title: Computational neuropharmacology: dynamical approaches in drug discovery.
abstract: Computational approaches that adopt dynamical models are widely accepted in basic and clinical neuroscience research as indispensable tools with which to understand normal and pathological neuronal mechanisms. Although computer-aided techniques have been used in pharmaceutical research (e.g. in structure- and ligand-based drug design), the power of dynamical models has not yet been exploited in drug discovery. We suggest that dynamical system theory and computational neuroscience--integrated with well-established, conventional molecular and electrophysiological methods--offer a broad perspective in drug discovery and in the search for novel targets and strategies for the treatment of neurological and psychiatric diseases.
authors.affiliation: Department of Physiology, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA.
authors.forename: Ildiko
authors.initials: I
authors.lastname: Aradi
authors.forename: Péter
authors.initials: P
authors.lastname: Erdi
mesh_terms: D014151:Anti-Anxiety Agents / Q000627:therapeutic use; D001927:Brain Diseases / Q000188:drug therapy; D002626:Chemistry, Pharmaceutical; D003198:Computer Simulation; D004594:Electrophysiology / Q000639:trends*; D006801:Humans; D009480:Neuropharmacology / Q000639:trends*
chemical_list: D014151:Anti-Anxiety Agents