Electron Density Fingerprints (EDprints): Virtual Screening Using Assembled Information of Electron Density. - Albert J. Kooistra; Thomas W. Binsl; Johannes H. G. M. van Beek; Chris de Graaf; Jaap Heringa (J. Chem. Inf. Model., 2010)

Snooker: A Structure-Based Pharmacophore Generation Tool Applied to Class A GPCRs. - Marijn P. A. Sanders; Stefan Verhoeven; Chris de Graaf; Luc Roumen; Bas Vroling; Sander B. Nabuurs; Jacob de Vlieg; Jan P. G. Klomp (J. Chem. Inf. Model., 2011)

Virtual Fragment Screening: Discovery of Histamine H3 Receptor Ligands Using Ligand-Based and Protein-Based Molecular Fingerprints. - Francesco Sirci; Enade P. Istyastono; Henry F. Vischer; Albert J. Kooistra; Saskia Nijmeijer; Martien Kuijer; Maikel Wijtmans; Raimund Mannhold; Rob Leurs; Iwan J. P. de Esch; Chris de Graaf (J. Chem. Inf. Model., 2012)

Structure-Based Prediction of G-Protein-Coupled Receptor Ligand Function: A β-Adrenoceptor Case Study. - Albert J. Kooistra; Rob Leurs; Iwan J. P. de Esch; Chris de Graaf (J. Chem. Inf. Model., 2015)

Analyzing Multitarget Activity Landscapes Using Protein-Ligand Interaction Fingerprints: Interaction Cliffs. - Oscar Méndez-Lucio; Albert J. Kooistra; Chris de Graaf; Andreas Bender 002; José L. Medina-Franco (J. Chem. Inf. Model., 2015)

Combinatorial Consensus Scoring for Ligand-Based Virtual Fragment Screening: A Comparative Case Study for Serotonin 5-HT3A, Histamine H1, and Histamine H4 Receptors. - Sabine Schultes; Albert J. Kooistra; Henry F. Vischer; Saskia Nijmeijer; Eric E. J. Haaksma; Rob Leurs; Iwan J. P. de Esch; Chris de Graaf (J. Chem. Inf. Model., 2015)

KLIFS: a structural kinase-ligand interaction database. - Albert J. Kooistra; Georgi K. Kanev; Oscar P. J. van Linden; Rob Leurs; Iwan J. P. de Esch; Chris de Graaf (Nucleic Acids Res., 2016)

3D-e-Chem-VM: Structural Cheminformatics Research Infrastructure in a Freely Available Virtual Machine. - Ross McGuire; Stefan Verhoeven; Márton Vass; Gerrit Vriend; Iwan J. P. de Esch; Scott J. Lusher; Rob Leurs; Lars Ridder; Albert J. Kooistra; Tina Ritschel; Chris de Graaf (J. Chem. Inf. Model., 2017)

Understanding Ligand Binding Selectivity in a Prototypical GPCR Family. - Giulio Mattedi; Francesca Deflorian; Jonathan S. Mason; Chris de Graaf; Francesco L. Gervasio (J. Chem. Inf. Model., 2019)

Accurate Prediction of GPCR Ligand Binding Affinity with Free Energy Perturbation. - Francesca Deflorian; Laura Pérez-Benito; Eelke B. Lenselink; Miles Congreve; Herman W. T. van Vlijmen; Jonathan S. Mason; Chris de Graaf; Gary Tresadern (J. Chem. Inf. Model., 2020)

Comparison of structure- and ligand-based scoring functions for deep generative models: a GPCR case study. - Morgan C. Thomas; Robert T. Smith; Noel M. O'Boyle; Chris de Graaf; Andreas Bender 002 (J. Cheminformatics, 2021)

KLIFS: an overhaul after the first 5 years of supporting kinase research. - Georgi K. Kanev; Chris de Graaf; Bart A. Westerman; Iwan J. P. de Esch; Albert J. Kooistra (Nucleic Acids Res., 2021)

Re-evaluating sample efficiency in de novo molecule generation. - Morgan C. Thomas; Noel M. O'Boyle; Andreas Bender 002; Chris de Graaf (CoRR, 2022)

Augmented Hill-Climb increases reinforcement learning efficiency for language-based de novo molecule generation. - Morgan C. Thomas; Noel M. O'Boyle; Andreas Bender 002; Chris de Graaf (J. Cheminformatics, 2022)

Classification Model for the Second Extracellular Loop of Class A GPCRs. - Alessandro Nicoli; Andreas Dunkel; Toni Giorgino; Chris de Graaf; Antonella Di Pizio (J. Chem. Inf. Model., 2022)

Predicting the target landscape of kinase inhibitors using 3D convolutional neural networks. - Georgi K. Kanev; Yaran Zhang; Albert J. Kooistra; Andreas Bender 002; Rob Leurs; David Bailey; Thomas Würdinger; Chris de Graaf; Iwan J. P. de Esch; Bart A. Westerman (PLoS Comput. Biol., 2023)

Comparative Study of Allosteric GPCR Binding Sites and Their Ligandability Potential. - Sonja Peter; Lydia Siragusa; Morgan Thomas; Tommaso Palomba; Simon Cross; Noel M. O'Boyle; Dávid Bajusz; György G. Ferenczy; György M. Keserü; Giovanni Bottegoni; Brian Joseph Bender; I-Jen Chen; et al. (J. Chem. Inf. Model., 2024)

MolScore: a scoring, evaluation and benchmarking framework for generative models in de novo drug design. - Morgan C. Thomas; Noel M. O'Boyle; Andreas Bender 002; Chris de Graaf (J. Cheminformatics, 2024)