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RESEARCH PAPER · Communications Chemistry · 2023

Identifying opportunities for late-stage C-H alkylation with high-throughput experimentation and in silico reaction screening

David F. Nippa, Kenneth Atz, Alex T. Müller, Jens Wolfard, Clemens Isert, Martin Binder, Oliver Scheidegger, David Benjamin Konrad, Uwe Grether, Rainer E. Martin, Gisbert Schneider

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16 direct citing papers in this saved network. Explore the next layer with second-order citations.

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42 direct citing works

Identifying opportunities for late-stage C-H alkylation with high-throughput experimentation and in silico reaction screeningOriginalCombining de novo molecular design with semiempirical protein–ligand binding free energy calculation7Exploring protein–ligand binding affinity prediction with electron density-based geometric deep learning26Geometric deep learning-guided Suzuki reaction conditions assessment for applications in medicinal chemistry11Prospective de novo drug design with deep interactome learning96Accelerating compound synthesis in drug discovery: the role of digitalisation and automation4Computational tools for the prediction of site- and regioselectivity of organic reactions33Investigation of arene and heteroarene nitration supported by high-throughput experimentation and machine learning0Standardized Approach for Diversification of Complex Small Molecules via Aryl Thianthrenium Salts48Production and evaluation of high-throughput reaction data from an automated chemical synthesis platform5Multistep Reactions Initiated by Amine‐Based Organometallic Methods1Autonomous Materials Synthesis Laboratories: Integrating Artificial Intelligence with Advanced Robotics for Accelerated Discovery4Late-stage functionalization in drug discovery1Expediting hit-to-lead progression in drug discovery through reaction prediction and multi-dimensional optimization9An overview of reaction outcome prediction with physics-based and data-driven methods2Phosphonium Ions as Activating Groups for the Selective Alkylation of Pyridines and Polyazines2Advancing chemical reaction prediction in data-scarce drug discovery with active and geometric deep learning1

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16 direct citing papers saved.

  1. Combining de novo molecular design with semiempirical protein–ligand binding free energy calculation

    RSC Advances · 2024-01-01

    Michael Iff, Kenneth Atz, Clemens Isert, Irène Pachón-Angona, Leandro Cotos, Mattis Hilleke, Jan A. Hiss, Gisbert Schneider

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  2. Exploring protein–ligand binding affinity prediction with electron density-based geometric deep learning

    RSC Advances · 2024-01-01

    Clemens Isert, Kenneth Atz, Sereina Riniker, Gisbert Schneider

    Read original paper ↗ ·

  3. Geometric deep learning-guided Suzuki reaction conditions assessment for applications in medicinal chemistry

    RSC Medicinal Chemistry · 2024-01-01

    Kenneth Atz, David F. Nippa, Alex T. Müller, Vera Jost, Andrea Anelli, Michael Reutlinger, Christian Krämer, Rainer E. Martin, Uwe Grether, Gisbert Schneider, Georg Wuitschik

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  4. Prospective de novo drug design with deep interactome learning

    Nature Communications · 2024-04-22

    Kenneth Atz, Leandro Cotos, Clemens Isert, M. Håkansson, Dorota Focht, Mattis Hilleke, David F. Nippa, Michael Iff, Jann Ledergerber, Carl C. G. Schiebroek, Valentina Romeo, Jan A. Hiss, Daniel Merk, Petra Schneider, Bernd Kuhn, Uwe Grether, Gisbert Schneider

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  5. Accelerating compound synthesis in drug discovery: the role of digitalisation and automation

    RSC Medicinal Chemistry · 2025-01-01

    David F. Nippa, Alexander J. Boddy, Kenneth Atz, Uwe Grether, Hayley Binch, Rainer E. Martin

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  6. Computational tools for the prediction of site- and regioselectivity of organic reactions

    Chemical Science · 2025-01-01

    Lukas M. Sigmund, Michele Assante, Magnus J. Johansson, Per‐Ola Norrby, Kjell Jorner, Mikhail Kabeshov

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  7. Investigation of arene and heteroarene nitration supported by high-throughput experimentation and machine learning

    Digital Discovery · 2025-01-01

    Taline Kerackian, Clément Wespiser, Matthieu Daniel, Éric Pasquinet, Eugénie Romero

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  8. Standardized Approach for Diversification of Complex Small Molecules via Aryl Thianthrenium Salts

    Journal of the American Chemical Society · 2025-01-22

    Dilgam Ahmadli, Sven Müller, Yuanhao Xie, Tomáš Šmejkal, Simon Jaeckh, Andrei V. Iosub, Simon R. Williams, Tobias Ritter

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  9. Production and evaluation of high-throughput reaction data from an automated chemical synthesis platform

    Science China Chemistry · 2025-05-26

    Leiyun Zhong, Yiming Xu, Xinghai Li, Peihao Cheng, Shengyang Tao

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  10. Multistep Reactions Initiated by Amine‐Based Organometallic Methods

    European Journal of Organic Chemistry · 2025-07-28

    Victoria D. Ho, Olutayo Nathanael Farinde, Kendra K. Shrestha, Michael C. Young

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  11. Autonomous Materials Synthesis Laboratories: Integrating Artificial Intelligence with Advanced Robotics for Accelerated Discovery

    ChemRxiv · 2025-08-04

    Yuze Hao, Lan Duo, Jinlu He

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  12. Late-stage functionalization in drug discovery

    Elsevier eBooks · 2025-10-10

    Daniele Antermite, Erik Weis, Martin A. Hayes, Magnus J. Johansson

    Read original paper ↗ ·

  13. Expediting hit-to-lead progression in drug discovery through reaction prediction and multi-dimensional optimization

    Nature Communications · 2025-11-26

    David F. Nippa, Kenneth Atz, Yannick Stenzhorn, Alex T. Müller, Andreas Tosstorff, Jörg Benz, Hayley Binch, Markus Bürkler, Ahmed Haider, Dominik Heer, Remo Hochstrasser, Christian Krämer, Michael Reutlinger, Petra Schneider, Thierry Shema, Andreas Topp, Alexander Walter, Matthias Wittwer, Jens Wolfard, Bernd Kuhn, Mario van der Stelt, Rainer E. Martin, Uwe Grether, Gisbert Schneider

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  14. An overview of reaction outcome prediction with physics-based and data-driven methods

    Chemical Society Reviews · 2026-01-01

    Joonyoung F. Joung, Nicholas Casetti, Priyanka Raghavan, Connor W. Coley

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  15. Phosphonium Ions as Activating Groups for the Selective Alkylation of Pyridines and Polyazines

    Journal of the American Chemical Society · 2026-06-05

    Dane A. Brunner, David C. Thomas, Kaila R. Steenback, Soren D. Rozema, Andrew McNally

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  16. Advancing chemical reaction prediction in data-scarce drug discovery with active and geometric deep learning

    Nature Computational Science · 2026-10-09

    Mason Minot, Yannick Stenzhorn, Jens Wolfard, Sebastian Strobel, Philippe Jablonski, Daniel Zimmerli, Martin Binder, Uwe Grether, Rainer E. Martin, Alex T. Müller, David F. Nippa, Kenneth Atz, Gisbert Schneider

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