Artificial Intelligence in Chemistry: Current Trends and Future Directions.

The application of artificial intelligence (AI) to chemistry has grown tremendously in recent years. In this Review, we studied the growth and distribution of AI-related chemistry publications in the last two decades using the CAS Content Collection. The volume of both journal and patent publications have increased dramatically, especially since 2015. Study of the distribution of publications over various chemistry research areas revealed that analytical chemistry and biochemistry are integrating AI to the greatest extent and with the highest growth rates. We also investigated trends in interdisciplinary research and identified frequently occurring combinations of research areas in publications. Furthermore, topic analyses were conducted for journal and patent publications to illustrate emerging associations of AI with certain chemistry research topics. Notable publications in various chemistry disciplines were then evaluated and presented to highlight emerging use cases. Finally, the occurrence of different classes of substances and their roles in AI-related chemistry research were quantified, further detailing the popularity of AI adoption in the life sciences and analytical chemistry. In summary, this Review offers a broad overview of how AI has progressed in various fields of chemistry and aims to provide an understanding of its future directions.

Recent Changes in the Scaffold Diversity of Organic Chemistry As Seen in the CAS Registry.

A large set of organic compounds extracted from the CAS Registry is analyzed to study recent changes in structural diversity. The diversity is characterized using the framework content of the compounds; the framework of a molecule is the scaffold consisting of all its ring systems and all the chain fragments connecting them. The compounds are partitioned based on their year of first report in the literature, which allows framework occurrence frequencies to be compared across a 10-year interval. The results are consistent with a process in which frameworks with the greatest frequency of use in the past are the most likely to be used again, but it is also found that the frequency ordering changes over time. These fluctuations in ordering are attributed to stochastic factors, scientific and economic, that can affect how chemical space is explored. Framework diversity is found to have increased over time despite the extensive reuse of a relatively small number of frameworks; this increase is due to the large number of new frameworks. The long tail of the framework distribution, composed of frameworks that occur in few compounds or only one compound, is found to be a large and growing part of framework space.