Focus on Human Monoamine Transporter Selectivity. New Human DAT and NET Models, Experimental Validation, and SERT Affinity Exploration

Machine Learning Tool for New Selective Serotonin and Serotonin-Norepinephrine Reuptake Inhibitors

Depression, a serious mood disorder, affects about 5% of the population. Currently, there are two groups of antidepressants that are the first-line treatment for depressive disorder: selective serotonin reuptake inhibitors and serotonin-norepinephrine reuptake inhibitors. The aim of the study was to develop Quantitative Structure-Activity Relationship (QSAR) models for serotonin (SERT) and norepinephrine (NET) transporters to predict the affinity and inhibition potential of new molecules. Models were developed using the Automated Machine Learning tool Mljar based on 80% of the dataset according to 10-fold cross-validation and externally validated on the remaining 20% of data. The molecular representation featured two-dimensional Mordred descriptors. For each model, Shapley additive explanations analysis was performed to clarify the influence of the descriptors on the models' predictions. Based on the final QSAR models, the following results were obtained: NET and pIC50 value RMSEtest = 0.678, R2test = 0.640; NET and pKi RMSEtest = 0.590, R2test = 0.709; SERT and pIC50 RMSEtest = 0.645, R2test = 0.678; SERT and pKi value RMSEtest = 0.540, R2test = 0.828. QSAR models for serotonin and norepinephrine transporters have been made available in a new module of the SerotoninAI application to enhance usability for scientists.

Computational Chemistry in Structure-Based Solute Carrier Transporter Drug Design: Recent Advances and Future Perspectives

Solute carrier transporters (SLCs) are a class of important transmembrane proteins that are involved in the transportation of diverse solute ions and small molecules into cells. There are approximately 450 SLCs within the human body, and more than a quarter of them are emerging as attractive therapeutic targets for multiple complex diseases, e.g., depression, cancer, and diabetes. However, only 44 unique transporters (∼9.8% of the SLC superfamily) with 3D structures and specific binding sites have been reported. To design innovative and effective drugs targeting diverse SLCs, there are a number of obstacles that need to be overcome. However, computational chemistry, including physics-based molecular modeling and machine learning- and deep learning-based artificial intelligence (AI), provides an alternative and complementary way to the classical drug discovery approach. Here, we present a comprehensive overview on recent advances and existing challenges of the computational techniques in structure-based drug design of SLCs from three main aspects: (i) characterizing multiple conformations of the proteins during the functional process of transportation, (ii) identifying druggability sites especially the cryptic allosteric ones on the transporters for substrates and drugs binding, and (iii) discovering diverse small molecules or synthetic protein binders targeting the binding sites. This work is expected to provide guidelines for a deep understanding of the structure and function of the SLC superfamily to facilitate rational design of novel modulators of the transporters with the aid of state-of-the-art computational chemistry technologies including artificial intelligence.

Uncovering Structure-Activity Relationships of Phenethylamines: Paving the Way for Innovative Mental Health Treatments

The rapidly evolving psychedelic industry has garnered considerable attention due to 3,4-methylenedioxymethamphetamine-assisted psychotherapy's ground-breaking success in treating moderate-to-severe Post-traumatic Stress Disorder in two Phase 3 clinical trials. This has opened Pandora's box for the development of innovative therapeutic modalities. Of particular interest are the phenethylamines and their ability to inhibit monoamine transporters. In this study, we employed the quantitative structure-activity relationship methodology to develop three vigorous models for the reuptake of serotonin, dopamine, and norepinephrine through monoamine transporters. These models were thoroughly validated using various criteria, including fitting (R2DAT = 0.869, R2SERT = 0.828, and R2NET = 0.887), internal (Q2looDAT = 0.795, Q2looSERT = 0.784, and Q2looNET = 0.820), and external (RMSEextDAT = 0.373, R2extDAT = 0.831, RMSEextSERT = 0.200, R2extSERT = 0.955, RMSEextNET = 0.318, and R2extNET = 0.711) criteria.

Chirality Matters: Fine-Tuning of Novel Monoamine Reuptake Inhibitors Selectivity through Manipulation of Stereochemistry

The high structural similarity, especially in transmembrane regions, of dopamine, norepinephrine, and serotonin transporters, as well as the lack of all crystal structures of human isoforms, make the specific targeting of individual transporters rather challenging. Ligand design itself is also rather limited, as many chemists, fully aware of the synthetic and analytical challenges, tend to modify lead compounds in a way that reduces the number of chiral centers and hence limits the potential chemical space of synthetic ligands. We have previously shown that increasing molecular complexity by introducing additional chiral centers ultimately leads to more selective and potent dopamine reuptake inhibitors. Herein, we significantly extend our structure-activity relationship of dopamine transporter-selective ligands and further demonstrate how stereoisomers of defined absolute configuration may fine-tune and direct the activity towards distinct targets. From the pool of active compounds, using the examples of stereoisomers 7h and 8h, we further showcase how in vitro activity significantly differs in in vivo drug efficacy experiments, calling for proper validation of individual stereoisomers in animal studies. Furthermore, by generating a large library of compounds with defined absolute configurations, we lay the groundwork for computational chemists to further optimize and rationally design specific monoamine transporter reuptake inhibitors.

Design, synthesis and cytotoxic evaluation of a selective serotonin reuptake inhibitor (SSRI) by virtual screening

Depression is one of the most common mental illnesses, affecting almost 300 million people. According to the WHO, depression is one of the world's leading causes of disability and morbidity. People with this illness require both psychological and pharmaceutical treatment because severe depressive episodes often result in suicide. Selective serotonin reuptake inhibitors (SSRI) are widely used antidepressants that target the human serotonin transporter (hSERT). The crystallization of hSERT and the experimental data available allows cost and time-efficient computational tools like virtual screening (VS) to be utilized in the development of therapeutic agents. Here, we synthesized, characterized, and evaluated the biological activity of a novel SSRI analog of paroxetine, rationally designed by applying an artificial neural network-based QSAR model and a molecular docking analysis on hSERT. The analog N-substituted 18a showed higher affinity for the transporter (-10.2 kcal/mol), lower Ki value (1.19 nM) and a safer toxicological profile than paroxetine and was synthesized with a 71% yield. The in vitro cytotoxicity of the analog was evaluated using human glioblastoma (U87 MG), human neuroblastoma (SH SY5Y) and murine fibroblast (L929) cell lines. Also, the hemolytic ability of the compound was assessed on human erythrocytes. Results showed that analog 18a did not exhibit cytotoxic activity on the cell lines used and has no hemolytic activity at any of the concentrations tested, whereas with paroxetine, hemolysis was observed at 2.3, 1.29 y 0.67 mM. Based on these results, it is possible to suggest that analog 18a could be a promising new SSRI candidate for the treatment of this illness.

Systematic review of studies using platelet serotonin content to assess bioeffect of serotonin reuptake inhibitors at the serotonin transporter

RATIONALE

Assessment of the bioeffect of serotonin reuptake inhibitors (SRIs, including both selective serotonin reuptake inhibitors (SSRIs) and serotonin-norepinephrine reuptake inhibitors (SNRIs)) at the serotonin transporter (SERT) in patients and healthy controls can have important theoretical and clinical implications.

OBJECTIVES

Bioeffect at SERT has been assessed by neuroimaging of brain SERT occupancy, through in vitro measurements of platelet serotonin (5-HT) uptake, and by measuring platelet 5-HT content pre- and post-initiation of SRI administration. Studies of platelet 5-HT content were reviewed in order to (1) determine the overall apparent bioeffect of SRIs; (2) compare bioeffect across types of SRIs; (3) compare the three approaches to assessing SRI bioeffect; and (4) determine how the findings might inform clinical practice.

METHODS

We performed a systematic review of the published studies that measured platelet 5-HT content to assess SRI bioeffect at the platelet SERT. Studies using neuroimaging and in vitro platelet 5-HT uptake to assess SRI bioeffect were reviewed for comparison purposes.

RESULTS

Clinical doses of SRIs typically resulted in 70-90% reductions in platelet 5-HT content. The observed bioeffect at the platelet SERT appeared similar among different SSRIs and SNRIs. The bioeffect estimations based on platelet 5-HT content were consistent with those obtained using neuroimaging to assess brain SERT occupancy and those based on the in vitro measurement of platelet 5-HT uptake.

CONCLUSIONS

In general, excellent agreement was seen in the apparent SRI bioeffect (70-90% inhibition) among the platelet 5-HT content studies and across the three bioeffect approaches. Theoretical and practical clinical implications are discussed.

Discovery and Development of Monoamine Transporter Ligands

Monoamine transporters (MATs) are targets of a wide range of compounds that have been developed as therapeutic treatments for various neuropsychiatric and neurodegenerative disorders such as depression, ADHD, neuropathic pain, anxiety disorders, stimulant use disorders, epilepsy, and Parkinson's disease. The MAT family is comprised of three main members - the dopamine transporter (DAT), the norepinephrine transporter (NET), and the serotonin transporter (SERT). These transporters are through reuptake responsible for the clearance of their respective monoamine substrates from the extracellular space. The determination of X-ray crystal structures of MATs and their homologues bound with various substrates and ligands has resulted in a surge of structure-function-based studies of MATs to understand the molecular basis of transport function and the mechanism of various ligands that ultimately result in their behavioral effects. This review focusses on recent examples of ligand-based structure-activity relationship studies trying to overcome some of the challenges associated with previously developed MAT inhibitors. These studies have led to the discovery of unique and novel structurally diverse MAT ligands including allosteric modulators. These novel molecular scaffolds serve as leads for designing more effective therapeutic interventions by modulating the activities of MATs and ultimately their associated neurotransmission and behavioral effects.

Overview of the structure and function of the dopamine transporter and its protein interactions

The dopamine transporter (DAT) plays an integral role in dopamine neurotransmission through the clearance of dopamine from the extracellular space. Dysregulation of DAT is central to the pathophysiology of numerous neuropsychiatric disorders and as such is an attractive therapeutic target. DAT belongs to the solute carrier family 6 (SLC6) class of Na⁺/Cl^- dependent transporters that move various cargo into neurons against their concentration gradient. This review focuses on DAT (SCL6A3 protein) while extending the narrative to the closely related transporters for serotonin and norepinephrine where needed for comparison or functional relevance. Cloning and site-directed mutagenesis experiments provided early structural knowledge of DAT but our contemporary understanding was achieved through a combination of crystallization of the related bacterial transporter LeuT, homology modeling, and subsequently the crystallization of drosophila DAT. These seminal findings enabled a better understanding of the conformational states involved in the transport of substrate, subsequently aiding state-specific drug design. Post-translational modifications to DAT such as phosphorylation, palmitoylation, ubiquitination also influence the plasma membrane localization and kinetics. Substrates and drugs can interact with multiple sites within DAT including the primary S1 and S2 sites involved in dopamine binding and novel allosteric sites. Major research has centered around the question what determines the substrate and inhibitor selectivity of DAT in comparison to serotonin and norepinephrine transporters. DAT has been implicated in many neurological disorders and may play a role in the pathology of HIV and Parkinson's disease via direct physical interaction with HIV-1 Tat and α-synuclein proteins respectively.

Pharmacological Characterization of Purified Full-Length Dopamine Transporter from Drosophila melanogaster

The dopamine transporter (DAT) is a member of the neurotransmitter:sodium symporter (NSS) family, mediating the sodium-driven reuptake of dopamine from the extracellular space thereby terminating dopaminergic neurotransmission. Our current structural understanding of DAT is derived from the resolutions of DAT from Drosophila melanogaster (dDAT). Despite extensive structural studies of purified dDAT in complex with a variety of antidepressants, psychostimulants and its endogenous substrate, dopamine, the molecular pharmacology of purified, full length dDAT is yet to be elucidated. In this study, we functionally characterized purified, full length dDAT in detergent micelles using radioligand binding with the scintillation proximity assay. We elucidate the consequences of Na⁺ and Cl^- binding on [³H]nisoxetine affinity and use this to evaluate the binding profiles of substrates and inhibitors to the transporter. Additionally, the technique allowed us to directly determine a equilibrium binding affinity (K_d) for [³H]dopamine to dDAT. To compare with a more native system, the affinities of specified monoamines and inhibitors was determined on dDAT, human DAT and human norepinephrine transporter expressed in COS-7 cells. With our gathered data, we established a pharmacological profile for purified, full length dDAT that will be useful for subsequent biophysical studies using dDAT as model protein for the mammalian NSS family of proteins.

Allosteric Binding of MDMA to the Human Serotonin Transporter (hSERT) via Ensemble Binding Space Analysis with ΔG Calculations, Induced Fit Docking and Monte Carlo Simulations

Despite the recent promising results of MDMA (3,4-methylenedioxy-methamphetamine) as a psychotherapeutic agent and its history of misuse, little is known about its molecular mode of action. MDMA enhances monoaminergic neurotransmission in the brain and its valuable psychoactive effects are associated to a dual action on the 5-HT transporter (SERT). This drug inhibits the reuptake of 5-HT (serotonin) and reverses its flow, acting as a substrate for the SERT, which possesses a central binding site (S1) for antidepressants as well as an allosteric (S2) one. Previously, we characterized the spatial binding requirements for MDMA at S1. Here, we propose a structure-based mechanistic model of MDMA occupation and translocation across both binding sites, applying ensemble binding space analyses, electrostatic complementarity, and Monte Carlo energy perturbation theory. Computed results were correlated with experimental data (r = 0.93 and 0.86 for S1 and S2, respectively). Simulations on all hSERT available structures with Gibbs free energy estimations (ΔG) revealed a favourable and pervasive dual binding mode for MDMA at S2, i.e., adopting either a 5-HT or an escitalopram-like orientation. Intermediate ligand conformations were identified within the allosteric site and between the two sites, outlining an internalization pathway for MDMA. Among the strongest and more frequent interactions were salt bridges with Glu494 and Asp328, a H-bond with Thr497, a π-π with Phe556, and a cation-π with Arg104. Similitudes and differences with the allosteric binding of 5-HT and antidepressants suggest that MDMA may have a distinctive chemotype. Thus, our models may provide a framework for future virtual screening studies and pharmaceutical design and to develop hSERT allosteric compounds with a unique psychoactive MDMA-like profile.

Assessment of Paroxetine Molecular Interactions with Selected Monoamine and γ-Aminobutyric Acid Transporters

Thus far, many hypotheses have been proposed explaining the cause of depression. Among the most popular of these are: monoamine, neurogenesis, neurobiology, inflammation and stress hypotheses. Many studies have proven that neurogenesis in the brains of adult mammals occurs throughout life. The generation of new neurons persists throughout adulthood in the mammalian brain due to the proliferation and differentiation of adult neural stem cells. For this reason, the search for drugs acting in this mechanism seems to be a priority for modern pharmacotherapy. Paroxetine is one of the most commonly used antidepressants. However, the exact mechanism of its action is not fully understood. The fact that the therapeutic effect after the administration of paroxetine occurs after a few weeks, even if the levels of monoamine are rapidly increased (within a few minutes), allows us to assume a neurogenic mechanism of action. Due to the confirmed dependence of depression on serotonin, norepinephrine, dopamine and γ-aminobutyric acid levels, studies have been undertaken into paroxetine interactions with these primary neurotransmitters using in silico and in vitro methods. We confirmed that paroxetine interacts most strongly with monoamine transporters and shows some interaction with γ-aminobutyric acid transporters. However, studies of the potency inhibitors and binding affinity values indicate that the neurogenic mechanism of paroxetine's action may be determined mainly by its interactions with serotonin transporters.