title: In silico-aided prediction of biological properties of chemicals: oestrogen receptor-mediated effects.
abstract: In silico methods are a valid tool for analysing the properties of chemical compounds and interest in computational modelling techniques to predict the activity of chemicals is constantly growing. Many computational methods can be used to analyse the toxicity or biological activity of chemicals, particularly as regards their interactions with biological macromolecules (e.g. receptors) and other physico-chemical properties. An overview of these methods is provided in this tutorial review, with some examples of their application to predict oestrogen receptor (ER)-mediated effects. Nuclear receptors, particularly ER, have been studied with in silico tools since concern is growing about substances, called endocrine disrupters, that can interfere with hormone regulation. Molecular modelling techniques such as Quantitative Structure-Activity Relationships (QSAR), related methods like 3D-QSAR, and virtual docking have been used to investigate these phenomena and are described here. Implications about regulatory acceptance and use of these methods and the resulting models for identifying hazards and setting priorities are also addressed.
authors.affiliation: Laboratory of Environmental Toxicology and Chemistry, Istituto di Ricerche Farmacologiche Mario Negri, via La Masa 19, Milan, Italy. aroncaglioni@marionegri.it
authors.forename: Alessandra
authors.initials: A
authors.lastname: Roncaglioni
authors.forename: Emilio
authors.initials: E
authors.lastname: Benfenati
mesh_terms: D000826:Animal Testing Alternatives; D000818:Animals; D019295:Computational Biology; D003198:Computer Simulation; D004353:Drug Evaluation, Preclinical; D005260:Female; D006801:Humans; D021281:Quantitative Structure-Activity Relationship; D011960:Receptors, Estrogen / Q000737:chemistry / Q000187:drug effects*
chemical_list: D011960:Receptors, Estrogen