The effect of dopamine on pain-related neurons in the parafascicular nucleus of rats

DTI-SNNFRA: Drug-target interaction prediction by shared nearest neighbors and fuzzy-rough approximation

In-silico prediction of repurposable drugs is an effective drug discovery strategy that supplements de-nevo drug discovery from scratch. Reduced development time, less cost and absence of severe side effects are significant advantages of using drug repositioning. Most recent and most advanced artificial intelligence (AI) approaches have boosted drug repurposing in terms of throughput and accuracy enormously. However, with the growing number of drugs, targets and their massive interactions produce imbalanced data which may not be suitable as input to the classification model directly. Here, we have proposed DTI-SNNFRA, a framework for predicting drug-target interaction (DTI), based on shared nearest neighbour (SNN) and fuzzy-rough approximation (FRA). It uses sampling techniques to collectively reduce the vast search space covering the available drugs, targets and millions of interactions between them. DTI-SNNFRA operates in two stages: first, it uses SNN followed by a partitioning clustering for sampling the search space. Next, it computes the degree of fuzzy-rough approximations and proper degree threshold selection for the negative samples' undersampling from all possible interaction pairs between drugs and targets obtained in the first stage. Finally, classification is performed using the positive and selected negative samples. We have evaluated the efficacy of DTI-SNNFRA using AUC (Area under ROC Curve), Geometric Mean, and F1 Score. The model performs exceptionally well with a high prediction score of 0.95 for ROC-AUC. The predicted drug-target interactions are validated through an existing drug-target database (Connectivity Map (Cmap)).

Monoaminergic Antidepressants in the Relief of Pain: Potential Therapeutic Utility of Triple Reuptake Inhibitors (TRIs)

Over 75% of depressed patients suffer from painful symptoms predicting a greater severity and a less favorable outcome of depression. Imaging, anatomical and functional studies have demonstrated the existence of common brain structures, neuronal pathways and neurotransmitters in depression and pain. In particular, the ascending serotonergic and noradrenergic pathways originating from the raphe nuclei and the locus coeruleus; respectively, send projections to the limbic system. Such pathways control many of the psychological functions that are disturbed in depression and in the perception of pain. On the other hand, the descending pathways, from monoaminergic nuclei to the spinal cord, are specifically implicated in the inhibition of nociception providing rationale for the use of serotonin (5-HT) and/or norepinephrine (NE) reuptake inhibitors (SSRIs, NRIs, SNRIs), in the relief of pain. Compelling evidence suggests that dopamine (DA) is also involved in the pathophysiology and treatment of depression. Indeed, recent insights have demonstrated a central role for DA in analgesia through an action at both the spinal and suprasinal levels including brain regions such as the periaqueductal grey (PAG), the thalamus, the basal ganglia and the limbic system. In this context, dopaminergic antidepressants (i.e., containing dopaminergic activity), such as bupropion, nomifensine and more recently triple reuptake inhibitors (TRIs), might represent new promising therapeutic tools in the treatment of painful symptoms with depression. Nevertheless, whether the addition of the dopaminergic component produces more robust effects than single- or dual-acting agents, has yet to be demonstrated. This article reviews the main pathways regulating pain transmission in relation with the monoaminergic systems. It then focuses on the current knowledge regarding the in vivo pharmacological properties and mechanism of action of monoaminergic antidepressants including SSRIs, NRIs, SNRIs and TRIs. Finally, a synthesis of the preclinical studies supporting the efficacy of these antidepressants in analgesia is also addressed in order to highlight the relative contribution of 5-HT, NE and DA to nociception.