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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...

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Main Authors: Ashari, Siti Efliza, Abdul Karim, Nurul Hidayu, Khairudin, Nur Shafira, Syed Azhar, Sharifah Nurfadhlin Afifah
Format: Article
Language:English
Published: Elsevier 2020
Online Access:http://psasir.upm.edu.my/id/eprint/86580/1/Lipase-catalysed%20synthesis.pdf
http://psasir.upm.edu.my/id/eprint/86580/
https://www.sciencedirect.com/science/article/abs/pii/S0022286020300855?via%3Dihub
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spelling my.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
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
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.
format Article
author Ashari, Siti Efliza
Abdul Karim, Nurul Hidayu
Khairudin, Nur Shafira
Syed Azhar, Sharifah Nurfadhlin Afifah
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
author_facet Ashari, Siti Efliza
Abdul Karim, Nurul Hidayu
Khairudin, Nur Shafira
Syed Azhar, Sharifah Nurfadhlin Afifah
author_sort Ashari, Siti Efliza
title 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_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_sort lipase-catalysed synthesis of a novel galanthamine derivative: process optimisation by artificial neural networks
publisher Elsevier
publishDate 2020
url http://psasir.upm.edu.my/id/eprint/86580/1/Lipase-catalysed%20synthesis.pdf
http://psasir.upm.edu.my/id/eprint/86580/
https://www.sciencedirect.com/science/article/abs/pii/S0022286020300855?via%3Dihub
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score 13.211869

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