ArticleJournal of the American Chemical Society2023
Hybrid Machine Learning Approach to Predict the Site Selectivity of Iridium-Catalyzed Arene Borylation.
Article in Journal of the American Chemical Society, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
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Who cites it
29 citing papers in PubMed.
- AI-Driven Synthesis in Medicinal Chemistry: Integrating Large Language Models, Robotic Automation, and Sustainability Metrics to Accelerate Drug Discovery.Medicinal research reviews · 2026Review
- Computational data as the fuel for AI in chemistry.Chemical science · 2026Review
- BONAFIDE: a Python framework for the calculation of local features for atoms and bonds in molecules.Journal of cheminformatics · 2026Article
- Transforming Molecular Synthesis With Large Language Models.Chemistry (Weinheim an der Bergstrasse, Germany) · 2026Review
- Interpreting terminal selectivity in undirected C(spChemical science · 2026Review
- Cyclic sulfone ring remodeling enables molecular shape diversity-oriented synthesis of privileged biaryl and oligoaryl motifs.Nature communications · 2026Article
- Expediting hit-to-lead progression in drug discovery through reaction prediction and multi-dimensional optimization.Nature communications · 2025Article
- Predicting reaction conditions: a data-driven perspective.Chemical science · 2025Review
- Molecular Machine Learning Approach to Enantioselective C-H Bond Activation Reactions: From Generative AI to Experimental Validation.Chemical science · 2025Article
- AI Approaches to Homogeneous Catalysis with Transition Metal Complexes.ACS catalysis · 2025Review
- The Importance of Atomic Charges for Predicting Site-Selective Ir-, Ru-, and Rh-Catalyzed C-H Borylations.The Journal of organic chemistry · 2025Article
- A meta-learning approach for selectivity prediction in asymmetric catalysis.Nature communications · 2025Article
- Computational tools for the prediction of site- and regioselectivity of organic reactions.Chemical science · 2025Review
- Controlling the Symmetry of Perylene Derivatives via SelectiveThe Journal of organic chemistry · 2025Article
- Designing Target-specific Data Sets for Regioselectivity Predictions on Complex Substrates.Journal of the American Chemical Society · 2025Article
- Direct (LC-)MS Identification of Regioisomers from C-H Functionalization by Partial Isotopic Labeling.ACS central science · 2025Article
- High-Throughput Enabled Iridium-Catalyzed C-H Borylation Platform for Late-Stage Functionalization.ACS catalysis · 2025Article
- Simple User-Friendly Reaction Format.Molecular informatics · 2025Article
- Data-Driven Insights into the Transition-Metal-Catalyzed Asymmetric Hydrogenation of Olefins.The Journal of organic chemistry · 2024Article
- Geometric deep learning-guided Suzuki reaction conditions assessment for applications in medicinal chemistry.RSC medicinal chemistry · 2024Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
The borylation of aryl and heteroaryl C-H bonds is valuable for the site-selective functionalization of C-H bonds in complex molecules. Iridium catalysts ligated by bipyridine ligands catalyze the borylation of the C-H bond that is most acidic and least sterically hindered in an arene, but predicting the site of borylation in molecules containing multiple arenes is difficult. To address this challenge, we report a hybrid computational model that predicts the Site of Borylation (SoBo) in complex molecules. The SoBo model combines density functional theory, semiempirical quantum mechanics, cheminformatics, linear regression, and machine learning to predict site selectivity and to extrapolate these predictions to new chemical space. Experimental validation of SoBo showed that the model predicts the major site of borylation of pharmaceutical intermediates with higher accuracy than prior machine-learning models or human experts, demonstrating that SoBo will be useful to guide experiments for the borylation of specific C(sp
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Registered trials
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