Artificial neural network modeling studies to predict the yield of enzymatic synthesis of betulinic acid ester

3β-O-phthalic ester of betulinic acid was synthesized from reaction of betulinic acid and phthalic anhydride using lipase as biocatalyst. This ester has clinical potential as an anticancer agent. In this study, artificial neural network (ANN) analysis of Candida antarctica lipase (Novozym 435) -cata...

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Main Authors: Moghaddam, Mansour Ghaffari, Ahmad, Faujan Bin H., Basri, Mahiran, Rahman, Mohd Basyaruddin Abdul
Format: Article in Journal/Newspaper
Language:English
Published: Universidad Católica de Valparaíso 2011
Subjects:
Online Access:http://hdl.handle.net/1807/49063
http://www.bioline.org.br/abstract?id=ej10025
http://www.bioline.org.br/ej
http://www.ejbiotechnology.info
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author Moghaddam, Mansour Ghaffari
Ahmad, Faujan Bin H.
Basri, Mahiran
Rahman, Mohd Basyaruddin Abdul
author_facet Moghaddam, Mansour Ghaffari
Ahmad, Faujan Bin H.
Basri, Mahiran
Rahman, Mohd Basyaruddin Abdul
author_sort Moghaddam, Mansour Ghaffari
collection University of Toronto: Research Repository T-Space
description 3β-O-phthalic ester of betulinic acid was synthesized from reaction of betulinic acid and phthalic anhydride using lipase as biocatalyst. This ester has clinical potential as an anticancer agent. In this study, artificial neural network (ANN) analysis of Candida antarctica lipase (Novozym 435) -catalyzed esterification of betulinic acid with phthalic anhydride was carried out. A multilayer feed-forward neural network trained with an error back-propagation algorithm was incorporated for developing a predictive model. The input parameters of the model are reaction time, reaction temperature, enzyme amount and substrate molar ratio while the percentage isolated yield of ester is the output. Four different training algorithms, belonging to two classes, namely gradient descent and Levenberg-Marquardt (LM), were used to train ANN. The paper makes a robust comparison of the performances of the above four algorithms employing standard statistical indices. The results showed that the quick propagation algorithm (QP) with 4-9-1 arrangement gave the best performances. The root mean squared error (RMSE), coefficient of determination (R2) and absolute average deviation (AAD) between the actual and predicted yields were determined as 0.0335, 0.9999 and 0.0647 for training set, 0.6279, 0.9961 and 1.4478 for testing set and 0.6626, 0.9488 and 1.0205 for validation set using quick propagation algorithm (QP).
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op_relation http://hdl.handle.net/1807/49063
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op_rights Copyright 2010 - Pontificia Universidad Católica de Valparaíso -- Chile
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spelling ftunivtoronto:oai:localhost:1807/49063 2025-01-16T19:02:13+00:00 Artificial neural network modeling studies to predict the yield of enzymatic synthesis of betulinic acid ester Moghaddam, Mansour Ghaffari Ahmad, Faujan Bin H. Basri, Mahiran Rahman, Mohd Basyaruddin Abdul 2011-03-29 http://hdl.handle.net/1807/49063 http://www.bioline.org.br/abstract?id=ej10025 http://www.bioline.org.br/ej http://www.ejbiotechnology.info en eng Universidad Católica de Valparaíso http://hdl.handle.net/1807/49063 http://www.bioline.org.br/abstract?id=ej10025 http://www.bioline.org.br/ej http://www.ejbiotechnology.info Copyright 2010 - Pontificia Universidad Católica de Valparaíso -- Chile Novozym 435 enzymatic synthesis Candida antarctica lipase betulinic acid artificial neural network acylation Article 2011 ftunivtoronto 2020-06-17T11:33:00Z 3β-O-phthalic ester of betulinic acid was synthesized from reaction of betulinic acid and phthalic anhydride using lipase as biocatalyst. This ester has clinical potential as an anticancer agent. In this study, artificial neural network (ANN) analysis of Candida antarctica lipase (Novozym 435) -catalyzed esterification of betulinic acid with phthalic anhydride was carried out. A multilayer feed-forward neural network trained with an error back-propagation algorithm was incorporated for developing a predictive model. The input parameters of the model are reaction time, reaction temperature, enzyme amount and substrate molar ratio while the percentage isolated yield of ester is the output. Four different training algorithms, belonging to two classes, namely gradient descent and Levenberg-Marquardt (LM), were used to train ANN. The paper makes a robust comparison of the performances of the above four algorithms employing standard statistical indices. The results showed that the quick propagation algorithm (QP) with 4-9-1 arrangement gave the best performances. The root mean squared error (RMSE), coefficient of determination (R2) and absolute average deviation (AAD) between the actual and predicted yields were determined as 0.0335, 0.9999 and 0.0647 for training set, 0.6279, 0.9961 and 1.4478 for testing set and 0.6626, 0.9488 and 1.0205 for validation set using quick propagation algorithm (QP). Article in Journal/Newspaper Antarc* Antarctica University of Toronto: Research Repository T-Space
spellingShingle Novozym 435
enzymatic synthesis
Candida antarctica lipase
betulinic acid
artificial neural network
acylation
Moghaddam, Mansour Ghaffari
Ahmad, Faujan Bin H.
Basri, Mahiran
Rahman, Mohd Basyaruddin Abdul
Artificial neural network modeling studies to predict the yield of enzymatic synthesis of betulinic acid ester
title Artificial neural network modeling studies to predict the yield of enzymatic synthesis of betulinic acid ester
title_full Artificial neural network modeling studies to predict the yield of enzymatic synthesis of betulinic acid ester
title_fullStr Artificial neural network modeling studies to predict the yield of enzymatic synthesis of betulinic acid ester
title_full_unstemmed Artificial neural network modeling studies to predict the yield of enzymatic synthesis of betulinic acid ester
title_short Artificial neural network modeling studies to predict the yield of enzymatic synthesis of betulinic acid ester
title_sort artificial neural network modeling studies to predict the yield of enzymatic synthesis of betulinic acid ester
topic Novozym 435
enzymatic synthesis
Candida antarctica lipase
betulinic acid
artificial neural network
acylation
topic_facet Novozym 435
enzymatic synthesis
Candida antarctica lipase
betulinic acid
artificial neural network
acylation
url http://hdl.handle.net/1807/49063
http://www.bioline.org.br/abstract?id=ej10025
http://www.bioline.org.br/ej
http://www.ejbiotechnology.info