title: Molecular interaction fingerprint approaches for GPCR drug discovery.
abstract: Protein-ligand interaction fingerprints (IFPs) are binary 1D representations of the 3D structure of protein-ligand complexes encoding the presence or absence of specific interactions between the binding pocket amino acids and the ligand. Various implementations of IFPs have been developed and successfully applied for post-processing molecular docking results for G Protein-Coupled Receptor (GPCR) ligand binding mode prediction and virtual ligand screening. Novel interaction fingerprint methods enable structural chemogenomics and polypharmacology predictions by complementing the increasing amount of GPCR structural data. Machine learning methods are increasingly used to derive relationships between bioactivity data and fingerprint descriptors of chemical and structural information of binding sites, ligands, and protein-ligand interactions. Factors that influence the application of IFPs include structure preparation, binding site definition, fingerprint similarity assessment, and data processing and these factors pose challenges as well possibilities to optimize interaction fingerprint methods for GPCR drug discovery.
authors.affiliation: Division of Medicinal Chemistry, Faculty of Sciences, Amsterdam Institute for Molecules, Medicines and Systems, Vrije Universiteit Amsterdam, De Boelelaan 1108, 1081 HZ Amsterdam, The Netherlands.
authors.forename: Márton
authors.initials: M
authors.lastname: Vass
authors.affiliation: Division of Medicinal Chemistry, Faculty of Sciences, Amsterdam Institute for Molecules, Medicines and Systems, Vrije Universiteit Amsterdam, De Boelelaan 1108, 1081 HZ Amsterdam, The Netherlands; Centre for Molecular and Biomolecular Informatics (CMBI), Radboud University Medical Center, Geert Grooteplein-Zuid 26-28, 6525 GA Nijmegen, The Netherlands.
authors.forename: Albert J
authors.initials: AJ
authors.lastname: Kooistra
authors.affiliation: Division of Medicinal Chemistry, Faculty of Sciences, Amsterdam Institute for Molecules, Medicines and Systems, Vrije Universiteit Amsterdam, De Boelelaan 1108, 1081 HZ Amsterdam, The Netherlands; Centre for Molecular and Biomolecular Informatics (CMBI), Radboud University Medical Center, Geert Grooteplein-Zuid 26-28, 6525 GA Nijmegen, The Netherlands.
authors.forename: Tina
authors.initials: T
authors.lastname: Ritschel
authors.affiliation: Division of Medicinal Chemistry, Faculty of Sciences, Amsterdam Institute for Molecules, Medicines and Systems, Vrije Universiteit Amsterdam, De Boelelaan 1108, 1081 HZ Amsterdam, The Netherlands.
authors.forename: Rob
authors.initials: R
authors.lastname: Leurs
authors.affiliation: Division of Medicinal Chemistry, Faculty of Sciences, Amsterdam Institute for Molecules, Medicines and Systems, Vrije Universiteit Amsterdam, De Boelelaan 1108, 1081 HZ Amsterdam, The Netherlands.
authors.forename: Iwan Jp
authors.initials: IJ
authors.lastname: de Esch
authors.affiliation: Division of Medicinal Chemistry, Faculty of Sciences, Amsterdam Institute for Molecules, Medicines and Systems, Vrije Universiteit Amsterdam, De Boelelaan 1108, 1081 HZ Amsterdam, The Netherlands. Electronic address: c.de.graaf@vu.nl.
authors.forename: Chris
authors.initials: C
authors.lastname: de Graaf
mesh_terms: D001665:Binding Sites; D055808:Drug Discovery / Q000379:methods*; D006801:Humans; D008024:Ligands; D000069550:Machine Learning; D062105:Molecular Docking Simulation; D004364:Pharmaceutical Preparations / Q000378:metabolism; D011485:Protein Binding; D043562:Receptors, G-Protein-Coupled / Q000737:chemistry / Q000378:metabolism*
chemical_list: D008024:Ligands; D004364:Pharmaceutical Preparations; D043562:Receptors, G-Protein-Coupled