title: Structure-based quantitative structure--activity relationship modeling of estrogen receptor β-ligands.
abstract: BACKGROUND
  A variety of chemotypes have been studied as estrogen receptor (ER) β-selective ligands for potential drugs against various indications, including neurodegenerative diseases. Their structure--activity relationship data and the x-ray structures of the ERβ ligand-binding domain bound with different ligands have become available. Thus, it is vitally important for future development of ERβ-selective ligands that robust quantitative structure-activity relationship (QSAR) models be built.
  
  
  RESULTS
  We employed a newly developed structure--based QSAR method (structure-based pharmacophore keys QSAR) that utilizes both the structure--activity relationship data and the 3D structural information of ERβ, as well as a robust QSAR workflow to analyze 37 ligands. Four sets of QSAR models were obtained, among which approximately 30 models afforded high (>0.60) training-r(2) and test set-R(2) statistics.
  
  
  CONCLUSIONS
  We have obtained an ensemble of predictive models of ERβ ligands that will be useful in the future discovery of novel ERβ-selective molecules.
authors.affiliation: Department of Pharmaceutical Sciences, College of Science & Technology and BRITE Institute, North Carolina Central University, Durham, NC 27707, USA.
authors.forename: Xialan
authors.initials: X
authors.lastname: Dong
authors.forename: Solomon G
authors.initials: SG
authors.lastname: Hilliard
authors.forename: Weifan
authors.initials: W
authors.lastname: Zheng
mesh_terms: D001665:Binding Sites; D015195:Drug Design; D047629:Estrogen Receptor beta / Q000737:chemistry / Q000378:metabolism*; D006801:Humans; D008024:Ligands; D008954:Models, Biological; D008958:Models, Molecular; D004364:Pharmaceutical Preparations / Q000737:chemistry*; D011485:Protein Binding; D021281:Quantitative Structure-Activity Relationship
chemical_list: D047629:Estrogen Receptor beta; D008024:Ligands; D004364:Pharmaceutical Preparations