet and Moore, 1997, Nisar et al., 2018). These findings could be useful for the development of novel therapeutic approaches by B. ceiba and its active metabolites for managing diabetic hyperglycemia via targeting α-glucosidase. Although two compounds Simalin A and B reported very first time in this study as α-glucosidase modulators yet their biochemical and in vitro evaluation is strongly recommended for their validation as α-glucosidase inhibitors.

5 Conclusion

In this study, in vitro enzymatic assay screening of 51 plant extracts was performed. The screening results showed that B. ceiba bark extract exhibited strong α-glucosidase inhibition with IC₅₀ value 1.95 ± 0.29 µg/mL. To the best of our knowledge, this is first report discloses Bombax ceiba as potent α-glucosidase inhibitor. Literature based library of 78 phytochemicals of B. ceiba was prepared and these compounds were docked with α-glucosidase binding site. Based on the in silico data, nine potent hits were identified with best binding affinities and showed favorable ADMET properties. Among these, Simalin A and B were identified as α-glucosidase modulators through virtual screening for the first time. Although, their in-vitro and biochemicals studies are strongly recommended to ensure α-glucosidase as the prime molecular target of these compounds. Furthermore, commercially available three phytochemicals, Apigenin, Quercetin and Mangiferin, were validated as α-glucosidase inhibitors using in vitro enzymatic assay with IC50 value 0.83 ± 0.07 µg/mL, 0.96 ± 0.01 µg/mL, 1.47 ± 0.16 µg/mL respectively. On the base of these findings, it is suggested that B. ceiba bark extract and its metabolites may holds the potential as a natural resource for managing hyperglycemic conditions in diabetic patients via targeting α-glucosidase. As α-glucosidase is a rate-limiting enzyme of intestinal carbohydrate digestion; therefore, it is recommended to evaluate the inhibitory efficacy of these compounds on the other key proteins involved in intestinal carbohydrate digestion. Additionally in vivo studies are recommended to validate their effectiveness and safety. Subsequently, clinical trials should be conducted to evaluate their potential as antidiabetic agents in diabetic patients.

Funding

This study was supported by a grant from Punjab Higher Education Commission (PHEC) under the project No. PHEC/ARA/PIRCA/20316/13.

CRediT authorship contribution statement

Mudassir Hassan: Conceptualization, Software, Validation, Writing – original draft, Writing – review & editing. Azhar Rasul: Conceptualization, Supervision, Writing – review & editing. Farhat Jabeen: Investigation, Writing – review & editing. Salma Sultana: Formal analysis, Writing – review & editing. Maria Manan: Methodology, Writing – review & editing.