C. Grebner

发表

Automated De-Novo Design in Medicinal Chemistry: Which Types of Chemistry Does a Generative Neural Network Learn?

C. Grebner, H. Matter, A. Plowright, 2020, Journal of medicinal chemistry.

Enhancing backbone sampling in Monte Carlo simulations using internal coordinates normal mode analysis.

C. Grebner, V. Guallar, V. Gil, 2016, Bioorganic & medicinal chemistry.

Ligand Binding Mechanism in Steroid Receptors: From Conserved Plasticity to Differential Evolutionary Constraints.

Victor Guallar, Christoph Grebner, Karl Edman, 2015, Structure.

Exploring Binding Mechanisms in Nuclear Hormone Receptors by Monte Carlo and X-ray-derived Motions.

Victor Guallar, Christian Tyrchan, Christoph Grebner, 2017, Biophysical journal.

QM/MM investigations of organic chemistry oriented questions.

C. Grebner, B. Engels, Kay Ansorg, 2014, Topics in current chemistry.

Optimizing interactions to protein binding sites by integrating docking-scoring strategies into generative AI methods

C. Grebner, H. Matter, G. Hessler, 2022, Frontiers in Chemistry.

Structural insight into allosteric modulation of protease-activated receptor 2

Patrik Johansson, Ali Jazayeri, Christoph Grebner, 2017, Nature.

A New Tabu-Search-Based Algorithm for Solvation of Proteins.

Walter Thiel, Bernd Engels, Johannes Kästner, 2013, Journal of chemical theory and computation.

Force field-based conformational searches: efficiency and performance for peptide receptor complexes

Christoph Grebner, Bernd Engels, Sebastian Schlücker, 2013 .

Computational Approaches for Target Inference

C. Grebner, G. Hessler, Hans Matter, 2019, Methods and Principles in Medicinal Chemistry.

CAST: A new program package for the accurate characterization of large and flexible molecular systems

Christoph Grebner, Daniel Weber, Johannes Becker, 2014, J. Comput. Chem..

Virtual Screening in the Cloud: How Big Is Big Enough?

Jens Sadowski, Christoph Grebner, Anthony Nicholls, 2020, J. Chem. Inf. Model..

Interpretation of Structure-Activity Relationships in Real-World Drug Design Data Sets Using Explainable Artificial Intelligence

C. Grebner, H. Matter, G. Hessler, 2022, J. Chem. Inf. Model..

Efficiency of tabu‐search‐based conformational search algorithms

Christoph Grebner, Bernd Engels, Svetlana Stepanenko, 2011, J. Comput. Chem..

Artificial Intelligence in Compound Design.

C. Grebner, H. Matter, G. Hessler, 2021, Methods in molecular biology.

Molecular Rift: Virtual Reality for Drug Designers

Jonas Boström, Joakim Eriksson, Magnus Norrby, 2015, J. Chem. Inf. Model..

PELE-MSM: a Monte Carlo based protocol for the estimation of absolute binding free energies.

Victor Guallar, Robert Soliva, Christian Tyrchan, 2019, Journal of chemical theory and computation.

Application of Deep Neural Network Models in Drug Discovery Programs

C. Grebner, H. Matter, G. Hessler, 2021, ChemMedChem.

11th German Conference on Chemoinformatics (GCC 2015)

Timothy Clark, Jonathan W. Essex, Peter Kolb, 2016, J. Cheminformatics.

Binding Mode and Induced Fit Predictions for Prospective Computational Drug Design

Christian Tyrchan, Christoph Grebner, Anders Hogner, 2016, J. Chem. Inf. Model..

Impact of Applicability Domains to Generative Artificial Intelligence

C. Grebner, H. Matter, Maxime Langevin, 2023, ACS omega.

Deep Batch Active Learning for Drug Discovery

Z. Bar-Joseph, C. Grebner, H. Matter, 2023, bioRxiv.

PathOpt—A global transition state search approach: Outline of algorithm

Christoph Grebner, Bernd Engels, Lukas P. Pason, 2013, J. Comput. Chem..

Ligand Binding Mechanism in Steroid Receptors: From Conserved Plasticity to Differential Evolutionary Constraints.

C. Grebner, V. Guallar, Magnus K. Bjursell, 2015, Structure.

Deep Batch Active Learning for Drug Discovery

Z. Bar-Joseph, C. Grebner, H. Matter, 2023, bioRxiv.

Integrating Reaction Schemes, Reagent Databases, and Virtual Libraries into Fragment-Based Design by Reinforcement Learning

C. Grebner, G. Hessler, Susanne Sauer, 2023, J. Chem. Inf. Model..