Machine Learning-Guided Synthesis of Clovane Sesquiterpenoids

An organic chemistry minilecture on ’A neural network model informs the total synthesis of clovane sesquiterpenoids’ by Pengpeng Zhang, Jungmin Eun, Masha Elkin, Yizhou Zhao, Rachel L. Cantrell & Timothy R. Newhouse*. It demonstrates the development of a machine learning approach that uses a neural network model to evaluate retrosyntheses and predict the outcome of radical cyclisations. This is applied to the synthesis of a range of clovane sesquiterpenoids, including the first total synthesis and structural revision of Canangaterpene II. Baldwins/Beckwiths Rules: SUPPORT THE CHANNEL ON PATREON: Socials: References:  Nat. Synth (2023). (This work) Chem. Rev. 117, 6110–6159 (2017) (Clovane terpenoid review) Nat. Rev. Chem. 5, 240–255 (2021) (Machine Learning in synthesis review) Chem. Eur. J. 2011, 17, 8404 – 8413 (Hydrosilylation) J. Nat. Prod. 77, 990–999 (2014) (Canangaterpene II)