Takashiro Akitsu - Computational and Data-Driven Chemistry Using Artificial Intelligence: Fundamentals, Methods and Applications

Computational and Data-Driven Chemistry Using Artificial Intelligence

Fundamentals, Methods and Applications

First Edition

Takashiro Akitsu

Department of Chemistry, Faculty of Science, Tokyo University of Science, Tokyo, Japan

Copyright

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ISBN: 9978-0-12-822249-2

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Contributors

Takashiro Akitsu Department of Chemistry, Faculty of Science, Tokyo University of Science, Tokyo, Japan

Golnaz Bissadi University of Applied Sciences Niederrhein, Institute for Surface Technology, Krefeld, Germany

Thomas Cauchy Laboratoire MOLTECH-Anjou, UMR CNRS 6200, UNIV Angers, SFR MATRIX, Angers, France

Kevin Cremanns University of Applied Sciences Niederrhein, Institute of Modelling and High-Performance Computing, Krefeld, Germany

Batrice Duval Laboratoire LERIA, UNIV Angers, SFR MathSTIC, Angers, France

Dea Gogishvili Medicinal Chemistry, Research and Early Development, Respiratory and Immunology (R&I), BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden

Junpei Iwama Department of Chemistry, Faculty of Science, Tokyo University of Science, Tokyo, Japan

Masato Kobayashi

Faculty of Science & WPI-ICReDD, Hokkaido University, Sapporo

ESICB, Kyoto University, Kyoto, Japan

Thierry Kogej Hit Discovery, Discovery Sciences, MolecularAI, R&D, AstraZeneca Gothenburg, Sweden

Jules Leguy Laboratoire LERIA, UNIV Angers, SFR MathSTIC, Angers, France

Benoit Da Mota Laboratoire LERIA, UNIV Angers, SFR MathSTIC, Angers, France

Eva Nittinger Medicinal Chemistry, Research and Early Development, Respiratory and Immunology (R&I), BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden

Atanas Patronov Hit Discovery, Discovery Sciences, MolecularAI, R&D, AstraZeneca Gothenburg, Sweden

Shi-Ping Peng State Key Laboratory for Physical Chemistry of Solid Surfaces, iChEM, Fujian Provincial Key Lab of Theoretical and Computational Chemistry, and College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, Peoples Republic of China

Hiroshi Sakiyama Yamagata University, Yamagata, Japan

Christian Schmitz University of Applied Sciences Niederrhein, Institute for Surface and Coatings Chemistry, Krefeld, Germany

Christian Tyrchan Medicinal Chemistry, Research and Early Development, Respiratory and Immunology (R&I), BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden

Xin-Yu Yang State Key Laboratory for Physical Chemistry of Solid Surfaces, iChEM, Fujian Provincial Key Lab of Theoretical and Computational Chemistry, and College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, Peoples Republic of China

Yi Zhao State Key Laboratory for Physical Chemistry of Solid Surfaces, iChEM, Fujian Provincial Key Lab of Theoretical and Computational Chemistry, and College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, Peoples Republic of China

About the editor

Takashiro Akitsu is a full professor of chemistry at Tokyo University of Science. He completed his undergraduate school training (chemistry) at Osaka University, Japan and his graduate school training (physical and inorganic chemistry, especially coordination, crystal, and bioinorganic chemistry) at Osaka University (PhD 2000). Following positions at Keio University, Japan, and Stanford University, United States, he moved to his current affiliation in 2008. He has published almost 220 articles in peer-reviewed journals and has presented multiple posters at international exhibitions. Prof. Akitsu has been a peer reviewer of many journals and acted as an organizing committee of several international conferences.

Preface

With the practical application of the third-generation artificial intelligence (AI), the possibility of computational chemistry and chemical researches based on databases are increasing gradually. In a recent decade, indeed, with the development of AI, applications of data sciences for chemistry or materials science including drug design have been reported more and more. In this book, the editor is aiming at editing review chapters mentioning each field (computational, theoretical, and analytical chemistry; database; crystallography; spectroscopy) of recent works from chemistry and informatics aspects including tutorial explanation. Beyond conventional computational chemistry or use of databases, this area is a newly developed field and there are few books summarizing new studies or tutorial information at present. This book may be recommended to graduate students and upper researchers of chemistry, because this area is a newly developed field and there may be few competitors or challengers to use such methods so far. To tell the truth, the editor himself is interested in using it for chemistry, but he is not an expert. Therefore, the editor examined the possibility of using a new method in comparison with his conventional chemistry research style of searching suitable compounds (especially with the help of crystal structure databases and computational chemistry). Ideal goal that I think now is improving conventional (empirical) chemical researches to find the law inductively from systematic data, searching for compounds with desired structures and functions from systematic experiments, and narrowing down candidate compounds by prediction by databases and computational chemistry. While reviewing the style and past research of the authors, one will be introduced to examples of research on AI utilization that may be applicable. While learning about this new style of chemistry research and how it compares with an experiment-centered style, readers will also be provided with low-threshold chemical content and topics, with points of particular interest noted.