A novel multilevel statistical method for the study of the relationships between multireceptorial binding affinity profiles and in vivo endpoints

Multi-targeted drug design strategies for the treatment of schizophrenia

INTRODUCTION

Schizophrenia is a complex psychiatric disease (or a conglomeration of disorders) manifesting with positive, negative and cognitive symptoms. The pathophysiology of schizophrenia is not completely known; however, it involves many neurotransmitters and their receptors. In order to treat schizophrenia, drugs need to be multi-target drugs. Indeed, the action of second and third generation antipsychotics involves interactions with many receptors, belonging mainly to aminergic GPCRs.

AREAS COVERED

In this review, the authors summarize current concepts of schizophrenia with the emphasis on the modern dopaminergic, serotoninergic, and glutamatergic hypotheses. Next, they discuss treatments of the disease, stressing multi-target antipsychotics. They cover different aspects of design of multi-target ligands, including the application of molecular modeling approaches for the design and benefits and limitations of multifunctional compounds. Finally, they present successful case studies of multi-target drug design against schizophrenia.

EXPERT OPINION

Treatment of schizophrenia requires the application of multi-target drugs. While designing single target drugs is relatively easy, designing multifunctional compounds is a challenge due to the necessity to balance the affinity to many targets, while avoiding promiscuity and the problems with drug-likeness. Multi-target drugs bring many benefits: better efficiency, fewer adverse effects, and drug-drug interactions and better patient compliance to drug regime.

Current Concepts and Treatments of Schizophrenia

Schizophrenia is a debilitating mental illness which involves three groups of symptoms, i.e., positive, negative and cognitive, and has major public health implications. According to various sources, it affects up to 1% of the population. The pathomechanism of schizophrenia is not fully understood and current antipsychotics are characterized by severe limitations. Firstly, these treatments are efficient for about half of patients only. Secondly, they ameliorate mainly positive symptoms (e.g., hallucinations and thought disorders which are the core of the disease) but negative (e.g., flat affect and social withdrawal) and cognitive (e.g., learning and attention disorders) symptoms remain untreated. Thirdly, they involve severe neurological and metabolic side effects and may lead to sexual dysfunction or agranulocytosis (clozapine). It is generally agreed that the interactions of antipsychotics with various neurotransmitter receptors are responsible for their effects to treat schizophrenia symptoms. In particular, several G protein-coupled receptors (GPCRs), mainly dopamine, serotonin and adrenaline receptors, are traditional molecular targets for antipsychotics. Comprehensive research on GPCRs resulted in the exploration of novel important signaling mechanisms of GPCRs which are crucial for drug discovery: intentionally non-selective multi-target compounds, allosteric modulators, functionally selective compounds and receptor oligomerization. In this review, we cover current hypotheses of schizophrenia, involving different neurotransmitter systems, discuss available treatments and present novel concepts in schizophrenia and its treatment, involving mainly novel mechanisms of GPCRs signaling.

In vitro, molecular modeling and behavioral studies of 3-{[4-(5-methoxy-1H-indol-3-yl)-1,2,3,6-tetrahydropyridin-1-yl]methyl}-1,2-dihydroquinolin-2-one (D2AAK1) as a potential antipsychotic

Antipsychotics currently available to treat schizophrenia suffer several limitations: (1) they are efficient against positive but not negative and cognitive symptoms of the disease; (2) they help only a half of patients; (3) they have severe side effects including neurological and metabolic side effects. Thus, novel drugs to treat schizophrenia are highly demanded. We identified a novel dopamine D2 receptor antagonist, D2AAK1, with Ki of 58 nM using structure-based virtual screening. D2AAK1 possesses additional nanomolar or low micromolar affinity to D1, D3, 5-HT1A and 5-HT2A receptors, making it an ideal candidate for a multi-target drug. Here we present homology modeling, molecular docking and molecular dynamics of D2AAK1 and its molecular targets and animal studies of D2AAK1 as a potential antipsychotic. The main contact of D2AAK1 and all the receptors studied is the electrostatic interaction between the protonable nitrogen atom of the ligand and the conserved Asp(3.32) as typical for orthosteric ligands of aminergic GPCRs. We confirmed antagonistic/partial agonistic properties of D2AAK1 towards all the receptors in in vitro essays and in in silico studies as the ligand stabilizes the ionic lock interaction. We also demonstrated neuroleptic, anxiolytic and, importantly, procognitive properties of D2AAK1 in mouse models.

A multivariate approach linking reported side effects of clinical antidepressant and antipsychotic trials to in vitro binding affinities

The vast majority of approved antidepressants and antipsychotics exhibit a complex pharmacology. The mechanistic understanding of how these psychotropic medications are related to adverse drug reactions (ADRs) is crucial for the development of novel drug candidates and patient adherence. This study aims to associate in vitro assessed binding affinity profiles (39 compounds, 24 molecular drug targets) and ADRs (n=22) reported in clinical trials of antidepressants and antipsychotics (n>59.000 patients) by the use of robust multivariate statistics. Orthogonal projection to latent structures (O-PLS) regression models with reasonable predictability were found for several frequent ADRs such as nausea, diarrhea, hypotension, dizziness, headache, insomnia, sedation, sleepiness, increased sweating, and weight gain. Results of the present study support many well-known pharmacological principles such as the association of hypotension and dizziness with α1-receptor or sedation with H1-receptor antagonism. Moreover, the analyses revealed novel or hardly investigated mechanisms for common ADRs including the potential involvement of 5-HT6-antagonism in weight gain, muscarinic receptor antagonism in dizziness, or 5-HT7-antagonism in sedation. To summarize, the presented study underlines the feasibility and value of a multivariate data mining approach in psychopharmacological development of antidepressants and antipsychotics.

Structure-based discovery of selective serotonin 5-HT(1B) receptor ligands

The development of safe and effective drugs relies on the discovery of selective ligands. Serotonin (5-hydroxytryptamine [5-HT]) G protein-coupled receptors are therapeutic targets for CNS disorders but are also associated with adverse drug effects. The determination of crystal structures for the 5-HT1B and 5-HT2B receptors provided an opportunity to identify subtype selective ligands using structure-based methods. From docking screens of 1.3 million compounds, 22 molecules were predicted to be selective for the 5-HT1B receptor over the 5-HT2B subtype, a requirement for safe serotonergic drugs. Nine compounds were experimentally verified as 5-HT1B-selective ligands, with up to 300-fold higher affinities for this subtype. Three of the ligands were agonists of the G protein pathway. Analysis of state-of-the-art homology models of the two 5-HT receptors revealed that the crystal structures were critical for predicting selective ligands. Our results demonstrate that structure-based screening can guide the discovery of ligands with specific selectivity profiles.

Progress in the structural prediction of G protein-coupled receptors: D3 receptor in complex with eticlopride

Predicting the three-dimensional structure of ligand-receptor complexes involving G protein-coupled receptors (GPCRs) is still a challenging task in rational drug design. To evaluate the reliability of the GPCR structural prediction, only a couple of community-wide assessments have been carried out. Our participation in the last edition, DOCK2010, involved the blind prediction of the dopaminergic D(3) receptor in complex with the D(2)/D(3) selective antagonist eticlopride for which the crystal structure has been recently released. Here, we describe a methodology that succeeded to produce a correctly predicted eticlopride-D(3) receptor complex out of three submitted models. Ranking the obtained models in the correct order is the main challenge due to subtle structural differences in the complex that are not sufficiently captured by conventional scoring functions. Importantly, our work reveals that a correct ranking is obtained by including a more sophisticated description of conformational ligand energy on binding. All in all, this case study highlights the current progress in modeling GPCR complexes and underlines that in silico modeling can be a valuable complement in GPCR drug discovery.