Opportunities in systems biology to discover mechanisms and repurpose drugs for CNS diseases

A Study to Decipher the Potential Effects of Butylphthalide against Central Nervous System Diseases Based on Network Pharmacology and Molecular Docking Integration Strategy

Background

Butylphthalide (NBP), approved by the China National Medical Products Administration (NMPA) for the treatment of ischemic stroke (IS), showed pleiotropic potentials against central nervous system (CNS) diseases, including neuroprotection and cognitive deficits improvement. However, the effects and corresponding modes of action were not fully explored. This study was designed to investigate the potential of NBP against IS-associated CNS diseases based on network pharmacology (NP) and molecular docking (MD).

Methods

IS was inputted as the index disease to retrieve the “associated diseases” in DisGeNET. Three-database-based IS genes were obtained and integrated (DisGeNET, Malacards, and OMIM). Then, IS-associated genes were identified by combining these genes. Meanwhile, PubMed references and online databases were applied to identify NBP target genes. The IS-related disease-disease association (DDA) network and NBP-disease regulation network were constructed and analyzed in Cytoscape. In silico MD and references were used to validate the binding affinity of NBP with critical targets and the potential of NBP against certain IS-related CNS disease regulation.

Results

175 NBP target genes were obtained, while 312 IS-related disease genes were identified. 36 NBP target genes were predicted to be associated with IS-related CNS diseases, including Alzheimer's disease (AD), epilepsy, major depressive disorder (MDD), amyotrophic lateral sclerosis (ALS), and dementia. Six target genes (i.e., GRIN1, PTGIS, PTGES, ADRA1A, CDK5, and SULT1E1) indicating disease specificity index (DSI) >0.5 showed certain to good degree binding affinity with NBP, ranging from −9.2 to −6.7 kcal/mol. And the binding modes may be mainly related to hydrogen bonds and hydrophobic “bonds.” Further literature validations inferred that these critical NBP targets had a tight association with AD, epilepsy, ALS, and depression.

Conclusions

Our study proposed a drug-target-disease integrated method to predict the drug repurposing potentials to associated diseases by application of NP and MD, which could be an attractive alternative to facilitate the development of CNS disease therapies. NBP may be promising and showed potentials to be repurposed for treatments for AD, epilepsy, ALS, and depression, and further investigations are warranted to be carefully designed and conducted.

Admission Hemoglobin Levels Are Associated With Functional Outcome in Spontaneous Intracerebral Hemorrhage

OBJECTIVES

To test the hypothesis that admission hemoglobin levels are associated with outcome in primary, nontraumatic intracerebral hemorrhage.

DESIGN

Individual patient data meta-analysis of three studies of intracerebral hemorrhage.

SETTING

Two randomized clinical trials and one multiethnic observational study.

PATIENTS

Patients with spontaneous, nontraumatic intracerebral hemorrhage.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Our exposure of interest was admission hemoglobin levels and the primary outcome was 3-month postintracerebral hemorrhage-dichotomized modified Rankin Scale (0-3 vs 4-6). Intermediate outcomes were admission hematoma volume and hematoma expansion defined as 6 mL or 33% increase in hemorrhage size on repeat CT. A total of 4,172 intracerebral hemorrhage patients were included in the study (mean age 63 [sd = 14]; female sex 1,668 [40%]). Each additional g/dL of admission hemoglobin was associated with 14% (odds ratio, 0.86; 95% CI, 0.82-0.91) and 7% (odds ratio, 0.93; 95% CI, 0.88-0.98) reductions in the risk of poor outcome in unadjusted and adjusted analyses, respectively. Dose-response analyses indicated a linear relationship between admission hemoglobin levels and poor outcome across the entire evaluated range (test-for-trend p < 0.001). No consistent associations were found between the admission hemoglobin levels and hematoma volume or hematoma expansion.

CONCLUSIONS

Higher hemoglobin levels are associated with better outcome in intracerebral hemorrhage. Further research is needed to evaluate admission hemoglobin levels as both a therapeutic target and predictor of outcome.

Nanomedicine Enables Drug-Potency Activation with Tumor Sensitivity and Hyperthermia Synergy in the Second Near-Infrared Biowindow

Disulfiram (DSF), a U.S. Food and Drug Administration (FDA)-approved drug for the treatment of chronic alcoholism, is also used as an antitumor drug in combination with Cu²⁺ ions. However, studies have shown that the endogenous Cu²⁺ dose in tumor tissues is still insufficient to form relatively high levels of a bis(N,N-diethyldithiocarbamate) copper(II) complex (denoted as Cu(DTC)₂) to selectively eradicate cancer cells. Here, DSF-loaded hollow copper sulfide nanoparticles (DSF@PEG-HCuSNPs) were designed to achieve tumor microenvironment (TME)-activated in situ formation of cytotoxic Cu(DTC)₂ for NIR-II-induced, photonic hyperthermia-enhanced, and DSF-initiated cancer chemotherapy. The acidic TME triggered the gradual degradation of DSF@PEG-HCuSNPs, promoting the rapid release of DSF and Cu²⁺ ions, causing the in situ formation of cytotoxic Cu(DTC)₂, to achieve efficient DSF-based chemotherapy. Additionally, DSF@PEG-HCuSNPs exhibited a notably high photothermal conversion efficiency of 23.8% at the second near-infrared (NIR-II) biowindow, thus significantly inducing photonic hyperthermia to eliminate cancer cells. Both in vitro and in vivo studies confirmed the effective photonic hyperthermia-induced chemotherapeutic efficacy of DSF by integrating the in situ formation of toxic Cu(DTC)₂ complexes and evident temperature elevation upon NIR-II laser irradiation. Thus, this study represents a distinctive paradigm of in situ Cu²⁺ chelation-initiated "nontoxicity-to-toxicity" transformation for photonic hyperthermia-augmented DSF-based cancer chemotherapy.

Drug Development for Central Nervous System Diseases Using In vitro Blood-brain Barrier Models and Drug Repositioning

An important goal of biomedical research is to translate basic research findings into practical clinical implementation. Despite the advances in the technology used in drug discovery, the development of drugs for central nervous system diseases remains challenging. The failure rate for new drugs targeting important central nervous system diseases is high compared to most other areas of drug discovery. The main reason for the failure is the poor penetration efficacy across the blood-brain barrier. The blood-brain barrier represents the bottleneck in central nervous system drug development and is the most important factor limiting the future growth of neurotherapeutics. Meanwhile, drug repositioning has been becoming increasingly popular and it seems a promising field in central nervous system drug development. In vitro blood-brain barrier models with high predictability are expected for drug development and drug repositioning. In this review, the recent progress of in vitro BBB models and the drug repositioning for central nervous system diseases will be discussed.

Glutamate transport system as a key constituent of glutamosome: Molecular pathology and pharmacological modulation in chronic pain

Neural uptake of glutamate is executed by the structurally related members of the SLC1A family of solute transporters: GLAST/EAAT1, GLT-1/EAAT2, EAAC1/EAAT3, EAAT4, ASCT2. These plasma membrane proteins ensure supply of glutamate, aspartate and some neutral amino acids, including glutamine and cysteine, for synthetic, energetic and signaling purposes, whereas effective removal of glutamate from the synaptic cleft shapes excitatory neurotransmission and prevents glutamate toxicity. Glutamate transporters (GluTs) possess also receptor-like properties and can directly initiate signal transduction. GluTs are physically linked to other glutamate signaling-, transporting- and metabolizing molecules (e.g., glutamine transporters SNAT3 and ASCT2, glutamine synthetase, NMDA receptor, synaptic vesicles), as well as cellular machineries fueling the transmembrane transport of glutamate (e.g., ion gradient-generating Na/K-ATPase, glycolytic enzymes, mitochondrial membrane- and matrix proteins, glucose transporters). We designate this supramolecular functional assembly as 'glutamosome'. GluTs play important roles in the molecular pathology of chronic pain, due to the predominantly glutamatergic nature of nociceptive signaling in the spinal cord. Down-regulation of GluTs often precedes or occurs simultaneously with development of pain hypersensitivity. Pharmacological inhibition or gene knock-down of spinal GluTs can induce/aggravate pain, whereas enhancing expression of GluTs by viral gene transfer can mitigate chronic pain. Thus, functional up-regulation of GluTs is turning into a prospective pharmacotherapeutic approach for the management of chronic pain. A number of novel positive pharmacological regulators of GluTs, incl. pyridazine derivatives and β-lactams, have recently been introduced. However, design and development of new analgesics based on this principle will require more precise knowledge of molecular mechanisms underlying physiological or aberrant functioning of the glutamate transport system in nociceptive circuits. This article is part of the issue entitled 'Special Issue on Neurotransmitter Transporters'.

In Silico Target Prediction for Small Molecules

Drugs modulate disease states through their actions on targets in the body. Determining these targets aids the focused development of new treatments, and helps to better characterize those already employed. One means of accomplishing this is through the deployment of in silico methodologies, harnessing computational analytical and predictive power to produce educated hypotheses for experimental verification. Here, we provide an overview of the current state of the art, describe some of the well-established methods in detail, and reflect on how they, and emerging technologies promoting the incorporation of complex and heterogeneous data-sets, can be employed to improve our understanding of (poly)pharmacology.

Drug Repurposing for Japanese Encephalitis Virus Infection by Systems Biology Methods

Japanese encephalitis is a zoonotic disease caused by the Japanese encephalitis virus (JEV). It is mainly epidemic in Asia with an estimated 69,000 cases occurring per year. However, no approved agents are available for the treatment of JEV infection, and existing vaccines cannot control various types of JEV strains. Drug repurposing is a new concept for finding new indication of existing drugs, and, recently, the concept has been used to discover new antiviral agents. Identifying host proteins involved in the progress of JEV infection and using these proteins as targets are the center of drug repurposing for JEV infection. In this study, based on the gene expression data of JEV infection and the phenome-wide association study (PheWAS) data, we identified 286 genes that participate in the progress of JEV infection using systems biology methods. The enrichment analysis of these genes suggested that the genes identified by our methods were predominantly related to viral infection pathways and immune response-related pathways. We found that bortezomib, which can target these genes, may have an effect on the treatment of JEV infection. Subsequently, we evaluated the antiviral activity of bortezomib using a JEV-infected mouse model. The results showed that bortezomib can lower JEV-induced lethality in mice, alleviate suffering in JEV-infected mice and reduce the damage in brains caused by JEV infection. This work provides an agent with new indication to treat JEV infection.

Repurposing of Approved Cardiovascular Drugs against Ischemic Cerebrovascular Disease by Disease-Disease Associated Network-Assisted Prediction

Stroke is one of the leading causes of death and disability globally, while intravenous thrombolysis with recombinant tissue plasminogen activator remains the only Food and Drug Administration (FDA)-approved therapy for ischemic stroke. The attempts to develop new treatments for acute ischemic stroke meet costly and spectacularly disappointing results, which requires both long time and high costs, whereas repurposing of safe existing drugs to new indications provides a cost-effective and not time-consuming alternative. Vascular protection is a promising strategy for improving stroke outcome, as vascular function is critical to both cardiovascular diseases (CVD) and ischemic cerebrovascular disease (ICD). Vascular function related biological processes and pathways maybe the critical associations between CVD and ICD. In this study, a multi-database, in silico target identification, gene function enrichment, and network pharmacology analysis integration approach was proposed and applied to investigate the FDA-approved CVD drugs repurposing for ICD. A list of 119 candidate drugs can be obtained for further investigation of their potential in ICD treatment. As a pleiotropic drug with multi-target, carvedilol was set an example to investigate its promising potential for ICD therapy. Our results indicated that the mode of action of carvedilol for ICD treatment may tightly associated with vascular function regulation and the mechanism is multi-target and multi-signaling pathway related. The disease-disease association network-assisted prediction needs further investigations. In summary, the proposed methods herein may provide a promising alternative to inferring novel disease indications for known drugs.

The Combination of Three Components Derived from Sheng MaiSan Protects Myocardial Ischemic Diseases and Inhibits Oxidative Stress via Modulating MAPKs and JAK2-STAT3 Signaling Pathways Based on Bioinformatics Approach

GRS is a drug combination of three components including ginsenoside Rb1, ruscogenin and schisandrin. It derived from the well-known TCM formula Sheng MaiSan, a widely used traditional Chinese medicine for the treatment of cardiovascular diseases in clinic. The present study illuminates its underlying mechanisms against myocardial ischemic diseases based on the combined methods of bioinformatic prediction and experimental verification. A protein database was established through constructing the drug-protein network. And the target-pathway interaction network clustered the potential signaling pathways and targets of GRS in treatment of myocardial ischemic diseases. Several target proteins, such as NFKB1, STAT3 and MAPK14, were identified as the candidate key proteins, and MAPKs and JAK-STAT signaling pathway were suggested as the most related pathways, which were in accordance with the gene ontology analysis. Then, the predictive results were further validated and we found that GRS treatment alleviated hypoxia/reoxygenation (H/R)-induced cardiomyocytes injury via suppression of MDA levels and ROS generation, and potential mechanisms might related to the suppression of activation of MAPKs and JAK2-STAT3 signaling pathways. Conclusively, our results offer the evidence that GRS attenuates myocardial ischemia injury via regulating oxidative stress and MAPKs and JAK2-STAT3 signaling pathways, which supplied some new insights for its prevention and treatment of myocardial ischemia diseases.

The future of psychiatric research

Abstract Psychiatric disorders place considerable burden on individuals and on public health. Funding for research in psychiatry is less than ideal, but even so high quality research is being conducted at many centers. However, these studies have not impacted clinical practice as much as expected. The complexity of psychiatric disorders is one of the reasons why we face difficulties in translating research results to patient care. New technologies and improved methodologies are now available and must be incorporated to deal with this complexity and to accelerate the translational process. I discuss the application of modern techniques for data acquisition and analysis and also the new possibilities for performing trials in virtual models of biological systems. Adoption of new technologies is necessary, but will not reduce the importance of some of the fundamentals of all psychiatry research, such as the developmental and translational perspectives. Psychiatrists wishing to integrate these novelties into their research will need to work with contributors with whom they are unaccustomed to working, such as computer experts, a multidisciplinary team, and stakeholders such as patients and caregivers. This process will allow us to further understand and alleviate the suffering and impairment of people with psychiatric disorders.

'RE:fine drugs': an interactive dashboard to access drug repurposing opportunities

The process of discovering new drugs has been extremely costly and slow in the last decades despite enormous investment in pharmaceutical research. Drug repurposing enables researchers to speed up the process of discovering other conditions that existing drugs can effectively treat, with low cost and fast FDA approval. Here, we introduce ‘RE:fine Drugs’, a freely available interactive website for integrated search and discovery of drug repurposing candidates from GWAS and PheWAS repurposing datasets constructed using previously reported methods in Nature Biotechnology. ‘RE:fine Drugs’ demonstrates the possibilities to identify and prioritize novelty of candidates for drug repurposing based on the theory of transitive Drug–Gene–Disease triads. This public website provides a starting point for research, industry, clinical and regulatory communities to accelerate the investigation and validation of new therapeutic use of old drugs.

Database URL:http://drug-repurposing.nationwidechildrens.org

A Systematic Investigation into Aging Related Genes in Brain and Their Relationship with Alzheimer's Disease

Aging, as a complex biological process, is accompanied by the accumulation of functional loses at different levels, which makes age to be the biggest risk factor to many neurological diseases. Even following decades of investigation, the process of aging is still far from being fully understood, especially at a systematic level. In this study, we identified aging related genes in brain by collecting the ones with sustained and consistent gene expression or DNA methylation changes in the aging process. Functional analysis with Gene Ontology to these genes suggested transcriptional regulators to be the most affected genes in the aging process. Transcription regulation analysis found some transcription factors, especially Specificity Protein 1 (SP1), to play important roles in regulating aging related gene expression. Module-based functional analysis indicated these genes to be associated with many well-known aging related pathways, supporting the validity of our approach to select aging related genes. Finally, we investigated the roles of aging related genes on Alzheimer's Disease (AD). We found that aging and AD related genes both involved some common pathways, which provided a possible explanation why aging made the brain more vulnerable to Alzheimer's Disease.

Alzheimer's as a Systems-Level Disease Involving the Interplay of Multiple Cellular Networks

Alzheimer's disease (AD), and many neurodegenerative disorders, are multifactorial in nature. They involve a combination of genomic, epigenomic, interactomic and environmental factors. Progress is being made, and these complex diseases are beginning to be understood as having their origin in altered states of biological networks at the cellular level. In the case of AD, genomic susceptibility and mechanisms leading to (or accompanying) the impairment of the central Amyloid Precursor Protein (APP) processing and tau networks are widely accepted as major contributors to the diseased state. The derangement of these networks may result in both the gain and loss of functions, increased generation of toxic species (e.g., toxic soluble oligomers and aggregates) and imbalances, whose effects can propagate to supra-cellular levels. Although well sustained by empirical data and widely accepted, this global perspective often overlooks the essential roles played by the main counteracting homeostatic networks (e.g., protein quality control/proteostasis, unfolded protein response, protein folding chaperone networks, disaggregases, ER-associated degradation/ubiquitin proteasome system, endolysosomal network, autophagy, and other stress-protective and clearance networks), whose relevance to AD is just beginning to be fully realized. In this chapter, an integrative perspective is presented. Alzheimer's disease is characterized to be a result of: (a) intrinsic genomic/epigenomic susceptibility and, (b) a continued dynamic interplay between the deranged networks and the central homeostatic networks of nerve cells. This interplay of networks will underlie both the onset and rate of progression of the disease in each individual. Integrative Systems Biology approaches are required to effect its elucidation. Comprehensive Systems Biology experiments at different 'omics levels in simple model organisms, engineered to recapitulate the basic features of AD may illuminate the onset and sequence of events underlying AD. Indeed, studies of models of AD in simple organisms, differentiated cells in culture and rodents are beginning to offer hope that the onset and progression of AD, if detected at an early stage, may be stopped, delayed, or even reversed, by activating or modulating networks involved in proteostasis and the clearance of toxic species. In practice, the incorporation of next-generation neuroimaging, high-throughput and computational approaches are opening the way towards early diagnosis well before irreversible cell death. Thus, the presence or co-occurrence of: (a) accumulation of toxic Aβ oligomers and tau species; (b) altered splicing and transcriptome patterns; (c) impaired redox, proteostatic, and metabolic networks together with, (d) compromised homeostatic capacities may constitute relevant 'AD hallmarks at the cellular level' towards reliable and early diagnosis. From here, preventive lifestyle changes and tailored therapies may be investigated, such as combined strategies aimed at both lowering the production of toxic species and potentiating homeostatic responses, in order to prevent or delay the onset, and arrest, alleviate, or even reverse the progression of the disease.

Learning from the past and looking to the future: Emerging perspectives for improving the treatment of psychiatric disorders

Modern neuropsychopharmacology commenced in the 1950s with the serendipitous discovery of first-generation antipsychotics and antidepressants which were therapeutically effective yet had marked adverse effects. Today, a broader palette of safer and better-tolerated agents is available for helping people that suffer from schizophrenia, depression and other psychiatric disorders, while complementary approaches like psychotherapy also have important roles to play in their treatment, both alone and in association with medication. Nonetheless, despite considerable efforts, current management is still only partially effective, and highly-prevalent psychiatric disorders of the brain continue to represent a huge personal and socio-economic burden. The lack of success in discovering more effective pharmacotherapy has contributed, together with many other factors, to a relative disengagement by pharmaceutical firms from neuropsychiatry. Nonetheless, interest remains high, and partnerships are proliferating with academic centres which are increasingly integrating drug discovery and translational research into their traditional activities. This is, then, a time of transition and an opportune moment to thoroughly survey the field. Accordingly, the present paper, first, chronicles the discovery and development of psychotropic agents, focusing in particular on their mechanisms of action and therapeutic utility, and how problems faced were eventually overcome. Second, it discusses the lessons learned from past successes and failures, and how they are being applied to promote future progress. Third, it comprehensively surveys emerging strategies that are (1), improving our understanding of the diagnosis and classification of psychiatric disorders; (2), deepening knowledge of their underlying risk factors and pathophysiological substrates; (3), refining cellular and animal models for discovery and validation of novel therapeutic agents; (4), improving the design and outcome of clinical trials; (5), moving towards reliable biomarkers of patient subpopulations and medication efficacy and (6), promoting collaborative approaches to innovation by uniting key partners from the regulators, industry and academia to patients. Notwithstanding the challenges ahead, the many changes and ideas articulated herein provide new hope and something of a framework for progress towards the improved prevention and relief of psychiatric and other CNS disorders, an urgent mission for our Century.

DrugNet: network-based drug-disease prioritization by integrating heterogeneous data

OBJECTIVE

Computational drug repositioning can lead to a considerable reduction in cost and time in any drug development process. Recent approaches have addressed the network-based nature of biological information for performing complex prioritization tasks. In this work, we propose a new methodology based on heterogeneous network prioritization that can aid researchers in the drug repositioning process.

METHODS

We have developed DrugNet, a new methodology for drug-disease and disease-drug prioritization. Our approach is based on a network-based prioritization method called ProphNet which has recently been developed by the authors. ProphNet is able to integrate data from complex networks involving a wide range of types of elements and interactions. In this work, we built a network of interconnected drugs, proteins and diseases and applied DrugNet to different types of tests for drug repositioning.

RESULTS

We tested the performance of our approach on different validation tests, including cross validation and tests based on real clinical trials. DrugNet achieved a mean AUC value of 0.9552±0.0015 in 5-fold cross validation tests, and a mean AUC value of 0.8364 for tests based on recent clinical trials (phases 0-4) not present in our data. These results suggest that DrugNet could be very useful for discovering new drug uses. We also studied specific cases of particular interest, proving the benefits of heterogeneous data integration in this problem.

CONCLUSIONS

Our methodology suggests that new drugs can be repositioned by generating ranked lists of drugs based on a given disease query or vice versa. Our study shows that the simultaneous integration of information about diseases, drugs and targets can lead to a significant improvement in drug repositioning tasks. DrugNet is available as a web tool from http://genome2.ugr.es/drugnet/ (accessed 23.09.14). Matlab source code is also available on the website.

Drug repurposing: a better approach for infectious disease drug discovery?

•

Infectious disease investigators need to embrace new drug repurposing approaches.

•

Key components include public databases and predictive computational methods.

•

This approach could significantly reduce cost and time for drug development.

•

Support for large scale drug and disease phenotype screening is essential.

The advent of publicly available databases containing system-wide phenotypic data of the host response to both drugs and pathogens, in conjunction with bioinformatics and computational methods now allows for in silico predictions of FDA-approved drugs as treatments against infection diseases. This systems biology approach captures the complexity of both the pathogen and drug host response in the form of expression patterns or molecular interaction networks without having to understand the underlying mechanisms of action. These drug repurposing techniques have been successful in identifying new drug candidates for several types of cancers and were recently used to identify potential therapeutics against influenza, the newly discovered Middle Eastern Respiratory Syndrome coronavirus and several parasitic diseases. These new approaches have the potential to significantly reduce both the time and cost for infectious diseases drug discovery.

Structure and dynamics of molecular networks: a novel paradigm of drug discovery: a comprehensive review

Despite considerable progress in genome- and proteome-based high-throughput screening methods and in rational drug design, the increase in approved drugs in the past decade did not match the increase of drug development costs. Network description and analysis not only give a systems-level understanding of drug action and disease complexity, but can also help to improve the efficiency of drug design. We give a comprehensive assessment of the analytical tools of network topology and dynamics. The state-of-the-art use of chemical similarity, protein structure, protein-protein interaction, signaling, genetic interaction and metabolic networks in the discovery of drug targets is summarized. We propose that network targeting follows two basic strategies. The "central hit strategy" selectively targets central nodes/edges of the flexible networks of infectious agents or cancer cells to kill them. The "network influence strategy" works against other diseases, where an efficient reconfiguration of rigid networks needs to be achieved by targeting the neighbors of central nodes/edges. It is shown how network techniques can help in the identification of single-target, edgetic, multi-target and allo-network drug target candidates. We review the recent boom in network methods helping hit identification, lead selection optimizing drug efficacy, as well as minimizing side-effects and drug toxicity. Successful network-based drug development strategies are shown through the examples of infections, cancer, metabolic diseases, neurodegenerative diseases and aging. Summarizing >1200 references we suggest an optimized protocol of network-aided drug development, and provide a list of systems-level hallmarks of drug quality. Finally, we highlight network-related drug development trends helping to achieve these hallmarks by a cohesive, global approach.