Discovery of potent, orally bioavailable, selective 5-HT1A/B/D receptor antagonists

5-HT1A receptor pharmacophores to screen for off-target activity of α1-adrenoceptor antagonists

The α1-adrenoceptors (α1-ARs), in particular the α1A-AR subtype, are current therapeutic targets of choice for the treatment of urogenital conditions, such as benign prostatic hyperplasia (BPH). Due to the similarity between the transmembrane domains of the α1-AR subtypes, and the serotonin receptor subtype 1A (5-HT1A-R), currently used α1-AR subtype-selective drugs to treat BPH display considerable off-target affinity for the 5-HT1A-R, leading to side effects. We describe the construction and validation of pharmacophores for 5-HT1A-R agonists and antagonists. Through the structural diversity of the training sets used in their development, these pharmacophores define the properties of a compound needed to bind to 5-HT1A receptors. Using these and previously published pharmacophores in virtual screening and profiling, we have identified unique chemical compounds (hits) that fit the requirements to bind to our target, the α1A-AR, selectively over the off-target, the 5-HT1A-R. Selected hits have been obtained and their affinities for α1A-AR, α1B-AR and 5-HT1A-R determined in radioligand binding assays, using membrane preparations which contain human receptors expressed individually. Three of the tested hits demonstrate statistically significant selectivity for α1A-AR over 5-HT1A-R. All seven tested hits bind to α1A-AR, with two compounds displaying K i values below 1 μM, and a further two K i values of around 10 μM. The insights and knowledge gained through the development of the new 5-HT1A-R pharmacophores will greatly aid in the design and synthesis of derivatives of our lead compound, and allow the generation of more efficacious and selective ligands.

Classification of 5-HT(1A) receptor agonists and antagonists using GA-SVM method

AIM

To construct a reliable computational model for the classification of agonists and antagonists of 5-HT(1A) receptor.

METHODS

Support vector machine (SVM), a well-known machine learning method, was employed to build a prediction model, and genetic algorithm (GA) was used to select the most relevant descriptors and to optimize two important parameters, C and r of the SVM model. The overall dataset used in this study comprised 284 ligands of the 5-HT(1A) receptor with diverse structures reported in the literatures.

RESULTS

A SVM model was successfully developed that could be used to predict the probability of a ligand being an agonist or antagonist of the 5-HT(1A) receptor. The predictive accuracy for training and test sets was 0.942 and 0.865, respectively. For compounds with probability estimate higher than 0.7, the predictive accuracy of the model for training and test sets was 0.954 and 0.927, respectively. To further validate our model, the receiver operating characteristic (ROC) curve was plotted, and the Area-Under-the-ROC- Curve (AUC) value was calculated to be 0.883 for training set and 0.906 for test set.

CONCLUSION

A reliable SVM model was successfully developed that could effectively distinguish agonists and antagonists among the ligands of the 5-HT(1A) receptor. To our knowledge, this is the first effort for the classification of 5-HT(1A) receptor agonists and antagonists based on a diverse dataset. This method may be used to classify the ligands of other members of the GPCR family.

Antidepressant potential of nitrogen-containing heterocyclic moieties: An updated review

Depression is currently the fourth leading cause of disease or disability worldwide. Antidepressant is approved for the treatment of major depression (including paediatric depression), obsessive-compulsive disorder (in both adult and paediatric populations), bulimia nervosa, panic disorder and premenstrual dysphoric disorder. Antidepressant is a psychiatric medication used to alleviate mood disorders, such as major depression and dysthymia and anxiety disorders such as social anxiety disorder. Many drugs produce an antidepressant effect, but restrictions on their use have caused controversy and off-label prescription a risk, despite claims of superior efficacy. Our current understanding of its pathogenesis is limited and existing treatments are inadequate, providing relief to only a subset of people suffering from depression. Reviews of literature suggest that heterocyclic moieties and their derivatives has proven success in treating depression.

Dual- and triple-acting agents for treating core and co-morbid symptoms of major depression: novel concepts, new drugs

The past decade of efforts to find improved treatment for major depression has been dominated by genome-driven programs of rational drug discovery directed toward highly selective ligands for nonmonoaminergic agents. Selective drugs may prove beneficial for specific symptoms, for certain patient subpopulations, or both. However, network analyses of the brain and its dysfunction suggest that agents with multiple and complementary modes of action are more likely to show broad-based efficacy against core and comorbid symptoms of depression. Strategies for improved multitarget exploitation of monoaminergic mechanisms include triple inhibitors of dopamine, serotonin (5-HT) and noradrenaline reuptake, and drugs interfering with feedback actions of monoamines at inhibitory 5-HT(1A), 5-HT(1B) and possibly 5-HT(5A) and 5-HT(7) receptors. Specific subsets of postsynaptic 5-HT receptors mediating antidepressant actions are under study (e.g., 5-HT(4) and 5-HT(6)). Association of a clinically characterized antidepressant mechanism with a nonmonoaminergic component of activity is an attractive strategy. For example, agomelatine (a melatonin agonist/5-HT(2C) antagonist) has clinically proven activity in major depression. Dual neurokinin(1) antagonists/5-HT reuptake inhibitors (SRIs) and melanocortin(4) antagonists/SRIs should display advantages over their selective counterparts, and histamine H(3) antagonists/SRIs, GABA(B) antagonists/SRIs, glutamatergic/SRIs, and cholinergic agents/SRIs may counter the compromised cognitive function of depression. Finally, drugs that suppress 5-HT reuptake and blunt hypothalamo-pituitary-adrenocorticotrophic axis overdrive, or that act at intracellular proteins such as GSK-3beta, may abrogate the negative effects of chronic stress on mood and neuronal integrity. This review discusses the discovery and development of dual- and triple-acting antidepressants, focusing on novel concepts and new drugs disclosed over the last 2 to 3 years.