Scopus
YÖKSİS ISSN Eşleşti
SJR Q1
Chemical characterization, phytochemical profiling, antioxidant and antidiabetic properties of Halopithys incurva (Hudson) Batters, 1902: In vitro and in silico approaches
Algal Research · Nisan 2026
Özet
Postprandial hyperglycemia (PPHG) is an early disturbance in glucose homeostasis linked to type 2 diabetes (T2D) and is often accompanied by oxidative stress. Inhibiting carbohydrate-hydrolyzing enzymes, particularly α-amylase and α-glucosidase is a key strategy for managing PPHG and preventing T2D. However, the adverse effects of synthetic inhibitors highlight the need for safer natural alternatives. This study investigated the seaweed Halopithys incurva as a potential source of bioactive compounds with antioxidant and antidiabetic properties. Five extracts (n-hexane, dichloromethane, ethanol, methanol, and water) were prepared and subjected to chemical characterization and the estimation of total phenol content (TPC), total flavonoid content (TFC), and total tannin content (TTC). Six complementary in vitro antioxidant assays, together with in vitro antidiabetic assays were performed. The dichloromethane extract contained the highest levels of TPC, TFC, and TTC. The ethanol extract showed the strongest anti-DPPH (503.60 ± 2.14 mg TE/g dry extract) and anti-ABTS (668.55 ± 7.15 mg TE/g dry extract) activities, along with high activity in CUPRAC assay (632.13 ± 14.9 mg TE/g dry extract). The methanol extract showed the highest activity in both CUPRAC and PBD assays (949.33 ± 21.61 mg TE/g dry extract and 4.06 ± 0.011 mmol TE/g dry extract, respectively). Among the tested samples dichloromethane, ethanol, and methanol extracts demonstrated the most potent dual antidiabetic activity among the tested extracts. Nine compounds were identified for the first time from this species and subsequently screened as ligands in in-silico study to elucidate their molecular mechanisms. The results highlighted the strong antioxidant and antidiabetic potential of H. incurva extracts and emphasized the role of herniarin, toddalolactone, loliolide, and isololiolide as promising antidiabetic molecules.
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Convolutional neural network - Support vector machine based approach for classification of cyanobacteria and chlorophyta microalgae groups
2022 ISSN: 2211-9264 SCI-Expanded Q1
Doç. Dr. BARAN AŞIKKUTLU →
Makale Bilgileri
Dergi
Algal Research
Toplam Atıf
3 atıf
· Scopus
ISSN22119264
Yayın TarihiNisan 2026
Cilt / Sayfa95
Scopus ID2-s2.0-105031424590
Kurumlar
College of Medicine
Abha Saudi Arabia
Faculté de Médecine et de Pharmacie de Rabat
Rabat Morocco
Faculté des Sciences Ben M’Sick
Casablanca Morocco
Faculté des Sciences Rabat
Rabat Morocco
Selçuk Üniversitesi
Selçuklu Turkey
Université Abdelmalek Essaadi
Tetouan Morocco
Havuzumuzdaki Atıflar 0
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Scimago Dergi (ISSN Eşleşmesi)
Algal Research
Q1
SJR Skoru0,914
H-Index123
YayıncıElsevier B.V.
ÜlkeNetherlands
Agronomy and Crop Science (Q1)
Metrikler
3
Atıf