A recent review, published in Expert Opinion on Drug Discovery, has explored our current understanding of schizophrenia and the applications of a multi-target drug design in developing treatments.
Schizophrenia
Schizophrenia is a complex and debilitating psychiatric disorder, with a prevalence of up to 1%. The disease manifests with positive (e.g. hallucinations), negative (e.g. social withdrawal) and cognitive (e.g. attention deficiencies) symptoms. Several comorbidities associate with schizophrenia, including panic disorder and obsessive-compulsive disorder.
The pathophysiology of schizophrenia is unclear. However, researchers know that it involves a number of neurotransmitter systems, such as dopamine and serotonin (and their receptors). Schizophrenia symptoms are currently managed with first, second and third-generation antipsychotics. Most antipsychotics are only efficient against positive symptoms of the disease, with limited impact on the negative and cognitive disturbances. In addition, researchers have found that first-generation antipsychotics can induce neurological side effects, such as Parkinson’s disease. The authors also note that not all currently available drugs are effective for every patient and often the clinical efficacy is only apparent after weeks of treatment. As a result, there are currently no ideal schizophrenia treatments, making the discovery of novel drugs essential.
Paradigm shift
In recent years, there has been a paradigm change from ‘one disease, one gene, one goal, one drug’ to multi-target drugs affecting a number of molecular targets. These drugs are characterised by better clinical efficacy, fewer sides effects and drug-drug interactions. Although the design of these drugs is much more complicated than a compound with a single target, the authors argue that the effort is worth it for complex diseases, like schizophrenia, where there are no better drugs.
Current treatments
Classical antipsychotics arise mainly from blocking the dopamine D2 receptor. Therefore, schizophrenia multi-target compounds often refer to antipsychotics that fall into second and third generations. This is because their efficacy in alleviating symptoms is the result of both affinity to dopamine and serotonin receptors. Newer antipsychotics still target the dopamine D2 receptor, yet also target other dopamine receptors, including D3, serotonin 5-HT2A and 5-HT1A.
First-generation
The most important group of first-generation antipsychotics include phenothiazines (e.g. chlorpromazine), butyrophenones (e. g. haloperidol) and thioxanthenes (e.g. clopenthixol). These drugs target a wide spectrum of receptors, resulting in numerous adverse effects. In some cases, first-generation antipsychotics are sufficient for management of schizophrenia. However, when the disease manifests itself with negative and cognitive symptoms, this generation of drugs fails.
Second and third-generation
The introduction of the first second-generation antipsychotic, clozapine, catalysed a new era of schizophrenia treatment. Antagonism at the serotonin 5-HT2A receptor is the main mechanism of action for this group. Their multi-receptor profile of action contributes to reducing positive, negative and cognitive symptoms. Other examples of these drugs include quetiapine, olanzapine and risperidone. While patients tolerate this group better compared to older drugs, serious side effects still occur. These include obesity and diabetes. Third-generation drugs (e.g. aripiprazole) are distinctive as their mechanism of action is partial agonism at dopamine D2 receptors rather than antagonism. They are also partial agonists of the 5-HT1A receptor and affect several other receptors. The main advantage of these drugs over first-generation is that the probability of causing extrapyramidal side effects is low.
The introduction of second and third-generation antipsychotics changed management of schizophrenia. Yet their effectiveness in comparison to older drugs is still under discussion. While claims cannot be made of the superiority of multi-target drugs, the team highlight that there is noticeable clinical benefit of targeting several neurotransmitter pathways. Therefore, they suggest that this constitutes the rationale for further investigation of such compounds.
Benefits and limitations of multi-drug design
Benefits:
- The obtained hybrid can interact with a wide range of targets, improving the efficacy of the treatment.
- They have a positive impact on pharmacokinetic parameters and improve safety.
- Administration of one drug avoids drug-drug interactions and different bioavailability of drugs used in combination.
- They have a lower risk of adverse effects compared to drug cocktails.
- They may also overcome drug resistance and tolerance.
- There is an increased likelihood of patient compliance.
Limitations:
- They are difficult to design as the molecules should exhibit balanced activity to multiple targets. To achieve this, other elements are often compromised.
- There is a strong tendency to follow the hybrid drug design approach, often resulting in dual ligands with high molecular masses.
- There are potential off-target effects.
Future
Multi-target drug design is a hot topic in many research projects. There is an apparent shift towards using knowledge obtained regarding the complexity of signalling and metabolic pathways. For currently available antipsychotics, second and third-generation drugs exhibit multi-target modes of action. This is particularly true for clozapine which exhibits affinity to many GPCRs and is often used to treat drug-resistant schizophrenia. Currently, most antipsychotics act through aminergic GPCRs. There is a lot of work exploring other targets, such as metabotropic glutamate receptors, NMDA receptors and nicotinic receptors. Nonetheless, the authors highlight that the effect here is limited. They suggest that an efficient antipsychotic will likely be a multi-target one, which includes inflammation or oxidative stress-associated targets or something beyond the dopaminergic hypothesis. They emphasise that the development of a tool, most likely computational, will be key to solving problems associated with GPCR ligand selectivity/polypharmacology.
Image credit: By Naeblys – canva.com
