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| http://dx.doi.org/10.1183/23120541.01026-2024 | DOI Listing |
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Computational tools for the prediction of site- and regioselectivity of organic reactions.
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Molecular AI, Discovery Sciences, R&D, AstraZeneca Gothenburg Pepparedsleden 1 43183 Mölndal Sweden
The regio- and site-selectivity of organic reactions is one of the most important aspects when it comes to synthesis planning. Due to that, massive research efforts were invested into computational models for regio- and site-selectivity prediction, and the introduction of machine learning to the chemical sciences within the past decade has added a whole new dimension to these endeavors. This review article walks through the currently available predictive tools for regio- and site-selectivity with a particular focus on machine learning models while being organized along the individual reaction classes of organic chemistry.
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