RESEARCH ARTICLE

In vitro screening of α-glucosidase, DPP-IV, and pancreatic lipase inhibitory activity of extracts from 181 coastal island plants of Korea

Yun-Su Lee1https://orcid.org/0009-0009-9743-0237, Wook-Chul Kim1https://orcid.org/0009-0002-5296-0620, Seung-Hong Lee1,2,*https://orcid.org/0000-0003-2823-8718, Ji-Won Park3,4https://orcid.org/0000-0003-2899-1937, Bohyun Yun3,4https://orcid.org/0000-0001-6723-5849, WonWoo Lee3,4https://orcid.org/0009-0000-0756-2178, Kyung-Min Choi3,4https://orcid.org/0009-0000-2565-2468
Author Information & Copyright
1Department of Medical Science, Soonchunhyang University, Asan 31538, Korea
2Department of Pharmaceutical Engineering, Soonchunhyang University, Asan 31538, Korea
3Practical Research Division, Honam National Institute of Biological Resources (HNIBR), Mokpo 58762, Korea
4Advanced Research Center for Island Wildlife Biomaterials, Honam National Institute of Biological Resources (HNIBR), Mokpo 58762, Korea
*Corresponding author: Seung-Hong Lee, Department of Medical Science, Soonchunhyang University, Asan 31538, Korea, Tel: +82-41-530-4980, Fax: +82-41-530-3085, E-mail:shlee80@sch.ac.kr

Copyright © 2026 The Korean Society of Fisheries and Aquatic Science. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Received: Jul 16, 2025; Revised: Aug 20, 2025; Accepted: Sep 12, 2025

Published Online: Mar 31, 2026

Abstract

Obesity, hyperglycemia, and dyslipidemia are key components of metabolic syndrome (MetS), which increases the risk of cardiovascular disease and type 2 diabetes. Although lifestyle changes are essential, they are often insufficient, leading to increased use of drug therapies. However, concerns over side effects and poor compliance have driven interest in natural products with high biocompatibility and low toxicity. Coastal plants, especially those from island environments, are promising sources of bioactive compounds due to their adaptation to environmental stresses such as salinity, UV exposure, and nutrient scarcity. Among the key enzymatic targets for managing MetS, α-glucosidase is involved in carbohydrate digestion and glucose absorption, dipeptidyl peptidase-4 (DPP-IV) degrades the incretin hormones glucagon-like peptide-1 (GLP-1) and glucose-dependent insulinotropic polypeptide (GIP), which stimulate insulin secretion, and pancreatic lipase facilitates lipid digestion and absorption. Inhibition of these enzymes is considered an effective strategy for controlling blood glucose and body fat accumulation. This study evaluated the in vitro inhibitory activities of 181 plant extracts collected from coastal islands in Korea against α-glucosidase, DPP-IV, and pancreatic lipase. Several extracts demonstrated strong inhibitory effects, with some showing activity levels comparable to or higher than those of existing therapeutic agents. These findings may suggest that plant extracts collected from coastal island, which exhibited biological activities, may be strong inhibitors of α-glucosidase, DPP-IV, and pancreatic lipase and could be valuable for application in replacing synthetic drug.

Keywords: α-Glucosidase; Dipeptidyl peptidase-IV; Metabolic syndrome; Pancreatic lipase; Coastal plant

Introduction

Metabolic syndrome (MetS) is a complex health condition characterized by the simultaneous occurrence of multiple metabolic disorders, including obesity, hypertension, hyperglycemia, and dyslipidemia, which are known as major causes of cardiovascular disease and type 2 diabetes (Heindel et al., 2017). The prevalence of MetS has been steadily increasing in recent years due to rapid industrialization and urbanization, which have led to reduced physical activity and the widespread adoption of high-calorie diets and Westernized eating habits (Asghari et al., 2015; Dziegielewska-Gesiak, 2021).

According to the 2021 Metabolic Syndrome Fact Sheet from the Korean Society of Cardiometabolic Syndrome (KSCMS), the prevalence of MetS among Korean adults increased from 22.2% in 2007 to 29.7% in 2018, reflecting a continuous upward trend since 2015, which has become a significant economic and social concern (Kim et al., 2022).

Although lifestyle modifications, such as increased physical activity, dietary adjustments, and weight loss, are essential for preventing and managing MetS, these approaches alone are often insufficient (Nam et al., 1999; Oh, 2015). Moreover, conventional pharmacological treatments for MetS are associated with high costs, side effects, and the potential for drug resistance (Casacchia et al., 2019).

As a result, there has been increasing interest in naturally derived substances as promising alternatives to conventional drugs, particularly in terms of efficacy and long-term sustainability (Graf et al., 2010). These substances are considered advantageous for therapeutic applications due to their high biocompatibility, reduced likelihood of adverse effects, and compatibility with prolonged use, which makes them appealing candidates for MetS treatment (Waltenberger et al., 2016).

Among these, coastal plants have drawn particular attention as valuable sources of such substances, owing to their adaptation to extreme environments with high salinity, ultraviolet radiation, and nutrient-poor conditions, as these stress factors are known to enhance the biosynthesis of diverse secondary metabolites with potent bioactivities (Saba Nazir et al., 2018; Sadeghi et al., 2024). These environmental stresses promote the production of diverse secondary metabolites with potent biological activities (Saba Nazir et al., 2018; Sadeghi et al., 2024). Therefore, coastal plants have significant potential as sources of natural therapeutics for the prevention and treatment of MetS (Pungin et al., 2023).

Among the various therapeutic targets for managing MetS, α-glucosidase inhibition, dipeptidyl peptidase-IV (DPP-IV) inhibition, and pancreatic lipase inhibition have received particular attention due to their roles in type 2 diabetes and obesity management (Hossain et al., 2020; Kumar & Chauhan, 2021; Lunagariya et al., 2014). α-Glucosidase, an enzyme present in the small intestine, facilitates carbohydrate digestion by breaking down disaccharides into monosaccharides, and its inhibition can slow carbohydrate digestion and reduce postprandial glucose spikes (Kumar et al., 2011). DPP-IV is an enzyme that degrades incretin hormones glucagon-like peptide-1 (GLP-1) and glucose-dependent insulinotropic polypeptide (GIP), which stimulate insulin secretion, and its inhibition can enhance insulin secretion and improve glycemic control (Barnett, 2006). Pancreatic lipase, a key enzyme in fat digestion, can be inhibited to reduce fat absorption, thereby preventing fat accumulation and promoting weight loss (Lunagariya et al., 2014).

Therefore, this study aimed to evaluate the in vitro inhibitory activities of 181 plant extracts collected from coastal islands in the Republic of Korea on α-glucosidase, DPP-IV, and pancreatic lipase. Through this approach, the study seeks to explore the potential of coastal plants as natural therapeutics for the prevention and treatment of MetS, providing a foundation for the development of high-efficacy, low-toxicity natural compounds that could overcome the limitations of conventional synthetic drugs (Table 1).

Table 1. The scientific names, plant parts used, and collection sites to conduct this study
Sample no. Scientific name Part Collection sites Latitude Longitude
1. Euscaphis japonica (Thunb.) Kanitz Stem Geogeumdo 34.46664 127.10417
2. Solidago altissima L. Flower Gohado 34.77303 126.36878
3. Solidago altissima L. Root Gohado 34.77303 126.36878
4. Camellia japonica L. Leaf Jindo 34.38439 126.21278
5. Sorbus alnifolia (Siebold & Zucc.) K. Koch Stem Gohado 34.76917 126.36056
6. Pourthiaea villosa (Thunb.) Decne. Leaf Jindo 34.39512 126.23931
7. Carpinus turczaninowii Hance Stem Jindo 34.39549 126.23506
8. Amorpha fruticosa L. Leaf Jindo 34.53465 126.32204
9. Pteridium aquilinum var. latiusculum Plant Jindo 34.39489 126.23408
10. Equisetum arvense L. Plant Jindo 34.53465 126.32204
11. Cornus macrophylla Wall. Leaf Ulleungdo 37.46842 130.84261
12. Maianthemum dilatatum (A. W. Wood). Plant Ulleungdo 37.48997 130.82846
13. Artemisia montana (Nakai) Pamp. Plant Ulleungdo 37.46268 130.87579
14. Fallopia sachalinensis (F. Schmidt) Ronse Plant Ulleungdo 37.46268 130.87579
15. Torilis japonica (Houtt.) DC. Plant Suncheon 34.84712 127.47195
16. Litsea japonica (Thunb.) Juss. Leaf Chujado 33.96584 126.28859
17. Litsea japonica (Thunb.) Juss. Stem Chujado 36.8309 126.70734
18. Sageretia theezans (Osbeck) M. C. Johnst. Leaf Chujado 33.95678 126.29338
19. Sageretia theezans (Osbeck) M. C. Johnst. Stem Chujado 33.95678 126.29338
20. Hypochaeris radicata Plant Chujado 33.93921 126.32391
21. Suaeda japonica Makino Plant Ganghwado 36.8313 126.36477
22. Farfugium japonicum (L.) Kitam. Plant Ulleungdo 37.47694 130.87639
23. Hydrangea petiolaris Siebold & Zucc. Leaf Ulleungdo 37.46833 130.84306
24. Peucedanum japonicum Thunb. Plant Ulleungdo 37.48412 130.91713
25. Aster spathulifolius Maxim. Plant Ulleungdo 37.54294 130.90907
26. Sorbus ulleungensis Chin. S. Chang Fruit Ulleungdo 37.47694 130.87639
27. Sedum takesimense Nakai Plant Ulleungdo 37.51235 130.80718
28. Allium ochotense Prokh. Plant Ulleungdo 37.48426 130.87954
29. Impatiens nolitangere L. Plant Ulleungdo 37.5032 130.81944
30. Lilium lancifolium Thunb. Plant Ulleungdo 37.54313 130.90877
31. Dystaenia takesimana (Nakai) Kitag. Plant Ulleungdo 37.47694 130.87639
32. Artemisia littoricola Kitam. Plant Ulleungdo 37.54427 130.9082
33. Zingiber mioga (Thunb.) Roscoe Plant Haenam 34.43551 126.61835
34. Viburnum japonicum (Thunb.) C. K. Spreng. Leaf Gageodo 34.06302 125.12193
35. Amaranthus powellii S. Watson Plant Pyeongchang 37.71376 128.57453
36. Eragrostis ferruginea (Thunb.) Plant Geojedo 34.79595 128.73152
37. Barnardia japonica (Thunb.) Plant Jeju 33.21111 126.26194
38. Sageretia theezans (Osbeck) M. C. Johnst. Leaf Damyang 35.28611 127.00083
39. Quercus acuta Thunb. Leaf Jindo 34.46944 126.32444
40. Elaeagnus macrophylla Thunb. Leaf Goha 34.77852 126.3557
41. Farfugium japonicum (L.) Kitam. Plant Jindo 34.47028 126.30778
42. Bidens pilosa L. Plant Goha 34.76667 126.36839
43. Hedera rhombea (Miq.) Bean Leaf Jeopdo 34.37639 126.28972
44. Elaeagnus glabra Thunb. Leaf Jindo 34.39111 126.23639
45. Vaccinium bracteatum Thunb. Leaf Jeopdo 34.36997 126.2827
46. Vaccinium bracteatum Thunb. Stem Jeopdo 34.36997 126.2827
47. Dystaenia takesimana (Nakai) Kitag. Stem Ulleungdo 37.49452 130.82752
48. Acer okamotoanum Nakai Leaf Ulleungdo 37.5155 130.86932
49. Sorbus ulleungensis Chin. S. Chang Leaf Ulleungdo 37.51064 130.86272
50. Tsuga sieblodii Carriere Leaf (Stem) Ulleungdo 37.5032 130.81943
51. Hepatica maxima NAKAI Leaf Ulleungdo 37.5155 130.86932
52. Lonicera insularis Nakai Leaf (Branch) Ulleungdo 37.48458 130.91314
53. Illicium anisatum L. Leaf Jindo 34.55671 126.29863
54. Illicium anisatum L. Stem Jindo 34.55671 126.29863
55. Trachelospermum asiaticum (Siebold & Zucc.) Nakai Leaf Bigeumdo 34.75437 125.90396
56. Trachelospermum asiaticum (Siebold & Zucc.) Nakai Stem Bigeumdo 34.75437 125.90396
57. Fatsia japonica (Thunb.) Decne. & Planch. Leaf Bigeumdo 34.75427 125.9211
58. Erythronium japonicum Decne. Plant Changwon 35.17487 128.37999
59. Stauntonia hexaphylla Decne. Stem Joyakdo 34.37465 126.94347
60. Staphylea bumalda DC. Leaf Haman 35.22789 128.4551
61. Acer tataricum subsp. ginnala (Maxim.) Wesm. Stem Haman 35.22613 128.45341
62. Neolitsea sericea (Blume) Koidz. Leaf Dangmyosan 34.47219 127.46478
63. Machilus thunbergii Siebold & Zucc. ex Meisn. Leaf Dangmyosan 34.4723 127.46455
64. Zanthoxylum piperitum DC. Leaf Geoje 34.78814 128.73779
65. Sedum kamtschaticum Fisch. & C. A. Mey. Plant Geoje 34.78814 128.73779
66. Ligularia taquetii (H. Lév. & Vaniot) Nakai Plant Geoje 34.78794 128.73796
67. Cirsium japonicum var. maackii (Regel) Kitam. Plant Geoje 34.78793 128.738
68. Machilus thunbergii Siebold & Zucc. Leaf Jindo 34.40152 126.22537
69. Neolitsea sericea (Blume) Koidz. Leaf Jindo 34.40152 126.22537
70. Lindera erythrocarpa Makino Leaf Jindo 34.40152 126.22537
71. Mallotus japonicus (L. f.) Müll. Leaf Jindo 34.40152 126.22537
72. Euscaphis japonica (Thunb.) Kanitz Leaf Jindo 34.40152 126.22537
73. Ligustrum obtusifolium Siebold & Zucc. Leaf Jindo 34.40035 126.22111
74. Boehmeria tricuspis (Hance) Makino Plant Jindo 34.40035 126.22111
75. Platycarya strobilacea Siebold & Zucc. Leaf Jindo 34.40035 126.22111
76. Rubus corchorifolius L. f. Leaf Jindo 34.40007 126.22129
77. Toxicodendron sylvestre (Siebold & Zucc.) Kuntze Leaf Jindo 34.40035 126.22111
78. Neolitsea sericea (Blume) Koidz. Leaf Geoje 34.78816 128.73783
79. Litsea japonica (Thunb.) Juss. Leaf Geoje 34.78823 128.73781
80. Ficus erecta Thunb. Leaf Geoje 34.78823 128.73781
81. Eurya japonica Thunb. Leaf Wando 34.36263 126.70973
82. Euscaphis japonica (Thunb.) Kanitz Leaf Wando 34.36258 126.7096
83. Zanthoxylum piperitum DC. Leaf Wando 34.36248 126.70955
84. Zanthoxylum ailanthoides Siebold & Zucc. Leaf Wando 34.3625 126.70952
85. Lindera erythrocarpa Makino Leaf Wando 34.36181 126.7067
86. Mallotus japonicus (L. f.) Müll. Leaf Wando 34.36179 126.70668
87. Daphniphyllum macropodum Miq. Leaf Wando 34.36183 126.70662
88. Styrax japonicus Siebold & Zucc. Leaf Wando 34.36199 126.70806
89. Celtis sinensis Pers. Leaf Wando 34.36417 126.71195
90. Cornus kousa F. Buerger ex Miq. Leaf Wando 34.36582 126.71452
91. Toxicodendron sylvestre (Siebold & Zucc.) Kuntze Leaf Wando 34.36601 126.71506
92. Cornus kousa F. Buerger ex Miq. Leaf Wando 35.82067 126.45847
93. Mallotus japonicus (L. f.) Müll. Leaf Wando 35.82069 126.45843
94. Toxicodendron sylvestre (Siebold & Zucc.) Kuntze Leaf Sinshido 35.82062 126.45834
95. Eurya japonica Thunb. Leaf Sinshido 35.82058 126.4583
96. Styrax japonicus Siebold & Zucc. Leaf Sinshido 35.82064 126.45848
97. Euscaphis japonica (Thunb.) Kanitz Leaf Sinshido 35.82069 126.45862
98. Platycarya strobilacea Siebold & Zucc. Leaf Sinshido 35.82056 126.46062
99. Celtis biondii var. heterophylla (H. Lév.) C. K. Schneid. Leaf Sinshido 35.81894 126.45331
100. Rubus takesimensis Nakai Leaf Ulleungdo 37.52433 130.87146
101. Hovenia dulcis Thunb. Leaf Ulleungdo 37.52433 130.87146
102. Maianthemum dilatatum (A. W. Wood) Plant Ulleungdo 37.5241 130.86518
103. Prunus takesimensis Nakai Leaf Ulleungdo 37.52356 130.86425
104. Sorbus ulleungensis Chin. S. Chang Leaf Ulleungdo 37.52279 130.86356
105. Ulmus laciniata (Trautv.) Mayr Leaf Ulleungdo 37.52279 130.86362
106. Kalopanax septemlobus (Thunb.) Koidz. Leaf Ulleungdo 37.524 130.86421
107. Neolitsea sericea (Blume) Koidz. Leaf Ulleungdo 37.48109 130.81373
108. Sambucus racemosa subsp. pendula (Nakai) Leaf Ulleungdo 37.48202 130.81428
109. Ligustrum foliosum Nakai Leaf Ulleungdo 37.48345 130.81937
110. Urtica laetevirens Maxim. Plant Ulleungdo 37.49034 130.82702
111. Tsuga sieboldii Carrière Leaf Ulleungdo 37.48994 130.82667
112. Alnus maximowiczii Callier ex C. K. Schneid. Leaf Ulleungdo 37.49672 130.8255
113. Glehnia littoralis F. Schmidt ex Miq. Plant Ulleungdo 37.48472 130.91792
114. Daphniphyllum macropodum Miq. Leaf Ulleungdo 37.47877 130.89355
115. Zanthoxylum simulans Hance Leaf Jeju 33.30121 126.25519
116. Cinnamomum japonicum Siebold Leaf Jeju 33.25765 126.3529
117. Actinodaphne lancifolia (Siebold & Zucc.) Meisn. Leaf Jeju 33.29577 126.26771
118. Sophora flavescens Aiton Plant Jeju 33.29456 126.26815
119. Ligustrum obtusifolium Siebold & Zucc. Leaf Geoje 34.81052 128.71651
120. Albizia julibrissin Durazz. Leaf Geoje 34.78826 128.7378
121. Rhus javanica L. Leaf Geoje 34.81047 128.71656
122. Osmanthus heterophyllus (G. Don) P. S. Green Leaf Tongyeong 34.79593 128.42831
123. Lindera erythrocarpa Makino Leaf Tongyeong 34.79589 128.42835
124. Aralia elata (Miq.) Seem. Plant Tongyeong 34.79617 128.42826
125. Viburnum odoratissimum var. awabuki Leaf Tongyeong 34.81075 128.43383
126. Albizia julibrissin Durazz. Leaf Jindo 34.40046 126.21431
127. Callicarpa mollis Siebold & Zucc. Leaf Jindo 34.40031 126.2147
128. Clerodendrum trichotomum Thunb. Leaf Jindo 34.39929 126.21827
129. Cinnamomum japonicum Siebold Leaf Jindo 34.39868 126.21812
130. Flueggea suffruticosa (Pall.) Baill. Leaf Jindo 34.39701 126.2197
131. Styrax japonicus Siebold & Zucc. Leaf Jindo 34.39627 126.22131
132. Zanthoxylum schinifolium Siebold & Zucc. Leaf Jindo 34.39718 126.22655
133. Lysimachia clethroides Duby Plant Jindo 34.39662 126.22628
134. Eupatorium lindleyanum DC. Plant Jindo 34.39591 126.22646
135. Eurya japonica Thunb. Leaf Nangdo 34.60939 127.54828
136. Toxicodendron sylvestre (Siebold & Zucc.) Kuntze Leaf Nangdo 34.60931 127.54833
137. Callicarpa japonica Thunb. Leaf Nangdo 34.60894 127.54867
138. Lespedeza maximowiczii C. K. Schneid. Leaf Nangdo 34.60877 127.54884
139. Weigela subsessilis (Nakai) L. H. Bailey Leaf Nangdo 34.60879 127.54889
140. Rhus javanica L. Leaf Nangdo 34.60983 127.5481
141. Sageretia theezans (Osbeck) M. C. Johnst. Leaf Nangdo 34.61081 127.5471
142. Pittosporum tobira (Thunb.) W. T. Aiton Leaf Nangdo 34.61536 127.5535
143. Ligustrum japonicum Thunb. Leaf Nangdo 34.61539 127.55378
144. Ficus erecta Thunb. Leaf Nangdo 34.61544 127.55379
145. Cornus macrophylla Wall. Leaf Nangdo 34.61323 127.54443
146. Glochidion chodoense J. S. Lee & H. T. Im Leaf Jodo 34.33597 126.02976
147. Smilax china L. Leaf Jodo 34.33621 126.02929
148. Toxicodendron sylvestre (Siebold & Zucc.) Kuntze Leaf Jodo 34.33618 126.02934
149. Euscaphis japonica (Thunb.) Kanitz Leaf Jodo 34.33604 126.02964
150. Rhaphiolepis indica var. umbellata (Thunb.) Ohashi Leaf Jodo 34.33604 126.02954
151. Eurya japonica Thunb. Leaf Jodo 34.33599 126.0296
152. Mallotus japonicus (L. f.) Müll. Leaf Jodo 34.3355 126.03136
153. Albizia julibrissin Durazz. Leaf Jodo 34.33576 126.03134
154. Hedera rhombea (Miq.) Bean Leaf Jodo 34.33565 126.03184
155. Elaeagnus macrophylla Thunb. Leaf Jodo 34.33583 126.03214
156. Albizia julibrissin Durazz. Leaf Imjado 35.07095 126.08951
157. Platycarya strobilacea Siebold & Zucc. Leaf Imjado 35.07096 126.0894
158. Chenopodium album L. Leaf Imjado 35.07176 126.08852
159. Smilax china L. Leaf Imjado 35.08762 126.04817
160. Clerodendrum trichotomum Thunb. Leaf Imjado 35.08763 126.04815
161. Lespedeza maximowiczii var. tricolor (Nakai) Nakai Leaf Imjado 35.0877 126.04822
162. Rhus javanica L. Leaf Imjado 35.08837 126.04828
163. Cudrania tricuspidata (Carrière) Bureau ex Lavallée Leaf Imjado 35.08948 126.04722
164. Eupatorium lindleyanum DC. Plant Imjado 35.09265 126.05316
165. Zanthoxylum schinifolium Siebold & Zucc. Leaf Paryeongsan 34.63625 127.32606
166. Angelica decursiva (Miq.) Franch. & Sav. Plant Paryeongsan 34.63666 127.32737
167. Cudrania tricuspidata (Carrière) Bureau ex Lavallée Leaf Paryeongsan 34.63656 127.32877
168. Clerodendrum trichotomum Thunb. Leaf Paryeongsan 34.63655 127.32876
169. Patrinia scabiosifolia Fisch. ex Trevir. Plant Paryeongsan 34.63245 127.32781
170. Flueggea suffruticosa (Pall.) Baill. Leaf Paryeongsan 34.65266 127.35388
171. Lespedeza maximowiczii var. tricolor (Nakai) Nakai Leaf Paryeongsan 34.65267 127.35386
172. Lespedeza bicolor Turcz. Leaf Paryeongsan 34.64938 127.3567
173. Rubus coreanus Miq. Leaf Paryeongsan 34.61854 127.46823
174. Ulmus davidiana var. japonica (Rehder) Nakai Leaf Paryeongsan 34.63205 127.4106
175. Aphananthe aspera (Thunb.) Planch. Leaf Paryeongsan 34.63213 127.41063
176. Zanthoxylum piperitum DC. Leaf Paryeongsan 34.63216 127.41057
177. Pueraria lobata (Willd.) Ohwi Plant Paryeongsan 34.63224 127.41048
178. Zanthoxylum ailanthoides Siebold & Zucc. Leaf Haenam 34.46696 126.62278
179. Lindera erythrocarpa Makino Leaf Haenam 34.46698 126.62275
180. Ilex macropoda Miq. Leaf Haenam 34.46698 126.62279
181. Cornus controversa Hemsl. Leaf Haenam 34.46274 126.6234
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Materials and Methods

Chemicals and reagents

All plant extracts derived from coastal island plants were obtained from the Honam National Institute of Biological Resources (Mokpo, Korea). The reagents used in this study included Bovine Serum Albumin (BSA), sodium azide (NaN₃), α-glucosidase (from Saccharomyces cerevisiae), p-nitrophenyl-α-D-glucopyranoside (pNPG), acarbose, dipeptidyl peptidase-IV (DPP-IV; human recombinant), Gly-Pro-p-nitroanilide hydrochloride (Gly-Pro-pNA), Ile-Pro-Ile (Diprotin A), sodium acetate, lipase (from porcine pancreas), and p-nitrophenyl butyrate, all of which were purchased from Sigma-Aldrich (St. Louis, MO, USA). 10X MOPS buffer was obtained from Bioneer (Daejeon, Korea).

α-Glucosidase inhibitory activity

The α-glucosidase inhibitory activity was determined using a modified method from (Indrianingsih et al., 2015). 10 μL of each plant extract or positive control Acarbose was added to a 96-well plate to reach a final concentration of 100 μg/mL. Then, 50 μL of 0.7 U/mL α-glucosidase solution in phosphate buffered saline (PBS) was added, and the initial absorbance at 405 nm was measured. The plate was incubated at room temperature for 5 minutes, followed by the addition of 50 μL of 5 mM pNPG in PBS. After an additional 5 minutes of incubation, the absorbance at 405 nm was measured to determine enzyme activity.

Dipeptidyl peptidase-IV inhibitory activity

The DPP-IV inhibitory activity was determined using a modified method from (Parmar et al., 2012). 25 μL of each plant extract or positive control Ile-Pro-Ile (Diprotin A) was added to a 96-well plate to reach a final concentration of 100 μg/mL. Then, 25 μL of 0.8 mM Gly-Pro-p-NA in 0.1 M Tris-HCl buffer (pH 8.0) was added, and the plate was incubated at 37°C for 10 minutes. After this, 50 μL of 5 mU/mL DPP-IV enzyme solution in the same tris(hydroxymethyl)aminomethane hydrochloride (Tris-HCl) buffer was added. The plate was incubated for 60 minutes at 37°C, and the reaction was stopped by adding 100 μL of 3% acetic acid. The absorbance at 405 nm was measured to determine enzyme activity.

Pancreatic lipase inhibitory activity

The pancreatic lipase inhibitory activity was determined using a modified method from (Wei et al., 2015). 20 μL of each plant extract or positive control (orlistat) was added to a 96-well plate to reach a final concentration of 100 μg/mL. Then, 169 μL of 0.1 M Tris-HCl buffer (pH 7.0) containing 5 mM CaCl2 was added, followed by 6 μL of 2.5 mg/mL lipase from porcine pancreas solution prepared in 1X MOPS buffer. The plate was incubated at 37°C for 15 minutes. After this, 5 μL of 10 mM p-nitrophenyl butyrate dissolved in dimethyl sulfoxide (DMSO) was added, and the plate was incubated for an additional 30 minutes at 37°C. The absorbance at 405 nm was then measured to determine enzyme activity.

Calculation of inhibition rate

To correct for potential color interference from plant extracts, a blank control was included for each assay. The blank was prepared under the same conditions as the test samples but without the enzyme. The inhibition rate was calculated using the following formula:

Inhibition  ( % ) = [ ( Absorbance of control Absorbance of sample ) / Absorbance of control ] × 100
Statistical analysis

All experiments were performed in triplicate and data are presented as mean ± SD. For each enzyme assay, differences between each extract (n = 181) and the control were assessed by one-way analysis of variance (ANOVA) followed by Dunnett’s multiple comparisons test in GraphPad Prism. Adjusted p-values are reported, statistical significance is denoted as *p < 0.05, **p < 0.01, ***p < 0.001, and ****p < 0.0001.

Results and Discussion

α-Glucosidase inhibitory activity

α-Glucosidase is an enzyme that breaks down disaccharides into monosaccharides in the small intestine, facilitating glucose absorption (Kumar et al., 2011). Inhibiting this enzyme can delay carbohydrate digestion and reduce postprandial blood glucose levels, making it a promising target for type 2 diabetes management (Hossain et al., 2020; Kumar et al., 2011). This inhibitory activity is known to be mediated by various bioactive compounds, including flavonoids (e.g., quercetin), polyphenols, tannins, and triterpenoids, which are commonly found in many medicinal and edible plants (Hossain et al., 2020; Martin & Montgomery, 1996).

Therefore, this study analyzed the α-glucosidase inhibitory activities of 181 extracts from coastal island plants in Korea. The 181 plant extracts were found to have different levels of α-glucosidase inhibitory activity, ranging from 0 ± 0.31% to 85 ± 0.56% (Table 2). Among the 181 plant extracts, Acer okamotoanum Nakai exhibited the highest α-glucosidase inhibitory activity (85 ± 0.56%). Furthermore, the next most potent α-glucosidase inhibitory capacities (> 75%) were found in the following extracts: Tsuga sieboldii Carriere (84 ± 1.31%), Elaeagnus glabra Thunb. (84 ± 0.48%), Acer tataricum subsp. ginnala (83 ± 0.41%), and Staphylea bumalda DC. (75 ± 0.35%). The inhibitory activity of the five extracts listed above was greater than that of the commercial α-glucosidase inhibitor acarbose (69%) (Martin & Montgomery, 1996).

Table 2. α-Glucosidase inhibitory activity of 181 plant extracts
Sample no. Inhibitory activity (%) Sample no. Inhibitory activity (%)
Acarbose 69 ± 1.63**** 44. 84 ± 0.481), ****
1. 18 ± 1.08**** 45. 62 ± 1.20****
2. 18 ± 3.24**** 46. 58 ± 0.90****
3. 9 ± 2.24* 47. 51 ± 0.69****
4. 3 ± 0.60 48. 85 ± 0.561), ****
5. 15 ± 1.10**** 49. 70 ± 1.26****
6. 23 ± 2.73**** 50. 84 ± 1.311), ****
7. 23 ± 1.38**** 51. 60 ± 0.83****
8. 22 ± 2.61**** 52. 49 ± 1.52****
9. 6 ± 0.68 53. 52 ± 2.48****
10. 6 ± 1.59 54. 69 ± 1.40****
11. 17 ± 1.55**** 55. 55 ± 2.34****
12. 7 ± 1.86 56. 51 ± 2.14****
13. 6 ± 1.49 57. 50 ± 1.70****
14. 9 ± 3.89* 58. 55 ± 1.76****
15. 8 ± 0.95 59. 51 ± 0.83****
16. 2 ± 5.50 60. 75 ± 0.351), ****
17. 7 ± 2.17 61. 83 ± 0.411), ****
18. 17 ± 5.51**** 62. 5 ± 2.38
19. 22 ± 0.34**** 63. 10 ± 2.87***
20. 57 ± 5.15**** 64. 8 ± 3.29*
21. 0 ± 6.20 65. 10 ± 1.22**
22. 7 ± 3.03 66. 5 ± 2.55
23. 19 ± 8.93**** 67. 12 ± 1.80****
24. 29 ± 3.86**** 68. 17 ± 1.85****
25. 12 ± 3.26** 69. 16 ± 0.52****
26. 6 ± 7.42 70. 19 ± 2.29****
27. 16 ± 1.57**** 71. 20 ± 0.70****
28. 7 ± 6.52 72. 21 ± 1.23****
29. 12 ± 5.16** 73. 5 ± 3.54
30. 8 ± 5.48 74. 6 ± 3.36
31. 11 ± 0.25** 75. 12 ± 2.23****
32. 6 ± 3.49 76. 11 ± 0.71***
33. 8 ± 1.82 77. 13 ± 1.91****
34. 22 ± 6.12**** 78. 11 ± 2.10***
35. 9 ± 1.07* 79. 16 ± 3.89****
36. 7 ± 2.50 80. 13 ± 2.19****
37. 23 ± 1.51**** 81. 15 ± 0.39****
38. 31 ± 1.37**** 82. 20 ± 2.42****
39. 18 ± 0.46**** 83. 19 ± 2.31****
40. 16 ± 2.59**** 84. 4 ± 0.96*
41. 43 ± 1.80**** 85. 3 ± 1.72
42. 48 ± 1.02**** 86. 5 ± 2.02**
43. 49 ± 1.53**** 87. 2 ± 1.49
88. 2 ± 1.27 132. 6 ± 1.43***
89. 7 ± 0.18**** 133. 13 ± 1.73****
90. 7 ± 1.81**** 134. 9 ± 0.97****
91. 10 ± 0.81**** 135. 11 ± 1.46****
92. 10 ± 0.66**** 136. 13 ± 2.30****
93. 5 ± 1.16** 137. 10 ± 0.42****
94. 10 ± 0.34**** 138. 13 ± 0.96****
95. 0 ± 0.64 139. 14 ± 1.25****
96. 2 ± 3.07 140. 21 ± 0.34****
97. 0 ± 2.04 141. 1 ± 2.86
98. 0 ± 0.31 142. 2 ± 0.93
99. 9 ± 2.42**** 143. 0 ± 1.81
100. 1 ± 1.53 144. 0 ± 1.60
101. 2 ± 1.02 145. 12 ± 1.67****
102. 2 ± 1.56 146. 11 ± 1.93****
103. 0 ± 1.05 147. 8 ± 1.53****
104. 2 ± 2.07 148. 13 ± .74****
105. 0 ± 1.86 149. 11 ± 2.21****
106. 1 ± 0.22 150. 9 ± 1.39****
107. 0 ± 1.36 151. 9 ± 1.73****
108. 0 ± 1.58 152. 12 ± 1.35****
109. 2 ± 1.26 153. 11 ± 0.20****
110. 0 ± 1.26 154. 0 ± 1.39
111. 3 ± 1.99 155. 5 ± 1.13**
112. 4 ± 0.50* 156. 21 ±1.98****
113. 1 ± 0.28 157. 5 ± 1.20**
114. 6 ± 1.37*** 158. 4 ± 0.30*
115. 8 ± 1.12**** 159. 10 ± 0.05****
116. 9 ± 1.27**** 160. 3 ± 0.73
117. 16 ± 1.12**** 161. 6 ± 0.77***
118. 0 ± 3.30 162. 15 ± 1.77****
119. 4 ± 1.64* 163. 4 ± 0.94**
120. 21 ± 0.49**** 164. 2 ± 2.68
121. 9 ± 1.54**** 165. 2 ± 0.64
122. 1 ± 1.21 166. 4 ± 2.46*
123. 2 ± 1.02 167. 3 ± 0.92
124. 3 ± 1.12 168. 3 ± 1.95
125. 4 ± 1.96** 169. 2 ± 1.72
126. 22 ± 0.85**** 170. 2 ± 0.72
127. 3 ± 0.44 171. 1 ± 1.99
128. 4 ± 1.15* 172. 3 ± 0.38
129. 4 ± 1.29* 173. 6 ± 0.58****
130. 6 ± 1.13**** 174. 3 ± 1.15
131. 5 ± 0.58** 175. 1 ± 1.65
176. 5 ± 1.06** 179. 5 ± 0.22***
177. 3 ± 0.91* 180. 3 ± 1.43*
178. 3 ± 1.41* 181. 4 ± 1.37**

Each extract was tested at a final concentration of 100 μg/mL, and results are presented as mean ± SD from triplicate experiments.

Differences between each extract (n = 181) and the control were assessed by one-way analysis of variance (ANOVA) followed by Dunnett’s multiple comparisons test.

1) Acarbose was used as the positive control, and the top five extracts with the highest activity.

Adjusted p-values are reported; statistical significance is denoted as

* p < 0.05,

** p < 0.01,

*** p < 0.001, and

**** p < 0.0001.

Download Excel Table

These findings suggest that the identified extracts could be promising candidates for controlling postprandial hyperglycemia, supporting the development of new α-glucosidase inhibitors for the treatment of type 2 diabetes (Kumar et al., 2011).

Dipeptidyl peptidase-IV inhibitory activity

DPP-IV is an enzyme that degrades GLP-1 and GIP, which are incretin hormones that stimulate insulin secretion and help regulate blood glucose levels (Barnett, 2006). Inhibiting DPP-IV prolongs GLP-1 activity, enhances insulin release and improves glycemic control, making DPP-IV a valuable target for type 2 diabetes therapy (Kumar & Chauhan, 2021). The inhibitory activity of DPP-IV is influenced by various bioactive compounds, including polyphenols (e.g., catechins), flavonoids and alkaloids, which are found in abundance in medicinal plants (Ansari et al., 2022; Singh et al., 2021).

This study evaluated the DPP-IV inhibitory activities of various plant extracts as illustrated in Table 3. The 181 plant extracts were found to have different levels of DPP-IV inhibitory activity, ranging from 0 ± 0.41% to 56 ± 2.76% (Table 3). Of the 181 extracts tested, Elaeagnus macrophylla Thunb. exhibited the highest DPP-IV inhibition (56 ± 2.76%). The next most potent DPP-IV inhibitory activities were observed in Camellia japonica L. (55 ± 5.97%), Farfugium japonicum (L.) Kitam. (55 ± 1.59%), Bidens pilosa L. (55 ± 1.20%), and Solidago altissima L. (54 ± 0.92%). Although these extracts demonstrated notable inhibitory activity, their inhibition rates did not exceed that of the positive control (Ile-Pro-Ile, 86%) (Singh et al., 2021).

Table 3. Dipeptidyl peptidase-IV (DPP-IV) inhibitory activity of 181 plant extracts
Sample no. Inhibitory activity (%) Sample no. Inhibitory activity (%)
Ile-Pro-Ile 86 ± 0.31**** 43. 51 ± 0.53****
1. 51 ± 2.55**** 44. 52 ± 0.61****
2. 54 ± 2.23**** 45. 50 ± 1.46****
3. 54 ± 0.921), **** 46. 51 ± 0.96****
4. 55 ± 5.971), **** 47. 49 ± 1.07****
5. 50 ± 2.40**** 48. 49 ± 1.07****
6. 48 ± 0.80**** 49. 52 ± 1.86****
7. 51 ± 0.41**** 50. 52 ± 1.00****
8. 52 ± 0.85**** 51. 50 ± 1.61****
9. 52 ± 2.11**** 52. 53 ± 1.84****
10. 49 ± 1.16**** 53. 47 ± 1.96****
11. 53 ± 4.39**** 54. 16 ± 1.86****
12. 53 ± 3.08**** 55. 51 ± 0.46****
13. 50 ± 0.81**** 56. 53 ± 1.51****
14. 50 ± 0.70**** 57. 53 ± 1.92****
15. 52 ± 2.00**** 58. 50 ± 0.70****
16. 50 ± 1.01**** 59. 53 ± 1.33****
17. 47 ± 0.55**** 60. 51 ± 0.96****
18. 49 ± 0.85**** 61. 51 ± 1.61****
19. 52 ± 5.48**** 62. 12 ± 1.08**
20. 52 ± 2.65**** 63. 12 ± 1.08**
21. 48 ± 0.85**** 64. 16 ± 1.42****
22. 55 ± 1.591), **** 65. 13 ± 1.42***
23. 49 ± 0.55**** 66. 7 ± 0.82
24. 52 ± 2.39**** 67. 8 ± 1.42
25. 48 ± 0.55**** 68. 13 ± 1.48***
26. 50 ± 0.81**** 69. 11 ± 2.49**
27. 53 ± 3.99**** 70. 11 ± 2.69**
28. 52 ± 0.93**** 71. 10 ± 2.56**
29. 50 ± 3.57**** 72. 10 ± 4.16**
30. 50 ± 1.07**** 73. 16 ± 2.13****
31. 49 ± 0.61**** 74. 10 ± 2.05*
32. 51 ± 1.07**** 75. 6 ± 1.23
33. 49 ± 2.13**** 76. 7 ± 1.78
34. 52 ± 0.85**** 77. 9 ± 1.42*
35. 52 ± 0.41**** 78. 9 ± 1.48*
36. 52 ± 1.60**** 79. 5 ± 3.64
37. 49 ± 0.41**** 80. 6 ± 3.35
38. 47 ± 2.92**** 81. 2 ± 2.28
39. 49 ± 3.57**** 82. 11 ± 2.58*
40. 56 ± 2.761), **** 83. 12 ± 3.10*
41. 50 ± 0.93**** 84. 18 ± 1.87****
42. 55 ± 1.201), **** 85. 15 ± 2.68***
86. 18 ± 1.14**** 130. 3 ± 2.08
87. 16 ± 1.55*** 131. 6 ± 1.91
88. 18 ± 0.74**** 132. 9 ± 2.53
89. 3 ± 3.72 133. 12 ± 1.10**
90. 18 ± 2.39**** 134. 5 ± 2.16
91. 12 ± 4.65** 135. 0 ± 2.53
92. 18 ± 4.49**** 136. 0 ± 3.63
93. 11 ± 6.36* 137. 5 ± 3.70
94. 13 ± 5.21** 138. 0 ± 5.51
95. 11 ± 5.28* 139. 0 ± 5.41
96. 10 ± 6.70 140. 2 ± 5.07
97. 5 ± 3.72 141. 0 ± 5.51
98. 8 ± 4.23 142. 1 ± 4.73
99. 9 ± 4.23 143. 7 ± 2.73
100. 12 ± 4.49** 144. 5 ± 4.50
101. 13 ± 3.36** 145. 19 ± 4.02****
102. 8 ± 3.72 146. 4 ± 5.12
103. 4 ± 4.88 147. 1 ± 2.20
104. 3 ± 4.79 148. 0 ± 3.70
105. 2 ± 3.24 149. 0 ± 2.91
106. 12 ± 2.39* 150. 0 ± 4.41
107. 12 ± 2.39* 151. 4 ± 2.51
108. 17 ± 2.23*** 152. 0 ± 1.24
109. 20 ± 1.97**** 153. 0 ± 0.41
110. 21 ± 4.53**** 154. 0 ± 2.30
111. 16 ± 2.23*** 155. 0 ± 2.89
112. 1 ± 1.55 156. 0 ± 1.09
113. 7 ± 3.75 157. 0 ± 0.71
114. 6 ± 3.01 158. 0 ± 2.30
115. 4 ± 5.07 159. 5 ± 2.30
116. 6 ± 5.69 160. 0 ± 2.58
117. 14 ± 6.71** 161. 0 ± 4.59
118. 5 ± 6.09 162. 0 ± 3.11
119. 10 ± 5.37 163. 1 ± 3.27
120. 10 ± 6.70 164. 2 ± 3.30
121. 19 ± 6.02**** 165. 1 ± 1.49
122. 19 ± 4.55**** 166. 0 ± 5.71
123. 12 ± 4.10* 167. 0 ± 4.12
124. 13 ± 3.94* 168. 0 ± 3.52
125. 6 ± 5.28 169. 0 ± 2.18
126. 6 ± 3.82 170. 0 ± 4.59
127. 5 ± 4.10 171. 7 ± 9.72
128. 0 ± 2.08 172. 0 ± 0.82
129. 5 ± 2.50 173. 0 ± 3.67
174. 5 ± 5.67 178. 7 ± 3.17
175. 7 ± 1.06 179. 10 ± 2.80
176. 12 ± 5.25* 180. 8 ± 4.33
177. 12 ± 10.74* 181. 12 ± 3.67

Each extract was tested at a final concentration of 100 μg/mL, and results are presented as mean ± SD from triplicate experiments.

Differences between each extract (n = 181) and the control were assessed by one-way analysis of variance (ANOVA) followed by Dunnett’s multiple comparisons test.

1) Ile-Pro-Ile was used as the positive control, and the top five extracts with the highest activity.

Adjusted p-values are reported; statistical significance is denoted as

* p < 0.05,

** p < 0.01,

*** p < 0.001, and

**** p < 0.0001.

Download Excel Table

These findings suggest that the identified extracts could be used to modulate incretin activity, supporting the development of new DPP-IV inhibitors for treating type 2 diabetes (Lin et al., 2019).

Pancreatic lipase inhibitory activity

Pancreatic lipase is an enzyme that plays a crucial part in digesting and absorbing dietary fats (Subramaniyan & Hanim, 2025). Inhibiting this enzyme reduces fat absorption and promotes weight loss, making it a promising target for obesity management (Lunagariya et al., 2014). Various natural compounds have been found to exhibit this inhibitory activity, including catechins, polyphenols, saponins and triterpenoids, which are commonly found in numerous edible and medicinal plants (de La Garza et al., 2011).

Therefore, this study analyzed the pancreatic lipase inhibitory activities of 181 extracts from coastal island plants in Korea. The 181 plant extracts were found to have different levels of pancreatic lipase inhibitory activity, ranging from 12 ± 6.84% to 105 ± 1.63% (Table 4). Among the 181 plant extracts, Ilex macropoda Miq. exhibited the highest pancreatic lipase inhibitory activity (105 ± 1.63%). Furthermore, the next most potent pancreatic lipase inhibitory capacities (> 90%) were found in the following extracts: Lilium lancifolium Thunb. (93 ± 5.02%), Mallotus japonicus (L. f.) Müll. (93 ± 2.50%), Viburnum japonicum (Thunb.) C. K. Spreng. (91 ± 2.35%), and Suaeda japonica Makino (90 ± 1.93%). The inhibitory activity of the five extracts listed above was greater than that of the commercial pancreatic lipase inhibitor orlistat (87%) (Rajan et al., 2020).

Table 4. Pancreatic lipase inhibitory activity of 181 plant extracts
Sample no. Inhibitory activity (%) Sample no. Inhibitory activity (%)
Orlistat 87 ± 0.58**** 44. 72 ± 6.37****
1. 61 ± 8.19**** 45. 66 ± 10.17****
2. 54 ± 0.60**** 46. 81 ± 0.60****
3. 65 ± 8.51**** 47. 76 ± 3.78****
4. 49 ± 4.26**** 48. 68 ± 3.14****
5. 60 ± 10.77**** 49. 85 ± 8.12****
6. 65 ± 12.14**** 50. 76 ± 5.83****
7. 72 ± 4.66**** 51. 75 ± 1.60****
8. 81 ± 5.40**** 52. 78 ± 12.78****
9. 38 ± 7.55**** 53. 46 ± 13.38****
10. 76 ± 5.89**** 54. 85 ± 13.08****
11. 55 ± 14.40**** 55. 69 ± 10.83****
12. 72 ± 6.68**** 56. 77 ± 2.64****
13. 60 ± 5.57**** 57. 76± 8.85****
14. 77 ± 9.87**** 58. 78 ± 7.36****
15. 88 ± 2.50**** 59. 42 ± 6.87****
16. 63 ± 12.99**** 60. 76 ± 10.57****
17. 80 ± 11.17**** 61. 65 ± 18.79****
18. 73 ± 5.54**** 62. 86 ± 11.76****
19. 72 ± 4.16**** 63. 53 ± 0.58****
20. 89 ± 12.65**** 64. 57 ± 3.80****
21. 90 ± 1.931), **** 65. 50 ± 6.45****
22. 87 ± 2.51**** 66. 61 ± 4.18****
23. 38 ± 3.74** 67. 63 ± 2.03****
24. 83 ± 10.58**** 68. 56 ± 4.19****
25. 43 ± 11.40*** 69. 65 ± 1.46****
26. 59 ± 14.13**** 70. 71 ± 0.33****
27. 81 ± 12.19**** 71. 41 ± 3.54****
28. 68 ± 7.56**** 72. 40 ± 6.46****
29. 66 ± 11.12**** 73. 47 ± 1.46****
30. 93 ± 5.021), **** 74. 57 ± 4.07****
31. 76 ± 7.00**** 75. 52 ± 4.11****
32. 83 ± 7.53**** 76. 56 ± 2.61****
33. 59 ± 18.60**** 77. 67 ± 4.93****
34. 91 ± 2.351), **** 78. 61 ± 3.49****
35. 81 ± 4.14**** 79. 59 ± 2.09****
36. 78 ± 12.09**** 80. 65 ± 3.22****
37. 15 ± 5.93 81. 57 ± 3.34****
38. 12 ± 6.84 82. 69 ± 2.01****
39. 39 ± 13.83** 83. 62 ± 6.14****
40. 68 ± 9.32**** 84. 63 ± 1.52****
41. 78 ± 11.39**** 85. 46 ± 5.17****
42. 89 ± 4.25**** 86. 50 ± 2.94****
43. 69 ± 13.91**** 87. 45 ± 1.52****
88. 44 ± 5.11**** 132. 62 ± 1.51****
89. 45 ± 3.44**** 133. 40 ± 10.63****
90. 36 ± 3.74**** 134. 59 ± 2.72****
91. 64 ± 1.46**** 135. 29 ± 7.89****
92. 37 ± 3.03**** 136. 49 ± 2.85****
93. 37 ± 1.46**** 137. 48 ± 3.29****
94. 54 ± 8.38**** 138. 56 ± 0.75****
95. 26 ± 5.10**** 139. 42 ± 7.59****
96. 47 ± 8.75**** 140. 62 ± 6.91****
97. 33 ± 5.47**** 141. 31 ± 7.00****
98. 32 ± 2.56**** 142. 42 ± 10.98****
99. 49 ± 2.91**** 143. 40 ± 0.75****
100. 56 ± 2.22**** 144. 46 ± 6.44****
101. 60 ± 9.10**** 145. 49 ± 6.78****
102. 51 ± 10.54**** 146. 81 ±1.15****
103. 47 ± 4.14**** 147. 60 ± 7.70****
104. 42 ± 5.83**** 148. 85 ± 4.58****
105. 58 ± 0.42**** 149. 79 ± 3.56****
106. 52 ± 4.45**** 150. 81 ± 5.85****
107. 60 ± 1.43**** 151. 75 ± 2.30****
108. 54 ± 5.62**** 152. 93 ± 9.141), ****
109. 54 ± 2.41**** 153. 64 ± 9.98****
110. 62 ± 1.59**** 154. 56 ± 0.75****
111. 22 ± 8.60**** 155. 76 ± 7.22****
112. 36 ± 6.60**** 156. 63 ± 8.12****
113. 40 ± 4.41**** 157. 55 ± 1.71****
114. 52 ± 3.52**** 158. 67 ± 6.87****
115. 52 ± 0.40**** 159. 55 ± 1.71****
116. 24 ± 1.82**** 160. 51 ± 6.12****
117. 32 ± 6.94**** 161. 49 ± 6.16****
118. 37 ± 7.40**** 162. 68 ± 3.74****
119. 47 ± 3.78**** 163. 56 ± 4.86****
120. 47 ± 2.86**** 164. 45 ± 4.55****
121. 56 ± 4.36**** 165. 49 ± 7.22****
122. 12 ± 0.40* 166. 57 ± 2.08****
123. 44 ± 2.48**** 167. 45 ± 4.31****
124. 57 ± 9.64**** 168. 57 ± 4.54****
125. 49 ± 3.24**** 169. 63 ± 5.88****
126. 61 ± 2.60**** 170. 67 ± 2.08****
127. 63 ± 3.63**** 171. 71 ± 4.17****
128. 58 ± 2.10**** 172. 64 ± 1.94****
129. 59 ± 3.10**** 173. 78 ± 2.45****
130. 59 ± 0.75**** 174. 66 ± 1.63****
131. 37 ± 5.89**** 175. 59 ± 1.71****
176. 70 ± 4.91**** 179. 67 ± 6.72****
177. 71 ± 2.32**** 180. 105 ± 1.631), ****
178. 75 ± 2.38**** 181. 62 ± 4.74****

Each extract was tested at a final concentration of 100 μg/mL, and results are presented as mean ± SD from triplicate experiments.

Differences between each extract (n = 181) and the control were assessed by one-way analysis of variance (ANOVA) followed by Dunnett’s multiple comparisons test.

1) Orlistat was used as the positive control, and the top five extracts with the highest activity.

Adjusted p-values are reported; statistical significance is denoted as

* p < 0.05,

** p < 0.01, and

**** p < 0.0001.

Download Excel Table

These findings suggest that the identified extracts could be promising candidates for reducing fat absorption, supporting the development of new anti-obesity agents (Hou et al., 2022).

MetS is a complex health condition in which multiple metabolic disorders, including obesity, hyperglycemia, and dyslipidemia, occur simultaneously, and it is recognized as a major cause of cardiovascular disease and type 2 diabetes (Heindel et al., 2017). The increasing prevalence of MetS, primarily driven by reduced physical activity, high-calorie diets, and the widespread adoption of Westernized eating habits, is considered a significant public health concern worldwide, leading to an increasing demand for effective therapeutic strategies (Asghari et al., 2015; Dziegielewska-Gesiak, 2021). Various mechanisms have been investigated for the treatment of MetS, and among them, enzyme inhibitors targeting α-glucosidase, DPP-IV, and pancreatic lipase have been demonstrated to be effective in the management of type 2 diabetes and obesity (Hossain et al., 2020; Kumar & Chauhan, 2021; Lunagariya et al., 2014).

Acarbose, a well-known α-glucosidase inhibitor, reduces glucose absorption in the intestinal lumen and enhances insulin sensitivity, thereby effectively controlling postprandial hyperglycemia and hyperinsulinemia (Altay, 2022). It is considered a safe and effective therapeutic agent for managing postprandial blood glucose levels, as it does not increase the risk of hypoglycemia or weight gain (Uuh Narvaez & Segura Campos, 2022). However, acarbose has been associated with gastrointestinal adverse effects, such as gas, bloating, and diarrhea (Hollander, 1992), and its efficacy has not been confirmed in cardiovascular outcome trials (Altay, 2022). Similarly, Ile-Pro-Ile, also known as diprotin A, is a well-known DPP-IV inhibitor that effectively prevents the degradation of GLP-1 in vitro (Holst et al., 1998). However, its in vivo efficacy remains limited, and several adverse effects, including nasopharyngitis, headache, nausea, hypersensitivity, dermatological reactions, and pancreatitis, have been reported (Juillerat-Jeanneret, 2014). Likewise, orlistat is a well-known pancreatic lipase inhibitor that reduces fat absorption by binding to the active site of the enzyme during the digestive process, thereby promoting the excretion of undigested dietary fat (Bülbül & Çokdinleyen, 2024). However, orlistat has been reported to induce gastrointestinal side effects, including bloating, loose stools, or diarrhea (Morales et al., 2016). Given these concerns, the long-term use of synthetic drugs targeting these enzymes may lead to adverse effects and reduced patient compliance (Asliddin & Gulnaz, 2025). Accordingly, there is a need for effective and sustainable alternative treatments that can overcome the limitations of current pharmacological approaches.

In this context, natural product-based therapeutics, known for their generally greater safety than synthetic drugs, are increasingly regarded as promising alternatives, owing to their structural diversity, favorable biocompatibility, and potential for multi-target activity (Meier & Lappas, 2016; Wu et al., 2025). Especially, coastal plants represent a promising resource due to their capacity to produce diverse bioactive metabolites in response to environmental stresses such as high salinity, ultraviolet radiation, and nutrient limitations (Saba Nazir et al., 2018; Sadeghi et al., 2024). To adapt to such environmental stresses, coastal plants are known to produce a wide array of secondary metabolites, including potent antioxidants such as phenolic compounds (Stanković et al., 2023). These bioactive constituents may act as valuable enzyme inhibitors, highlighting their therapeutic potential for potential in the management of MetS.

In this study, the inhibitory activities of 181 natural extracts derived from coastal island were evaluated against α-glucosidase, DPP-IV, and pancreatic lipase in vitro. Several extracts exhibited inhibitory activities that were comparable to or even exceeded those of commercially available positive controls. Notably, certain extracts, including Hypochaeris radicata, Vaccinium bracteatum Thunb., Sorbus ulleungensis Chin. S. Chang, Lonicera insularis Nakai, and Trachelospermum asiaticum (Siebold & Zucc.) Nakai, exhibited potent inhibitory activity across all three enzyme assays, highlighting their potential as multifunctional natural therapeutics for the simultaneous regulation of carbohydrate and lipid metabolism. Given that MetS is characterized by a multifactorial pathophysiology involving the dysregulation of multiple metabolic pathways, therapeutic strategies that simultaneously modulate multiple targets are increasingly recognized as being more efficacious than those focusing on a single enzyme or pathway (Lillich et al., 2021). Accordingly, the simultaneous inhibition of α-glucosidase, DPP-IV, and pancreatic lipase by these extracts suggests a broader modulatory potential on the metabolic disturbances underlying MetS, thereby conferring therapeutic advantages over agents targeting a single enzymatic pathway. Moreover, these extracts present as high-value natural therapeutic candidates, offering potential advantages over conventional drugs, which often face challenges such as high costs, adverse side effects, and resistance.

In conclusion, this study provides robust scientific evidence supporting the potential of island-derived natural resources as sustainable and effective therapeutic agents for managing MetS. These findings provide a strong basis for the development of natural product-based alternatives to conventional pharmacological treatments. To facilitate clinical translation into pharmacotherapy, functional food development, and preventive strategies, future studies should aim to isolate the active constituents and validate their efficacy and safety through vivo and clinical trials.

Competing interests

No potential conflict of interest relevant to this article was reported.

Funding sources

This work was supported financially by Korea Environment Industry & Technology Institute through Project to make multi-ministerial national biological research resources more advanced program, funded by Korea Ministry of Environment (grant number RS-2023-00230403) and it was also supported by the Soonchunhyang University Research Fund.

Acknowledgements

Not applicable.

Availability of data and materials

Upon reasonable request, the datasets of this study can be available from the corresponding author.

Ethics approval and consent to participate

Not applicable.

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