In silico modeling of brain receptors for antidepressants, psychostimulants and other CNS-active drugs

Brain receptors for drug classes including antidepressants, antipsychotics, psychostimulants, opiates and anticonvulsants are typically embedded in the lipid bilayer of the cell membrane. For decades, the dearth of precise structural information on CNS receptors hindered development of new medications. Such integral membrane proteins have been notoriously difficult to crystallize in situ, and alternatively extracting the proteins from the membrane before crystallization renders a physiologically irrelevant drug target. Breakthroughs in the last decade have yielded high-resolution x-ray crystal data for G protein-coupled receptors, ligand-gated ion channels and neurotransmitter transporter proteins, often co-crystallized with the drug molecule. These structures finally provide credible templates on which to build computational models of these drug receptors and their ligand binding sites. The in silico receptor models can be used to predict or identify intermolecular drug-receptor interactions. If the location of a ligand binding site has been mapped, the receptor model can be used for virtual screening (VS) of structural libraries containing millions of small molecule compounds to find new ligands, many of which would never have been found using a conventional structure-activity relationship approach. VS may provide that “needle in a haystack” lead compound that would otherwise take considerable time and money to find with in vitro pharmacologic high-throughput screens. In this way, computational models allow academic laboratories and similar small-budget enterprises to participate in drug discovery. Additionally, atomistic and coarse-grained molecular dynamics simulations allow investigation of scenarios for conformational changes during receptor activation, ion movement through a membrane channel, or the transporter protein conformations involved in moving a substrate across a biological membrane. The articles in this issue reflect the cutting edge of in silico approaches for understanding brain receptor mechanisms of action, orientation of ligands within the receptor, and high-throughput virtual screening for novel lead compound therapeutics.