Clickable photoaffinity ligands for the human serotonin transporter based on the selective serotonin reuptake inhibitor (S)-citalopram.

To date, the development of photoaffinity ligands targeting the human serotonin transporter (hSERT), a key protein involved in disease states such as depression and anxiety, have been radioisotope-based (i.e., 3H or 125I). This letter instead highlights three derivatives of the selective serotonin reuptake inhibitor (SSRI) (S)-citalopram that were rationally designed and synthesized to contain a photoreactive benzophenone or an aryl azide for protein target capture via photoaffinity labeling and a terminal alkyne or an aliphatic azide for click chemistry-based proteomics. Specifically, clickable benzophenone-based (S)-citalopram photoprobe 6 (hSERT Ki = 0.16 nM) displayed 11-fold higher binding affinity at hSERT when compared to (S)-citalopram (hSERT Ki = 1.77 nM), and was subsequently shown to successfully undergo tandem photoaffinity labeling-biorthogonal conjugation using purified hSERT. Given clickable photoprobes can be used for various applications depending on which reporter is attached by click chemistry subsequent to photoaffinity labeling, photoprobe 6 is expected to find value in structure-function studies and other research applications involving hSERT (e.g., imaging).

SKI-178: A Multitargeted Inhibitor of Sphingosine Kinase and Microtubule Dynamics Demonstrating Therapeutic Efficacy in Acute Myeloid Leukemia Models.

AIM: To further characterize the selectivity, mechanism-of-action and therapeutic efficacy of the novel small molecule inhibitor, SKI-178. METHODS: Using the state-of-the-art Cellular Thermal Shift Assay (CETSA) technique to detect "direct target engagement" of proteins intact cells, in vitro and in vivo assays, pharmacological assays and multiple mouse models of acute myeloid leukemia (AML). RESULTS: Herein, we demonstrate that SKI-178 directly target engages both Sphingosine Kinase 1 and 2. We also present evidence that, in addition to its actions as a Sphingosine Kinase Inhibitor, SKI-178 functions as a microtubule network disrupting agent both in vitro and in intact cells. Interestingly, we separately demonstrate that simultaneous SphK inhibition and microtubule disruption synergistically induces apoptosis in AML cell lines. Furthermore, we demonstrate that SKI-178 is well tolerated in normal healthy mice. Most importantly, we demonstrate that SKI-178 has therapeutic efficacy in several mouse models of AML. CONCLUSION: SKI-178 is a multi-targeted agent that functions both as an inhibitor of the SphKs as well as a disruptor of the microtubule network. SKI-178 induced apoptosis arises from a synergistic interaction of these two activities. SKI-178 is safe and effective in mouse models of AML, supporting its further development as a multi-targeted anti-cancer therapeutic agent.

Rapid and sustained antidepressant properties of an NMDA antagonist/monoamine reuptake inhibitor identified via transporter-based virtual screening.

Rational design of lead compounds targeting monoamine transporters (MATs) is critical to developing novel therapeutics to treat psychiatric disorders including depression and substance abuse. A 3-D dopamine transporter (DAT) computer model was used to virtually screen a commercially available small molecule library for high DAT affinity drug-like compounds. One hit, coded "MI-4", inhibited human dopamine, norepinephrine, and serotonin transporters in vitro. In vivo administration in mice induced robust, dose-dependent antidepressant-like behaviors in learned helplessness models (tail suspension and forced swim tests). Moreover, chronic administration (21day, 10mg/kg, bid) reduced drinking latencies comparable to fluoxetine (10mg/kg, bid) in the novelty-induced hypophagia test, which requires chronic treatment to produce antidepressant-like effects. MI-4 (10mg/kg, bid) produced rapid (three-day) antidepressant-like effects in the social avoidance test following 10days of social defeat stress. Unlike ketamine, chronic administration of MI-4 increased social interaction scores while improving resiliency to the mood-altering effects of stress to over 70%. Importantly, MI-4 exhibited minimal abuse liability in behavioral and neurological models (conditioned place preference and dopamine in vivo microdialysis). MI-4 was found to be Ro-25-6981, an ifenprodil analog and reputed NMDA antagonist. The data suggest that Ro-25-6981, previously known for rapid-acting glutamatergic antidepressant actions, may also functionally inhibit monoamine reuptake and produces sustained antidepressant effects in vivo. This demonstrates, as proof of principle, the viability of combining these mechanisms to produce rapid and sustained antidepressant-like effects. Overall, these findings suggest MAT computational model-based virtual screening is a viable method for identifying antidepressant lead compounds of unique scaffold.

Discovery of novel-scaffold monoamine transporter ligands via in silico screening with the S1 pocket of the serotonin transporter.

Discovery of new inhibitors of the plasmalemmal monoamine transporters (MATs) continues to provide pharmacotherapeutic options for depression, addiction, attention deficit disorders, psychosis, narcolepsy, and Parkinson's disease. The windfall of high-resolution MAT structural information afforded by X-ray crystallography has enabled the construction of credible computational models. Elucidation of lead compounds, creation of compound structure-activity series, and pharmacologic testing are staggering expenses that could be reduced by using a MAT computational model for virtual screening (VS) of structural libraries containing millions of compounds. Here, VS of the PubChem small molecule structural database using the S1 (primary substrate) ligand pocket of a serotonin transporter homology model yielded 19 prominent "hit" compounds. In vitro pharmacology of these VS hits revealed four structurally unique MAT substrate uptake inhibitors with high nanomolar affinity at one or more of the three MATs. In vivo characterization of three of these hits revealed significant activity in a mouse model of acute depression at doses that did not elicit untoward locomotor effects. This constitutes the first report of MAT inhibitor discovery using exclusively the primary substrate pocket as a VS tool. Novel-scaffold MAT inhibitors offer hope of new medications that lack the many classic adverse effects of existing antidepressant drugs.

New design strategies for antidepressant drugs.

INTRODUCTION: 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. AREAS COVERED: 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. EXPERT OPINION: 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.

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.