Systems psychopharmacology: A network approach to developing novel therapies

AADB: A Manually Collected Database for Combinations of Antibiotics With Adjuvants

Antimicrobial resistance is a global public health concern. The lack of innovations in antibiotic development has led to renewed interest in antibiotic adjuvants. However, there is no database to collect antibiotic adjuvants. Herein, we build a comprehensive database named Antibiotic Adjuvant DataBase (AADB) by manually collecting relevant literature. Specifically, AADB includes 3,035 combinations of antibiotics with adjuvants, covering 83 antibiotics, 226 adjuvants, and 325 bacterial strains. AADB provides user-friendly interfaces for searching and downloading. Users can easily obtain these datasets for further analysis. In addition, we also collected related datasets (e.g., chemogenomic and metabolomic data) and proposed a computational strategy to dissect these datasets. As a test case, we identified 10 candidates for minocycline, and 6 of 10 candidates are the known adjuvants that synergize with minocycline to inhibit the growth of E. coli BW25113. We hope that AADB can help users to identify effective antibiotic adjuvants. AADB is freely available at http://www.acdb.plus/AADB.

Differential gene regulation in the anterior cingulate cortex and superior temporal cortex in schizophrenia: A molecular network approach

The closely connected anterior cingulate cortex (ACC) and superior temporal cortex (STC) are important for higher cognitive functions. Both brain regions are disturbed in schizophrenia, i.e., functional and structural alterations have been reported. This postmortem investigation in brains from patients with schizophrenia and controls compared gene expression in the left ACC and left STC. Most differentially expressed genes were unique to each brain region, but some clusters of genes were equally dysregulated in both, giving rise to a more general disease-specific pattern of gene regulation. The data was used to construct a molecular network of the genes identically expressed in both regions as primary nodes and the metabolically connected genes as secondary nodes. The network analysis identified downregulated clusters of immune-associated gene products and upregulated clusters belonging to the ubiquitin-proteasome system. These findings could help to identify new potential therapeutic targets for future approaches.

A simple mechanistic terminology of psychoactive drugs: a proposal

Antidepressants, antiepileptics, mood stabilizers, and antipsychotics are extremely broadly used psychoactive drugs. These drug terms are universally used in the literature. However, the indications of these drugs have broadened substantially and overlap. The mismatch between drug classification and clinical uses causes a lot of confusion in communication and renders literature searches increasingly difficult. Therefore, we propose to drop the above terms altogether and replace them by simple mechanistic terms. Antidepressants are re-named as norepinephrine/serotonin (NE/5-HT) enhancers, antiepileptics comprising drugs with different mechanisms become neuronal inhibitors with pleiotropic effects (NIPEs), and antipsychotics become antagonists at multiple G protein-coupled receptors (mGPCR antagonists). Alkali metal ions, comprising lithium, are integrated into NIPEs. The terms "typical/first-generation/conventional" and "atypical/second-generation/non-conventional" antipsychotics should be dropped, because the original criterion for distinction, i.e., the presence and absence of extrapyramidal motor effects, respectively, is not valid anymore. The suggested changes in drug nomenclature have already been implemented into a recent textbook (Seifert R, Basic Knowledge of Pharmacology). The revised nomenclature ensures consistency with other fields of pharmacology and assignment of drug classes to indications without causing confusion. The authors acknowledge that the change in drug nomenclature is a cultural process that will take time and openly discuss the problems associated with the proposal. Ultimately, international learned societies will have to agree on a new nomenclature.

Epigenetic Drugs for Mood Disorders

There is increasing evidence that changes in epigenetic mechanisms of gene expression are involved in the pathogenesis of mood disorders. Such evidence stems from studies conducted on postmortem brain tissues and peripheral cells or tissues of patients with mood disorders. This article describes and discusses the epigenetic changes in the mood disorders (major depressive disorder and bipolar disorder) found to date. The article also describes and discusses preclinical drug trials of epigenetic drugs for treating mood disorders. In addition, nonrandomized and randomized controlled trials of nutritional drugs with effects on epigenetic mechanisms of gene expression in patients with major depressive disorder and bipolar disorder are discussed. Trials of epigenetic drugs and nutritional drugs with epigenetic effects are showing promising results for the treatment of mood disorders. Thus, epigenetic drugs and nutritional drugs with epigenetic effects could be useful in the treatment of patients with these disorders.

Molecular signatures associated with tumor-specific immune response in melanoma patients treated with dendritic cell-based immunotherapy

Purpose

We previously showed that autologous dendritic cells (DCs) loaded with an allogeneic heat shock (HS)-conditioned melanoma cell-derived lysate, called TRIMEL, induce T-cell-mediated immune responses in stage IV melanoma patients. Importantly, a positive delayed-type hypersensitivity (DTH) reaction against TRIMEL after vaccination, correlated with patients prolonged survival. Furthermore, we observed that DTH reaction was associated with a differential response pattern reflected in the presence of distinct cell subpopulations in peripheral blood. Detected variations in patient responses encouraged molecular studies aimed to identify gene expression profiles induced after vaccination in treated patients, allowing the identification of new molecular predictive markers.

Methods

Gene expression patterns were analyzed by microarrays during vaccination, and some of them confirmed by quantitative real-time reverse transcriptase PCR (qRT-PCR) in the total leukocyte population of a representative group of responder and non-responder patients. New candidates for biomarkers with predictive value were identified using bioinformatics, molecular analysis, and flow cytometry.

Results

Seventeen genes overexpressed in responder patients after vaccination respect to non-responders were identified after a mathematical analysis, from which ten were linked to immune responses and five related to cell cycle control and signal transduction. In immunological responder patients, increased protein levels of the chemokine receptor CXCR4 and the Fc-receptor CD32 were observed on cell membranes of CD8+ T and B cells and the monocyte population, respectively, confirming gene expression results.

Conclusions

Our study contributes to finding new molecular markers associated with clinical outcome and better understanding of clinically relevant immunological responses induced by anti-tumor DC-vaccines.

A computational network analysis based on targets of antipsychotic agents

Currently, numerous antipsychotic agents have been developed in the area of pharmacological treatment of schizophrenia. However, the molecular mechanism underlying multi targets of antipsychotics were yet to be explored. In this study we performed a computational network analysis based on targets of antipsychotic agents. We retrieved a total of 96 targets from 56 antipsychotic agents. By expression enrichment analysis, we identified that the expressions of antipsychotic target genes were significantly enriched in liver, brain, blood and corpus striatum. By protein-protein interaction (PPI) network analysis, a PPI network with 77 significantly interconnected target genes was generated. By historeceptomics analysis, significant brain region specific target-drug interactions were identified in targets of dopamine receptors (DRD1-Olanzapine in caudate nucleus and pons (P-value<0.005), DRD2-Bifeprunox in caudate nucleus and pituitary (P-value<0.0005), DRD4-Loxapine in Pineal (P-value<0.00001)) and 5-hydroxytryptamine receptor (HTR2A-Risperidone in occipital lobe, prefrontal cortex and subthalamic nucleus (P-value<0.0001)). By pathway grouped network analysis, 34 significant pathways were identified and significantly grouped into 6 sub networks related with drug metabolism, Calcium signaling, GABA receptors, dopamine receptors, Bile secretion and Gap junction. Our results may provide biological explanation for antipsychotic targets and insights for molecular mechanism of antipsychotic agents.

Identification of potential drug targets for treatment of refractory epilepsy using network pharmacology

Epilepsy is the fourth most common neurological disease after migraine, stroke, and Alzheimer's disease. Approximately one-third of all epilepsy cases are refractory to the existing anticonvulsants. Thus, there is an unmet need for newer antiepileptic drugs (AEDs) to manage refractory epilepsy (RE). Discovery of novel AEDs for the treatment of RE further retards for want of potential pharmacological targets, unavailable due to unclear etiology of this disease. In this regard, network pharmacology as an area of bioinformatics is gaining popularity. It combines the methods of network biology and polypharmacology, which makes it a promising approach for finding new molecular targets. This work is aimed at discovering new pharmacological targets for the treatment of RE using network pharmacology methods. In the framework of our study, the genes associated with the development of RE were selected based on analysis of available data. The methods of network pharmacology were used to select 83 potential pharmacological targets linked to the selected genes. Then, 10 most promising targets were chosen based on analysis of published data. All selected target proteins participate in biological processes, which are considered to play a key role in the development of RE. For 9 of 10 selected targets, the potential associations with different kinds of epilepsy have been recently mentioned in the literature published, which gives additional evidence that the approach applied is rather promising.

Advances in Pharmacotherapy Development: Human Clinical Studies

For more than 25 years, researchers have made advances in developing medications to treat alcohol use disorder (AUD), highlighted by the US Food and Drug Administration's (FDA's) approval of disulfiram, naltrexone (oral and long-acting), and acamprosate. These medications are also approved in Europe, where the European Medicines Agency (EMA) recently added a fourth medication, nalmefene, for AUD. Despite these advances, today's medications have a small effect size, showing efficacy for only a limited number of individuals with AUD. However, a host of new medications, which act on variety of pharmacologic targets, are in the pipeline and have been evaluated in numerous human studies. This article reviews the efficacy and safety of medications currently being tested in human trials and looks at ongoing efforts to identify candidate compounds in human studies. As mentioned in the National Institute on Alcohol Abuse and Alcoholism's Strategic Plan 2017-2021 ( https://www.niaaa.nih.gov/sites/default/files/StrategicPlan_NIAAA_optimized_2017-2020.pdf ), medications development remains a high priority. By developing more effective and safe medications, and identifying those patients who will benefit the most from these treatments, we can provide clinicians with the tools they need to treat this devastating disorder, providing relief for patients and their families and markedly improving public health and safety.

Multiple target-centric strategy to tame inflammation

Single-target inhibition is an unsatisfactory therapeutic option to treat multifactorial pathologies, brought into limelight 'paradox of inflammation' beside dearth of innovation, rationalizes a shift toward 'multiple-target' design concept in anti-inflammatory research field. To improvise, two platform strategies, drugs mixture or multitarget drugs, are plausible. Dual cyclooxygenase/lipoxygenase inhibitor 'licofelone' developed after the backfire of rofecoxib due to safety concerns has fetched first light of triumph of the latter strategy. As hitting multiple targets in restraint is perhaps more viable strategy rather than single target, this review, outlines the most germane multiple target agents of synthetic and natural origin placing clear advantage in favors of multitarget strategy as real therapeutic solution for inflammation.

Network analysis and in silico prediction of protein-protein interactions with applications in drug discovery

Protein-protein interactions (PPIs) are vital to maintaining cellular homeostasis. Several PPI dysregulations have been implicated in the etiology of various diseases and hence PPIs have emerged as promising targets for drug discovery. Surface residues and hotspot residues at the interface of PPIs form the core regions, which play a key role in modulating cellular processes such as signal transduction and are used as starting points for drug design. In this review, we briefly discuss how PPI networks (PPINs) inferred from experimentally characterized PPI data have been utilized for knowledge discovery and how in silico approaches to PPI characterization can contribute to PPIN-based biological research. Next, we describe the principles of in silico PPI prediction and survey the existing PPI and PPI site prediction servers that are useful for drug discovery. Finally, we discuss the potential of in silico PPI prediction in drug discovery.