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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| Format: | Article |
| Language: | English |
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Pontificia Universidad Catolica de Valparaiso
2010
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| Online Access: | http://psasir.upm.edu.my/id/eprint/13278/ http://psasir.upm.edu.my/id/eprint/13278/1/Artificial%20neural%20network%20modeling%20studies%20to%20predict%20the%20yield%20of%20enzymatic%20synthesis%20of%20betulinic%20acid%20ester.pdf |
| _version_ | 1848842069297070080 |
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| author | Moghaddam, Mansour Ghaffari Ahmad @ Amat, Faujan Basri, Mahiran Abdul Rahman, Mohd Basyaruddin |
| author_facet | Moghaddam, Mansour Ghaffari Ahmad @ Amat, Faujan Basri, Mahiran Abdul Rahman, Mohd Basyaruddin |
| author_sort | Moghaddam, Mansour Ghaffari |
| building | UPM Institutional Repository |
| collection | Online Access |
| 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). |
| first_indexed | 2025-11-15T07:53:16Z |
| format | Article |
| id | upm-13278 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T07:53:16Z |
| publishDate | 2010 |
| publisher | Pontificia Universidad Catolica de Valparaiso |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-132782016-12-09T08:48:21Z http://psasir.upm.edu.my/id/eprint/13278/ Artificial neural network modeling studies to predict the yield of enzymatic synthesis of betulinic acid ester Moghaddam, Mansour Ghaffari Ahmad @ Amat, Faujan Basri, Mahiran Abdul Rahman, Mohd Basyaruddin 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). Pontificia Universidad Catolica de Valparaiso 2010-05-15 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/13278/1/Artificial%20neural%20network%20modeling%20studies%20to%20predict%20the%20yield%20of%20enzymatic%20synthesis%20of%20betulinic%20acid%20ester.pdf Moghaddam, Mansour Ghaffari and Ahmad @ Amat, Faujan and Basri, Mahiran and Abdul Rahman, Mohd Basyaruddin (2010) Artificial neural network modeling studies to predict the yield of enzymatic synthesis of betulinic acid ester. Electronic Journal of Biotechnology, 13 (3). pp. 1-12. ISSN 0717-3458 http://www.ejbiotechnology.info/index.php/ejbiotechnology/article/view/v13n3-9 10.2225/vol13-issue3-fulltext-9 |
| spellingShingle | Moghaddam, Mansour Ghaffari Ahmad @ Amat, Faujan Basri, Mahiran Abdul Rahman, Mohd Basyaruddin 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 |
| url | http://psasir.upm.edu.my/id/eprint/13278/ http://psasir.upm.edu.my/id/eprint/13278/ http://psasir.upm.edu.my/id/eprint/13278/ http://psasir.upm.edu.my/id/eprint/13278/1/Artificial%20neural%20network%20modeling%20studies%20to%20predict%20the%20yield%20of%20enzymatic%20synthesis%20of%20betulinic%20acid%20ester.pdf |