title: New design strategies for antidepressant drugs.
abstract: BACKGROUND
  In spite of research efforts spanning six decades, the most prominent antidepressant drugs to date still carry several adverse effects, often serious enough to warrant discontinuation of the drug. Molecular mechanisms of depression are now better understood such that some of the specific receptors responsible can be targeted for activation or inhibition. This advance, coupled with the recent availability of crystal structures of relevant drug targets or their homologs, has opened the door for new antidepressant therapeutic compounds.
  
  
  METHODS
  The authors review the evolution of monoamine-based antidepressant drugs, up to the selective serotonin reuptake inhibitors (SSRIs). The authors discuss classic and contemporary antidepressant drug design strategies, with a focus on virtual screening and fragment-based drug design methods. Furthermore, they discuss the recent advancements in the understanding of the serotonin transporter (SERT) structure/function relationship in the context of recognition of SSRIs and outline a strategy for the use of computational approaches in producing new SSRI lead compounds.
  
  
  CONCLUSIONS
  The authors suggest that given the long-awaited availability of credible three-dimensional structures for the SERT and related monoamine transporter proteins, cutting-edge computational methods should be the linchpin of future drug discovery efforts regarding monoamine-based antidepressant lead compounds. Because these transporter inhibitors cause a ubiquitous increase in extraneuronal neurotransmitter levels leading to side and adverse therapeutic effects, the drug discovery should extend to appropriate manipulation of the 'downstream' receptors affected by the neurotransmitter boost. Efficient use of new computational strategies will accelerate the drug discovery process and reduce its economic burden.
authors.affiliation: Duquesne University, Center for Computational Sciences, Department of Chemistry and Biochemistry , 600 Forbes Ave, 308 Mellon Hall, Pittsburgh, PA 15282 , USA +1 412 396 4129 ; +1 412 396 5683 ; madura@duq.edu.
authors.forename: Kalyan
authors.initials: K
authors.lastname: Immadisetty
authors.forename: Laura M
authors.initials: LM
authors.lastname: Geffert
authors.forename: Christopher K
authors.initials: CK
authors.lastname: Surratt
authors.forename: Jeffry D
authors.initials: JD
authors.lastname: Madura
mesh_terms: D000818:Animals; D000928:Antidepressive Agents / Q000737:chemistry* / Q000494:pharmacology / Q000627:therapeutic use; D017076:Computer-Aided Design; D015195:Drug Design; D006801:Humans; D015394:Molecular Structure; D017367:Selective Serotonin Reuptake Inhibitors / Q000737:chemistry* / Q000494:pharmacology / Q000627:therapeutic use; D013329:Structure-Activity Relationship; D050493:Vesicular Monoamine Transport Proteins / Q000037:antagonists & inhibitors
chemical_list: D000928:Antidepressive Agents; D017367:Selective Serotonin Reuptake Inhibitors; D050493:Vesicular Monoamine Transport Proteins