In Silico Analysis and ADMET Prediction of Flavonoid Compounds from Syzigium cumini var. album on α-Glucosidase Receptor for Searching Anti-Diabetic Drug Candidates
Background: One of the causes of death is diabetes. Anti-diabetic drugs currently available do not work optimally because some have been reported to have side effect and resistance. Objective: This study aimed to flavonoid compounds from Syzygium cumini var. album with the greatest anti-diabetic act...
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Pharmacognosy Network Worldwide
2022
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id-langga.1250552023-04-28T01:19:53Z https://repository.unair.ac.id/125055/ In Silico Analysis and ADMET Prediction of Flavonoid Compounds from Syzigium cumini var. album on α-Glucosidase Receptor for Searching Anti-Diabetic Drug Candidates Yanu Andhiarto, - Suciati, - Ersanda Nurma Praditapuspa, - Sukardiman, - R Medicine RS Pharmacy and materia medica RS1-441 Pharmacy and materia medica RS200-201 Pharmaceutical dosage forms Background: One of the causes of death is diabetes. Anti-diabetic drugs currently available do not work optimally because some have been reported to have side effect and resistance. Objective: This study aimed to flavonoid compounds from Syzygium cumini var. album with the greatest anti-diabetic activity and lower toxicity than acarbose. Materials and Methods: This research is an in silico study of nine flavonoid compounds from Syzygium cumini var. album, starting with PASS online was used to predict the activity spectrum of substances, drug-likeness prediction using DruLiTo, ADMET prediction (absorption, distribution, metabolism, excretion, and toxicity) using pkCSM online. Molecular docking was carried out by the AutoDock 4.2.6 program on α-glucosidase targeting. Visualization is done with the Discovery Studio Visualizer software. Results: From the data obtained, D-(+)-Catechin has a high affinity for α-glucosidase with a free energy of binding (ΔG) -5.94 kcal/mol and an inhibition constant (Ki) of 44270 nm. Conclusion: Based on the results of the study, it can be concluded that the flavonoid compounds from Syzygium cumini var. album has the potential as a promising anti-diabetic drug candidate, where the best candidate is D- (+)-Catechin. However, further studies of flavonoid compounds from Syzygium cumini var. album are needed. Pharmacognosy Network Worldwide 2022-10-05 Article PeerReviewed text en https://repository.unair.ac.id/125055/1/C-14_Artikel.pdf text en https://repository.unair.ac.id/125055/2/C-14%20kualitas%20karil%20dan%20validasi%20kadep.pdf text en https://repository.unair.ac.id/125055/3/C-14_Similarity.pdf Yanu Andhiarto, - and Suciati, - and Ersanda Nurma Praditapuspa, - and Sukardiman, - (2022) In Silico Analysis and ADMET Prediction of Flavonoid Compounds from Syzigium cumini var. album on α-Glucosidase Receptor for Searching Anti-Diabetic Drug Candidates. Pharmacognosy Journal, 14 (6). pp. 736-743. ISSN 0975-3575 https://www.phcogj.com/article/1904 http://dx.doi.org/10.5530/pj.2022.14.161 |
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R Medicine RS Pharmacy and materia medica RS1-441 Pharmacy and materia medica RS200-201 Pharmaceutical dosage forms Yanu Andhiarto, - Suciati, - Ersanda Nurma Praditapuspa, - Sukardiman, - In Silico Analysis and ADMET Prediction of Flavonoid Compounds from Syzigium cumini var. album on α-Glucosidase Receptor for Searching Anti-Diabetic Drug Candidates |
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Background: One of the causes of death is diabetes. Anti-diabetic drugs currently available do not work optimally because some have been reported to have side effect and resistance. Objective: This study aimed to flavonoid compounds from Syzygium cumini var. album with the greatest anti-diabetic activity and lower toxicity than acarbose. Materials and Methods: This research is an in silico study of nine flavonoid compounds from Syzygium cumini var. album, starting with PASS online was used to predict the activity spectrum of substances, drug-likeness prediction using DruLiTo, ADMET prediction (absorption, distribution, metabolism, excretion, and toxicity) using pkCSM online. Molecular docking was carried out by the AutoDock 4.2.6 program on α-glucosidase targeting. Visualization is done with the Discovery Studio Visualizer software. Results: From the data obtained, D-(+)-Catechin has a high affinity for α-glucosidase with a free energy of binding (ΔG) -5.94 kcal/mol and an inhibition constant (Ki) of 44270 nm. Conclusion: Based on the results of the study, it can be concluded that the flavonoid compounds from Syzygium cumini var. album has the potential as a promising anti-diabetic drug candidate, where the best candidate is D- (+)-Catechin. However, further studies of flavonoid compounds from Syzygium cumini var. album are needed. |
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Article PeerReviewed |
author |
Yanu Andhiarto, - Suciati, - Ersanda Nurma Praditapuspa, - Sukardiman, - |
author_facet |
Yanu Andhiarto, - Suciati, - Ersanda Nurma Praditapuspa, - Sukardiman, - |
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Yanu Andhiarto, - |
title |
In Silico Analysis and ADMET Prediction of Flavonoid Compounds from Syzigium cumini var. album on α-Glucosidase Receptor for Searching Anti-Diabetic Drug Candidates |
title_short |
In Silico Analysis and ADMET Prediction of Flavonoid Compounds from Syzigium cumini var. album on α-Glucosidase Receptor for Searching Anti-Diabetic Drug Candidates |
title_full |
In Silico Analysis and ADMET Prediction of Flavonoid Compounds from Syzigium cumini var. album on α-Glucosidase Receptor for Searching Anti-Diabetic Drug Candidates |
title_fullStr |
In Silico Analysis and ADMET Prediction of Flavonoid Compounds from Syzigium cumini var. album on α-Glucosidase Receptor for Searching Anti-Diabetic Drug Candidates |
title_full_unstemmed |
In Silico Analysis and ADMET Prediction of Flavonoid Compounds from Syzigium cumini var. album on α-Glucosidase Receptor for Searching Anti-Diabetic Drug Candidates |
title_sort |
in silico analysis and admet prediction of flavonoid compounds from syzigium cumini var. album on α-glucosidase receptor for searching anti-diabetic drug candidates |
publisher |
Pharmacognosy Network Worldwide |
publishDate |
2022 |
url |
https://repository.unair.ac.id/125055/1/C-14_Artikel.pdf https://repository.unair.ac.id/125055/2/C-14%20kualitas%20karil%20dan%20validasi%20kadep.pdf https://repository.unair.ac.id/125055/3/C-14_Similarity.pdf https://repository.unair.ac.id/125055/ https://www.phcogj.com/article/1904 http://dx.doi.org/10.5530/pj.2022.14.161 |
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