A molecular graphics study exploring a putative ligand binding site of theβ-adrenoceptor. - Adriaan P. IJzerman; Herman W. T. van Vlijmen (J. Comput. Aided Mol. Des., 1988)

Molecular modeling of a putative antagonist binding site on helix III of the β-adrenoceptor. - Herman W. T. van Vlijmen; Adriaan P. IJzerman (J. Comput. Aided Mol. Des., 1989)

Relative binding orientations of adenosine A1 receptor ligands - A test case for Distributed Multipole Analysis in medicinal chemistry. - Eleonora M. van der Wenden; Sarah L. Price; Robert P. Apaya; Adriaan P. IJzerman; Willem Soudijn (J. Comput. Aided Mol. Des., 1995)

Combining and Comparing Cluster Methods in a Receptor Database. - Elena V. Samsonova; Thomas Bäck; Margot W. Beukers; Adriaan P. IJzerman; Joost N. Kok (IDA, 2003)

Using data mining to improve mutation in a tool for molecular evolution. - Eric-Wubbo Lameijer; Adriaan P. IJzerman; Joost N. Kok (Congress on Evolutionary Computation, 2005)

The molecule evoluator: an interactive evolutionary algorithm for designing drug molecules. - Eric-Wubbo Lameijer; Adriaan P. IJzerman; Joost N. Kok (GECCO, 2005)

Reliable Hierarchical Clustering with the Self-organizing Map. - Elena V. Samsonova; Thomas Bäck; Joost N. Kok; Adriaan P. IJzerman (IDA, 2005)

Evolutionary Algorithms in Drug Design. - Eric-Wubbo Lameijer; Thomas Bäck; Joost N. Kok; Adriaan P. IJzerman (Nat. Comput., 2005)

Substructure Mining Using Elaborate Chemical Representation. - Jeroen Kazius; Siegfried Nijssen; Joost N. Kok; Thomas Bäck; Adriaan P. IJzerman (J. Chem. Inf. Model., 2006)

The Molecule Evoluator. An Interactive Evolutionary Algorithm for the Design of Drug-Like Molecules. - Eric-Wubbo Lameijer; Joost N. Kok; Thomas Bäck; Adriaan P. IJzerman (J. Chem. Inf. Model., 2006)

Mining a Chemical Database for Fragment Co-occurrence: Discovery of "Chemical Clichés". - Eric-Wubbo Lameijer; Joost N. Kok; Thomas Bäck; Adriaan P. IJzerman (J. Chem. Inf. Model., 2006)

TreeSOM: Cluster analysis in the self-organizing map. - Elena V. Samsonova; Joost N. Kok; Adriaan P. IJzerman (Neural Networks, 2006)

An efficient, versatile and scalable pattern growth approach to mine frequent patterns in unaligned protein sequences. - Kai Ye 001; Walter A. Kosters; Adriaan P. IJzerman (Bioinform., 2007)

Evolutionary algorithms for automated drug design towards target molecule properties. - Johannes W. Kruisselbrink; Thomas Bäck; Adriaan P. IJzerman; Eelke van der Horst (GECCO, 2008)

Multi-RELIEF: a method to recognize specificity determining residues from multiple sequence alignments using a Machine-Learning approach for feature weighting. - Kai Ye 001; K. Anton Feenstra; Jaap Heringa; Adriaan P. IJzerman; Elena Marchiori (Bioinform., 2008)

Tracing evolutionary pressure. - Kai Ye 001; Gert Vriend; Adriaan P. IJzerman (Bioinform., 2008)

Combining Aggregation with Pareto Optimization: A Case Study in Evolutionary Molecular Design. - Johannes W. Kruisselbrink; Michael T. M. Emmerich; Thomas Bäck; Andreas Bender 002; Adriaan P. IJzerman; Eelke van der Horst (EMO, 2009)

Enhancing search space diversity in multi-objective evolutionary drug molecule design using niching. - Johannes W. Kruisselbrink; Alexander Aleman; Michael T. M. Emmerich; Adriaan P. IJzerman; Andreas Bender 002; Thomas Bäck; Eelke van der Horst (GECCO, 2009)

Substructure Mining of GPCR Ligands Reveals Activity-Class Specific Functional Groups in an Unbiased Manner. - Eelke van der Horst; Yasushi Okuno; Andreas Bender 002; Adriaan P. IJzerman (J. Chem. Inf. Model., 2009)

Chemogenomics: Looking at biology through the lens of chemistry. - Munikumar R. Doddareddy; Gerard J. P. van Westen; Eelke van der Horst; Julio E. Peironcely; Frans Corthals; Adriaan P. IJzerman; Michael Emmerich 001; Jeremy L. Jenkins; Andreas Bender 002 (Stat. Anal. Data Min., 2009)

A novel chemogenomics analysis of G protein-coupled receptors (GPCRs) and their ligands: a potential strategy for receptor de-orphanization. - Eelke van der Horst; Julio E. Peironcely; Adriaan P. IJzerman; Margot W. Beukers; Jonathan Robert Lane; Herman W. T. van Vlijmen; Michael T. M. Emmerich; Yasushi Okuno; Andreas Bender 002 (BMC Bioinform., 2010)

Evolutionary design of selective adenosine receptor ligands. - Eelke van der Horst; Johannes W. Kruisselbrink; Alexander Aleman; Michael T. M. Emmerich; Andreas Bender 002; Adriaan P. IJzerman (J. Cheminformatics, 2010)

Molecular bioactivity extrapolation to novel targets by support vector machines. - Gerard J. P. van Westen; Jörg K. Wegner; Adriaan P. IJzerman; Herman W. T. van Vlijmen; Andreas Bender 002 (J. Cheminformatics, 2010)

Multi-Objective Evolutionary Design of Adenosine Receptor Ligands. - Eelke van der Horst; Patricia Marqués-Gallego; Thea Mulder-Krieger; Jacobus van Veldhoven; Johannes W. Kruisselbrink; Alexander Aleman; Michael T. M. Emmerich; Johannes Brussee; Andreas Bender 002; Adriaan P. IJzerman (J. Chem. Inf. Model., 2012)

Benchmarking of protein descriptor sets in proteochemometric modeling (part 2): modeling performance of 13 amino acid descriptor sets. - Gerard J. P. van Westen; Remco F. Swier; Isidro Cortes-Ciriano; Jörg K. Wegner; John P. Overington; Adriaan P. IJzerman; Herman W. T. van Vlijmen; Andreas Bender 002 (J. Cheminformatics, 2013)

Benchmarking of protein descriptor sets in proteochemometric modeling (part 1): comparative study of 13 amino acid descriptor sets. - Gerard J. P. van Westen; Remco F. Swier; Jörg K. Wegner; Adriaan P. IJzerman; Herman W. T. van Vlijmen; Andreas Bender 002 (J. Cheminformatics, 2013)

Complementarity between in Silico and Biophysical Screening Approaches in Fragment-Based Lead Discovery against the A2A Adenosine Receptor. - Dan Chen; Anirudh Ranganathan; Adriaan P. IJzerman; Gregg Siegal; Jens Carlsson (J. Chem. Inf. Model., 2013)

Significantly Improved HIV Inhibitor Efficacy Prediction Employing Proteochemometric Models Generated From Antivirogram Data. - Gerard J. P. van Westen; Alwin Hendriks; Jörg K. Wegner; Adriaan P. IJzerman; Herman W. T. van Vlijmen; Andreas Bender 002 (PLoS Comput. Biol., 2013)

How Diverse Are Diversity Assessment Methods? A Comparative Analysis and Benchmarking of Molecular Descriptor Space. - Alexios Koutsoukas; Shardul Paricharak; Warren R. J. D. Galloway; David R. Spring; Adriaan P. IJzerman; Robert C. Glen; David Marcus; Andreas Bender 002 (J. Chem. Inf. Model., 2014)

Selecting an Optimal Number of Binding Site Waters To Improve Virtual Screening Enrichments Against the Adenosine A2A Receptor. - Eelke B. Lenselink; Thijs Beuming; Woody Sherman; Herman W. T. van Vlijmen; Adriaan P. IJzerman (J. Chem. Inf. Model., 2014)

Proteochemometric modelling coupled to in silico target prediction: an integrated approach for the simultaneous prediction of polypharmacology and binding affinity/potency of small molecules. - Shardul Paricharak; Isidro Cortes-Ciriano; Adriaan P. IJzerman; Therese E. Malliavin; Andreas Bender 002 (J. Cheminformatics, 2015)

In search of novel ligands using a structure-based approach: a case study on the adenosine A2A receptor. - Eelke B. Lenselink; Thijs Beuming; Corine van Veen; Arnault Massink; Woody Sherman; Herman W. T. van Vlijmen; Adriaan P. IJzerman (J. Comput. Aided Mol. Des., 2016)

Interacting with GPCRs: Using Interaction Fingerprints for Virtual Screening. - Eelke B. Lenselink; Willem Jespers; Herman W. T. van Vlijmen; Adriaan P. IJzerman; Gerard J. P. van Westen (J. Chem. Inf. Model., 2016)

Data-Driven Derivation of an "Informer Compound Set" for Improved Selection of Active Compounds in High-Throughput Screening. - Shardul Paricharak; Adriaan P. IJzerman; Jeremy L. Jenkins; Andreas Bender 002; Florian Nigsch (J. Chem. Inf. Model., 2016)

Beyond the hype: deep neural networks outperform established methods using a ChEMBL bioactivity benchmark set. - Eelke B. Lenselink; Niels ten Dijke; Brandon J. Bongers; George Papadatos; Herman W. T. van Vlijmen; Wojtek Kowalczyk; Adriaan P. IJzerman; Gerard J. P. van Westen (J. Cheminformatics, 2017)

Data-driven approaches used for compound library design, hit triage and bioactivity modeling in high-throughput screening. - Shardul Paricharak; Oscar Méndez-Lucio; Aakash Chavan Ravindranath; Andreas Bender 002; Adriaan P. IJzerman; Gerard J. P. van Westen (Briefings Bioinform., 2018)

Application of portfolio optimization to drug discovery. - Iryna Yevseyeva; Eelke B. Lenselink; Alice de Vries; Adriaan P. IJzerman; André H. Deutz; Michael T. M. Emmerich (Inf. Sci., 2019)

Identification of novel small molecule inhibitors for solute carrier SGLT1 using proteochemometric modeling. - Lindsey Burggraaff; Paul Oranje; Robin Gouka; Pieter van der Pijl; Marian Geldof; Herman W. T. van Vlijmen; Adriaan P. IJzerman; Gerard J. P. van Westen (J. Cheminformatics, 2019)

An exploration strategy improves the diversity of de novo ligands using deep reinforcement learning: a case for the adenosine A2A receptor. - Xuhan Liu; Kai Ye 001; Herman W. T. van Vlijmen; Adriaan P. IJzerman; Gerard J. P. van Westen (J. Cheminformatics, 2019)

Advances and Challenges in Computational Target Prediction. - Dominique Sydow; Lindsey Burggraaff; Angelika Szengel; Herman W. T. van Vlijmen; Adriaan P. IJzerman; Gerard J. P. van Westen; Andrea Volkamer (J. Chem. Inf. Model., 2019)

Quantitative prediction of selectivity between the A1 and A2A adenosine receptors. - Lindsey Burggraaff; Herman W. T. van Vlijmen; Adriaan P. IJzerman; Gerard J. P. van Westen (J. Cheminformatics, 2020)

Successive Statistical and Structure-Based Modeling to Identify Chemically Novel Kinase Inhibitors. - Lindsey Burggraaff; Eelke B. Lenselink; Willem Jespers; Jesper E. van Engelen; Brandon J. Bongers; Marina Gorostiola González; Rongfang Liu; Holger H. Hoos; Herman W. T. van Vlijmen; Adriaan P. IJzerman; Gerard J. P. van Westen (J. Chem. Inf. Model., 2020)

Annotation of Allosteric Compounds to Enhance Bioactivity Modeling for Class A GPCRs. - Lindsey Burggraaff; Amber van Veen; Chi Chung Lam; Herman W. T. van Vlijmen; Adriaan P. IJzerman; Gerard J. P. van Westen (J. Chem. Inf. Model., 2020)

Computational Approaches for De Novo Drug Design: Past, Present, and Future. - Xuhan Liu; Adriaan P. IJzerman; Gerard J. P. van Westen (Artificial Neural Networks, 3rd Edition, 2021)

DrugEx v2: de novo design of drug molecules by Pareto-based multi-objective reinforcement learning in polypharmacology. - Xuhan Liu; Kai Ye 001; Herman W. T. van Vlijmen; Michael T. M. Emmerich; Adriaan P. IJzerman; Gerard J. P. van Westen (J. Cheminformatics, 2021)

Deciphering conformational selectivity in the A2A adenosine G protein-coupled receptor by free energy simulations. - Willem Jespers; Laura H. Heitman; Adriaan P. IJzerman; Eddy Sotelo; Gerard J. P. van Westen; Johan Åqvist; Hugo Gutiérrez-de-Terán (PLoS Comput. Biol., 2021)

Papyrus: a large-scale curated dataset aimed at bioactivity predictions. - Olivier J. M. Béquignon; Brandon J. Bongers; Willem Jespers; Adriaan P. IJzerman; B. van der Water; Gerard J. P. van Westen (J. Cheminformatics, 2023)

Proteochemometric Modeling Identifies Chemically Diverse Norepinephrine Transporter Inhibitors. - Brandon J. Bongers; Huub J. Sijben; Peter B. R. Hartog; Andrey Tarnovskiy; Adriaan P. IJzerman; Laura H. Heitman; Gerard J. P. van Westen (J. Chem. Inf. Model., 2023)

3DDPDs: describing protein dynamics for proteochemometric bioactivity prediction. A case for (mutant) G protein-coupled receptors. - Marina Gorostiola González; Remco L. van den Broek; Thomas G. M. Braun; Magdalini Chatzopoulou; Willem Jespers; Adriaan P. IJzerman; Laura H. Heitman; Gerard J. P. van Westen (J. Cheminformatics, 2023)

DrugEx v3: scaffold-constrained drug design with graph transformer-based reinforcement learning. - Xuhan Liu; Kai Ye 001; Herman W. T. van Vlijmen; Adriaan P. IJzerman; Gerard J. P. van Westen (J. Cheminformatics, 2023)