Biological Testing of Organophosphorus-Inactivated Acetylcholinesterase Oxime Reactivators Identified via Virtual Screening.

There is a pressing need for new therapeutics to reactivate covalently inactivated acetylcholinesterase (AChE) due to exposure to organophosphorus (OP) compounds. Current reactivation therapeutics (RTs) are not broad-spectrum and suffer from other liabilities, specifically the inability to cross the blood-brain-barrier. Additionally, the chemical diversity of available therapeutics is small, limiting opportunities for structure-activity relationship (SAR) studies to aid in the design of more effective compounds. In order to find new starting points for the development of oxime-containing therapeutic reactivators and to increase our base of knowledge, we have employed a combination of computational and experimental procedures to identify additional compounds with the real or potential ability to reactivate AChE while augmenting and complementing current knowledge. Computational methods were used to identify previously uninvestigated oxime-containing molecules. Experimentally, six compounds were found with reactivation capabilities comparable to, or exceeding, those of 2-pralidoxime (2-PAM) against a panel of AChE inactivated by paraoxon, diisopropylfluorophosphate (DFP), fenamiphos, and methamidophos. One compound showed enhanced reactivation ability against DFP and fenamiphos, the least tractable of these OPs to be reactivated.

Monoamine transporter structure, function, dynamics, and drug discovery: a computational perspective.

With the breakthrough crystallization of the bacterial leucine transporter protein LeuT, the first available X-ray structure for the neurotransmitter/sodium symporter family, development of 3-D computational models is suddenly essential for structure-function studies on the plasmalemmal monoamine transporters (MATs). LeuT-based MAT models have been used to guide elucidation of substrate and inhibitor binding pockets, and molecular dynamics simulations using these models are providing insight into conformations involved in the substrate translocation cycle. With credible MAT models finally in hand, structure-based virtual screening for novel ligands is yielding lead compounds toward the development of new medications for psychostimulant dependence, attention deficit hyperactivity, depression, anxiety, schizophrenia, and other disorders associated with dopamine, norepinephrine, or serotonin dysregulation.

Identification of a novel selective serotonin reuptake inhibitor by coupling monoamine transporter-based virtual screening and rational molecular hybridization.

Ligand virtual screening (VS) using the vestibular binding pocket of a 3-D monoamine transporter (MAT) computational model followed by in vitro pharmacology led to the identification of a human serotonin transporter (hSERT) inhibitor with modest affinity (hSERT K(i) = 284 nM). Structural comparison of this VS-elucidated compound, denoted MI-17, to known SERT ligands led to the rational design and synthesis of DJLDU-3-79, a molecular hybrid of MI-17 and dual SERT/5-HT(1A) receptor antagonist SSA-426. Relative to MI-17, DJLDU-3-79 displayed 7-fold improvement in hSERT binding affinity and a 3-fold increase in [(3)H]-serotonin uptake inhibition potency at hSERT/HEK cells. This hybrid compound displayed a hSERT:hDAT selectivity ratio of 50:1, and a hSERT:hNET (human norepinephrine transporter) ratio of >200:1. In mice, DJLDU-3-79 decreased immobility in the tail suspension test comparable to the SSRI fluvoxamine, suggesting that DJLDU-3-79 may possess antidepressant properties. This proof of concept study highlights MAT virtual screening as a powerful tool for identifying novel inhibitor chemotypes and chemical fragments for rational inhibitor design.

Discovery of novel selective serotonin reuptake inhibitors through development of a protein-based pharmacophore.

The serotonin transporter (SERT), a member of the neurotransmitter sodium symporter (NSS) family, is responsible for the reuptake of serotonin from the synaptic cleft to maintain neurotransmitter homeostasis. SERT is established as an important target in the treatment of anxiety and depression. Because a high-resolution crystal structure is not available, a computational model of SERT was built based upon the X-ray coordinates of the leucine transporter LeuT, a bacterial NSS homologue. The model was used to develop the first SERT structure-based pharmacophore. Virtual screening (VS) of a small molecule structural library using the generated SERT computational model yielded candidate ligands of diverse scaffolds. Pharmacological analysis of the VS hits identified two SERT-selective compounds, potential lead compounds for further SERT-related medication development.