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Annual Review of Biomedical Data Science

Volume 5, 2022

Machine Learning in Chemoinformatics and Medicinal Chemistry

Abstract

In chemoinformatics and medicinal chemistry, machine learning has evolved into an important approach. In recent years, increasing computational resources and new deep learning algorithms have put machine learning onto a new level, addressing previously unmet challenges in pharmaceutical research. In silico approaches for compound activity predictions, de novo design, and reaction modeling have been further advanced by new algorithmic developments and the emergence of big data in the field. Herein, novel applications of machine learning and deep learning in chemoinformatics and medicinal chemistry are reviewed. Opportunities and challenges for new methods and applications are discussed, placing emphasis on proper baseline comparisons, robust validation methodologies, and new applicability domains.

Keyword(s): chemoinformatics, data structures, deep learning, learning strategies, machine learning, medicinal chemistry
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/content/journals/10.1146/annurev-biodatasci-122120-124216
2022-08-10
2024-04-19
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/content/journals/10.1146/annurev-biodatasci-122120-124216
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Machine Learning in Chemoinformatics and Medicinal Chemistry
Annual Review of Biomedical Data Science 5, 43 (2022); https://doi.org/10.1146/annurev-biodatasci-122120-124216
/content/journals/10.1146/annurev-biodatasci-122120-124216
/content/journals/10.1146/annurev-biodatasci-122120-124216
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  • Article Type: Review Article

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