Timesaving for Conformational Analysis by Machine Learning

In the conformational analysis of [Mg(dmso)6]2+ complex cation (dmso: dimethylsulfoxide), 130 candidates of the conformers were successfully narrowed down to 26 conformers by machine learning. As a result, the time required for the structural optimization turned out to be reduced to 1/8, and the mac...

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Published inJournal of Computer Chemistry, Japan Vol. 18; no. 3; pp. 150 - 151
Main Author SAKIYAMA, Hiroshi
Format Journal Article
LanguageJapanese
Published Society of Computer Chemistry, Japan 2019
Subjects
ディープニューラルネットワーク
マシンラーニング
構造予測
正八面体型錯体
配座解析
Online AccessGet full text
ISSN1347-1767
1347-3824
DOI10.2477/jccj.2019-0020

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Abstract In the conformational analysis of [Mg(dmso)6]2+ complex cation (dmso: dimethylsulfoxide), 130 candidates of the conformers were successfully narrowed down to 26 conformers by machine learning. As a result, the time required for the structural optimization turned out to be reduced to 1/8, and the machine learning was found to be effective in timesaving for conformational analysis.
AbstractList In the conformational analysis of [Mg(dmso)6]2+ complex cation (dmso: dimethylsulfoxide), 130 candidates of the conformers were successfully narrowed down to 26 conformers by machine learning. As a result, the time required for the structural optimization turned out to be reduced to 1/8, and the machine learning was found to be effective in timesaving for conformational analysis.
Author SAKIYAMA, Hiroshi
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References [7] H. Sakiyama, J. Comput. Chem. Jpn. Int. Ed., 4, 2018-0013 (2018).
[4] Project Jupyter, 2018 https://jupyter.org/.
[5] TensorFlow, 2018 https://www.tensorflow.org/.
[2] H. Sakiyama, K. Waki, Iranian, J. Math. Chem., 7, 223 (2016).
[3] Anaconda, 2018 https://www.anaconda.com/.
[1] H. Sakiyama, K. Shomura, M. Ito, K. Waki, M. Yamasaki, Dalton Trans., 48, 10174 (2019). , doi:10.1039/C9DT02173F31187849
[6] Keras, 2018 https://keras.io/ 2.0.
References_xml – reference: [2] H. Sakiyama, K. Waki, Iranian, J. Math. Chem., 7, 223 (2016).
– reference: [7] H. Sakiyama, J. Comput. Chem. Jpn. Int. Ed., 4, 2018-0013 (2018).
– reference: [4] Project Jupyter, 2018 https://jupyter.org/.
– reference: [3] Anaconda, 2018 https://www.anaconda.com/.
– reference: [6] Keras, 2018 https://keras.io/ 2.0.
– reference: [5] TensorFlow, 2018 https://www.tensorflow.org/.
– reference: [1] H. Sakiyama, K. Shomura, M. Ito, K. Waki, M. Yamasaki, Dalton Trans., 48, 10174 (2019). , doi:10.1039/C9DT02173F31187849
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SubjectTerms ディープニューラルネットワーク
マシンラーニング
構造予測
正八面体型錯体
配座解析
Title Timesaving for Conformational Analysis by Machine Learning
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