Artificial Intelligence in Drug Design von Hessler, Gerhard, Baringhaus, Karl-Heinz

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Optimizing interactions to protein binding sites by integrating docking-scoring strategies into generative AI methods von Sauer, Susanne, Matter, Hans, Hessler, Gerhard, Grebner, Christoph

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Development of in silico filters to predict activation of the pregnane X receptor (PXR) by structurally diverse drug-like molecules von Matter, Hans, Anger, Lennart T., Giegerich, Clemens, Güssregen, Stefan, Hessler, Gerhard, Baringhaus, Karl-Heinz

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A Combination of Spin Diffusion Methods for the Determination of Protein-Ligand Complex Structural Ensembles von Pilger, Jens, Mazur, Adam, Monecke, Peter, Schreuder, Herman, Elshorst, Bettina, Bartoschek, Stefan, Langer, Thomas, Schiffer, Alexander, Krimm, Isabelle, Wegstroth, Melanie, Lee, Donghan, Hessler, Gerhard, Wendt, K.-Ulrich, Becker, Stefan, Griesinger, Christian

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Artificial Intelligence in Compound Design von Grebner, Christoph, Matter, Hans, Hessler, Gerhard

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Introduction to the themed collection on 'AI in Medicinal Chemistry' von Zhang, Jian, Engkvist, Ola, Hessler, Gerhard

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Integrating Reaction Schemes, Reagent Databases, and Virtual Libraries into Fragment-Based Design by Reinforcement Learning von Sauer, Susanne, Matter, Hans, Hessler, Gerhard, Grebner, Christoph

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Impact of Different Automated Binding Pose Generation Approaches on Relative Binding Free Energy Simulations von Cappel, Daniel, Jerome, Steven, Hessler, Gerhard, Matter, Hans

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Automated De Novo Design in Medicinal Chemistry: Which Types of Chemistry Does a Generative Neural Network Learn? von Grebner, Christoph, Matter, Hans, Plowright, Alleyn T, Hessler, Gerhard

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Modern machine‐learning for binding affinity estimation of protein–ligand complexes: Progress, opportunities, and challenges von Harren, Tobias, Gutermuth, Torben, Grebner, Christoph, Hessler, Gerhard, Rarey, Matthias

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Synthesis and Conformational Analysis of Linear and Cyclic Peptides Containing Sugar Amino Acids von Graf von Roedern, Erich, Lohof, Elisabeth, Hessler, Gerhard, Hoffmann, Matthias, Kessler, Horst

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The PROTACtable genome von Schneider, Melanie, Radoux, Chris J., Hercules, Andrew, Ochoa, David, Dunham, Ian, Zalmas, Lykourgos-Panagiotis, Hessler, Gerhard, Ruf, Sven, Shanmugasundaram, Veerabahu, Hann, Michael M., Thomas, Pam J., Queisser, Markus A., Benowitz, Andrew B., Brown, Kris, Leach, Andrew R.

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Interpretation of Structure–Activity Relationships in Real-World Drug Design Data Sets Using Explainable Artificial Intelligence von Harren, Tobias, Matter, Hans, Hessler, Gerhard, Rarey, Matthias, Grebner, Christoph

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Application of Deep Neural Network Models in Drug Discovery Programs von Grebner, Christoph, Matter, Hans, Kofink, Daniel, Wenzel, Jan, Schmidt, Friedemann, Hessler, Gerhard

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Drug Design Strategies for Targeting G-Protein-Coupled Receptors von Klabunde, Thomas, Hessler, Gerhard

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Automated Design of Macrocycles for Therapeutic Applications: From Small Molecules to Peptides and Proteins von Sindhikara, Dan, Wagner, Michael, Gkeka, Paraskevi, Güssregen, Stefan, Tiwari, Garima, Hessler, Gerhard, Yapici, Engin, Li, Ziyu, Evers, Andreas

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Using Graph Databases to Investigate Trends in Structure–Activity Relationship Networks von Matter, Hans, Buning, Christian, Stefanescu, Dan Dragos, Ruf, Sven, Hessler, Gerhard

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Task‐Similarity is a Crucial Factor for Few‐Shot Meta‐Learning of Structure‐Activity Relationships von Kötter, Alex, Allenspach, Stephan, Grebner, Christoph, Matter, Hans, Hiss, Jan A., Schneider, Gisbert, Hessler, Gerhard

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We are MedChem: The Frontiers in Medicinal Chemistry 2024 von Schiedel, Matthias, Barbie, Philipp, Pape, Felix, Pinto, Marta, Unzue Lopez, Andrea, Méndez, María, Hessler, Gerhard, Merk, Daniel, Gehringer, Matthias, Lamers, Christina

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Virtual Screening of Biogenic Amine-Binding G-Protein Coupled Receptors:  Comparative Evaluation of Protein- and Ligand-Based Virtual Screening Protocols von Evers, Andreas, Hessler, Gerhard, Matter, Hans, Klabunde, Thomas

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