Lipase-catalysed synthesis of a novel galanthamine derivative: process optimisation by artificial neural networks
Artificial neural networks (ANNs) analysis was carried out to optimize the esterification of galanthamine and acetic acid in a solvent system. To predict performance parameters of the enzymatic reaction conditions, several parameters were studied which were reaction temperature (50–90 °C), enzyme am...
| Үндсэн зохиолчид: | , , , |
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| Формат: | Өгүүллэг |
| Хэл сонгох: | English |
| Хэвлэсэн: |
Elsevier
2020
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| Онлайн хандалт: | http://psasir.upm.edu.my/id/eprint/86580/1/Lipase-catalysed%20synthesis.pdf |
| _version_ | 1825952227438624768 |
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| author | Ashari, Siti Efliza Abdul Karim, Nurul Hidayu Khairudin, Nur Shafira Syed Azhar, Sharifah Nurfadhlin Afifah |
| author_facet | Ashari, Siti Efliza Abdul Karim, Nurul Hidayu Khairudin, Nur Shafira Syed Azhar, Sharifah Nurfadhlin Afifah |
| author_sort | Ashari, Siti Efliza |
| collection | UPM |
| description | Artificial neural networks (ANNs) analysis was carried out to optimize the esterification of galanthamine and acetic acid in a solvent system. To predict performance parameters of the enzymatic reaction conditions, several parameters were studied which were reaction temperature (50–90 °C), enzyme amount (2–5 wt%), reaction time (6–18 h), and substrate molar ratio of galanthamine to acetic acid (2–5:1). The algoritms used in the network were batch back propagation (BBP), incremental back propagation (IBP), genetic algorithm (GA), Levenberg–Marguardt (LM) and quick propagation (QP) algorithms. The configuration of 4 inputs, one hidden layer with 7 nodes, and 1 output using the batch back propagation (BBP) was determined as the optimum algorithm. The predicted and experimental percentage yield value were 60.24% and 60.36%, respectively. These results prove the validity of ANN model. |
| first_indexed | 2024-03-06T10:41:46Z |
| format | Article |
| id | upm.eprints-86580 |
| institution | Universiti Putra Malaysia |
| language | English |
| last_indexed | 2024-03-06T10:41:46Z |
| publishDate | 2020 |
| publisher | Elsevier |
| record_format | dspace |
| spelling | upm.eprints-865802021-09-26T22:30:19Z http://psasir.upm.edu.my/id/eprint/86580/ Lipase-catalysed synthesis of a novel galanthamine derivative: process optimisation by artificial neural networks Ashari, Siti Efliza Abdul Karim, Nurul Hidayu Khairudin, Nur Shafira Syed Azhar, Sharifah Nurfadhlin Afifah Artificial neural networks (ANNs) analysis was carried out to optimize the esterification of galanthamine and acetic acid in a solvent system. To predict performance parameters of the enzymatic reaction conditions, several parameters were studied which were reaction temperature (50–90 °C), enzyme amount (2–5 wt%), reaction time (6–18 h), and substrate molar ratio of galanthamine to acetic acid (2–5:1). The algoritms used in the network were batch back propagation (BBP), incremental back propagation (IBP), genetic algorithm (GA), Levenberg–Marguardt (LM) and quick propagation (QP) algorithms. The configuration of 4 inputs, one hidden layer with 7 nodes, and 1 output using the batch back propagation (BBP) was determined as the optimum algorithm. The predicted and experimental percentage yield value were 60.24% and 60.36%, respectively. These results prove the validity of ANN model. Elsevier 2020-05-05 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/86580/1/Lipase-catalysed%20synthesis.pdf Ashari, Siti Efliza and Abdul Karim, Nurul Hidayu and Khairudin, Nur Shafira and Syed Azhar, Sharifah Nurfadhlin Afifah (2020) Lipase-catalysed synthesis of a novel galanthamine derivative: process optimisation by artificial neural networks. Journal of Molecular Structure, 1207. 280 - 286. ISSN 0022-2860 https://www.sciencedirect.com/science/article/abs/pii/S0022286020300855?via%3Dihub 10.1016/j.molstruc.2020.127761 |
| spellingShingle | Ashari, Siti Efliza Abdul Karim, Nurul Hidayu Khairudin, Nur Shafira Syed Azhar, Sharifah Nurfadhlin Afifah Lipase-catalysed synthesis of a novel galanthamine derivative: process optimisation by artificial neural networks |
| title | Lipase-catalysed synthesis of a novel galanthamine derivative: process optimisation by artificial neural networks |
| title_full | Lipase-catalysed synthesis of a novel galanthamine derivative: process optimisation by artificial neural networks |
| title_fullStr | Lipase-catalysed synthesis of a novel galanthamine derivative: process optimisation by artificial neural networks |
| title_full_unstemmed | Lipase-catalysed synthesis of a novel galanthamine derivative: process optimisation by artificial neural networks |
| title_short | Lipase-catalysed synthesis of a novel galanthamine derivative: process optimisation by artificial neural networks |
| title_sort | lipase catalysed synthesis of a novel galanthamine derivative process optimisation by artificial neural networks |
| url | http://psasir.upm.edu.my/id/eprint/86580/1/Lipase-catalysed%20synthesis.pdf |
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