Computational and Data Science
The Computational and Data Science team conducts research into state-of-the-art computational chemistry, drives industry-defining, data-based insights, and integrates relevant tools into the CCDC suite.
Fragment Hotspot Mapping to Identify Selectivity-Determining Regions between Related Proteins
Mihaela D. Smilova, Peter R. Curran, Chris J. Radoux, Frank von Delft, Jason C. Cole, Anthony R. Bradley, Brian D. Marsden
Conformational Change in Molecular Crystals: Impact of solvate formation and importance of conformational free energies.
Wright, Sarah; Cole, Jason; Cruz-Cabeza, Aurora
Mechanistic insight into the fluorescence activity of forensic fingerprinting reagents
L. M. Hunnisett, P. F. Kelly, S. Bleay, F. Plasser, R. King, B. McMurchie, and P. Goddard
Automated In-Silico Energy Mapping of Facet Specific Inter-Particle Interactions
Alexandru A. Moldovan, Radoslav Penchev, Robert B. Hammond, Jakub Janowiak, Thomas Hardcastle, Andrew Maloney, Simon Connell
Augmenting structure-based design with experimental protein-ligand interaction data: molecular recognition, interactive visualization and rescoring
Andreas Tosstorff, Bernd Kuhn, Jason C. Cole, Robin Taylor
Validation of a field-based ligand screener using a novel benchmarking data set for assessing 3D-based virtual screening methods.
Ilenia Giangreco, Abhik Mukhopadhyay and Jason C. Cole