Genomics and bioinformatics of Parkinson's disease

Inhibition of human and rat placental 3β-hydroxysteroid dehydrogenases by bisphenol A analogues depends on their hydrophobicity: In silico docking analysis

Bisphenol A (BPA) and its analogues are widely used industrial chemicals. Placental 3β-hydroxysteroid dehydrogenases (3β-HSDs) catalyse the conversion of pregnenolone to progesterone. However, the potency of BPA analogues in inhibiting 3β-HSDs activity remains unclear. We investigated the inhibitory effect of 10 BPA analogues on 3β-HSDs activity using an in vitro assay and performed the structure-activity relationship and in silico docking analysis. BPH was the most potent inhibitor of human 3β-HSD1, with an IC50 value of 0.95 μM. BPFL, BPG, DABPA, BPAP, BPZ, DMBPA, and BPB also inhibited human 3β-HSD1 activity, albeit with lower potency. BPG was the most potent inhibitor of rat 3β-HSD4, with an IC50 value of 1.14 μM. BPAP, BPFL, BPG, BPH, BPZ, DABPA, and DMBPA are mixed inhibitors of human 3β-HSD1 and they significantly inhibited human JAr cells to secrete progesterone. The LogP values were inversely correlated with the inhibitory effects. Docking analysis showed that most BPA analogues bind to steroid-binding site of both 3β-HSDs. A pharmacophore containing hydrogen bond donor and hydrophobic region was generated for predicting the inhibitory strength of BPA analogues. In conclusion, this study demonstrates that some BPA analogues are potent inhibitors of 3β-HSDs and lipophilicity determines the inhibitory potency.

Network Analysis Performed on Transcriptomes of Parkinson's Disease Patients Reveals Dysfunction in Protein Translation

Parkinson's disease (PD) is a prevalent neurodegenerative disorder characterized by the progressive degeneration of dopaminergic neurons in the substantia nigra region of the brain. The hallmark pathological feature of PD is the accumulation of misfolded proteins, leading to the formation of intracellular aggregates known as Lewy bodies. Recent data evidenced how disruptions in protein synthesis, folding, and degradation are events commonly observed in PD and may provide information on the molecular background behind its etiopathogenesis. In the present study, we used a publicly available transcriptomic microarray dataset of peripheral blood of PD patients and healthy controls (GSE6613) to investigate the potential dysregulation of elements involved in proteostasis-related processes at the transcriptomic level. Our bioinformatics analysis revealed 375 differentially expressed genes (DEGs), of which 281 were down-regulated and 94 were up-regulated. Network analysis performed on the observed DEGs highlighted a cluster of 36 elements mainly involved in the protein synthesis processes. Different enriched ontologies were related to translation initiation and regulation, ribosome structure, and ribosome components nuclear export. Overall, this data consistently points to a generalized impairment of the translational machinery and proteostasis. Dysregulation of these mechanics has been associated with PD pathogenesis. Understanding the precise regulation of such processes may shed light on the molecular mechanisms of PD and provide potential data for early diagnosis.

Hybrid Pharmacophore- and Structure-Based Virtual Screening Pipeline to Identify Novel EGFR Inhibitors That Suppress Non-Small Cell Lung Cancer Cell Growth

Dysregulated epidermal growth factor receptor (EGFR) expression is frequently observed in non-small cell lung cancer (NSCLC) growth and metastasis. Despite recent successes in the development of tyrosine kinase inhibitors (TKIs), inevitable resistance to TKIs has led to urgent calls for novel EGFR inhibitors. Herein, we report a rational workflow used to identify novel EGFR-TKIs by combining hybrid ligand- and structure-based pharmacophore models. Three types of models were developed in this workflow, including 3D QSAR-, common feature-, and structure-based EGFR-TK domain-containing pharmacophores. A National Cancer Institute (NCI) compound dataset was adopted for multiple-stage pharmacophore-based virtual screening (PBVS) of various pharmacophore models. The six top-scoring compounds were identified through the PBVS pipeline coupled with molecular docking. Among these compounds, NSC609077 exerted a significant inhibitory effect on EGFR activity in gefitinib-resistant H1975 cells, as determined by an enzyme-linked immunosorbent assay (ELISA). Further investigations showed that NSC609077 inhibited the anchorage-dependent growth and migration of lung cancer cells. Furthermore, NSC609077 exerted a suppressive effect on the EGFR/PI3K/AKT pathway in H1975 cells. In conclusion, these findings suggest that hybrid virtual screening may accelerate the development of targeted drugs for lung cancer treatment.

Pharmacophore-based virtual screening for the identification of the novel Src inhibitor SJG-136 against lung cancer cell growth and motility

Aberrant elevated Src activity is related to lung cancer growth and metastasis. Therefore, the development of potent small molecule inhibitors to target Src kinase is a potential therapeutic strategy for lung cancer. This study aimed to develop a computational model for the in silico screening of Src inhibitors and then assess the suppressive effect of candidate compounds on cellular functions. A 3D-quantitative structure-activity relationship (QSAR) pharmacophore model consisting of two hydrogen bond acceptors and two hydrophobic regions was constructed by using 28 structurally diverse compounds with IC50 values spanning four orders of magnitude. A National Cancer Institute (NCI) compound dataset was employed for virtual screening by applying the pharmacophore model and molecular docking. Candidate compounds were chosen from the top 20% of scored hits. Among these compounds, the suppressive effects of 30 compounds available in the NCI on Src phosphorylation were validated by using an enzyme-linked immunosorbent assay. Among these compounds, SJG-136, a pyrrolobenzodiazepine dimer, showed a significant inhibitory effect against Src activity in a dose-dependent manner. Further investigations showed that SJG-136 can inhibit lung cancer cell proliferation, clonogenicity, invasion and migration in vitro and tumour growth in vivo. Furthermore, SJG-136 also had an inhibitory effect on Src-related signaling pathways, including the FAK, paxillin, p130Cas, PI3K, AKT, and MEK pathways. In conclusion, we have established a pharmacophore-based virtual screening approach to identify novel Src inhibitors that can inhibit lung cancer cell growth and motility through suppressing Src-related pathways. These findings may contribute to the development of targeted drugs for lung cancer treatment, such as lead compounds.

The Challenge to Search for New Nervous System Disease Biomarker Candidates: the Opportunity to Use the Proteogenomics Approach

Alzheimer's disease, Parkinson's disease, prion diseases, schizophrenia, and multiple sclerosis are the most common nervous system diseases, affecting millions of people worldwide. The current scientific literature associates these pathological conditions to abnormal expression levels of certain proteins, which in turn improved the knowledge concerning normal and affected brains. However, there is no available cure or preventive therapy for any of these disorders. Proteogenomics is a recent approach defined as the data integration of both nucleotide high-throughput sequencing and protein mass spectrometry technologies. In the last years, proteogenomics studies in distinct diseases have emerged as a strategy for the identification of uncharacterized proteoforms, which are all the different protein forms derived from a single gene. For many of these diseases, at least one protein used as biomarker presents more than one proteoform, which fosters the analysis of publicly available data focusing proteoforms. Given this context, we describe the most important biomarkers for each neurodegenerative disease and how genomics, transcriptomics, and proteomics separately contributed to unveil them. Finally, we present a selection of proteogenomics studies in which the combination of nucleotide and proteome high-throughput data, from cell lines or brain tissue samples, is used to uncover proteoforms not previously described. We believe that this new approach may improve our knowledge about nervous system diseases and brain function and an opportunity to identify new biomarker candidates.

Spatial perspectives in the redox code-Mass spectrometric proteomics studies of moonlighting proteins

The Redox Code involves specific, reversible oxidative changes in proteins that modulate protein tertiary structure, interactions, trafficking, and activity, and hence couple the proteome to the metabolic/oxidative state of cells. It is currently a major focus of study in cell biology. Recent studies of dynamic cellular spatial reorganization with MS-based subcellular-spatial-razor proteomics reveal that protein constituents of many subcellular structures, including mitochondria, the endoplasmic reticulum, the plasma membrane, and the extracellular matrix, undergo changes in their subcellular abundance/distribution in response to oxidative stress. These proteins are components of a diverse variety of functional processes spatially distributed across cells. Many of the same proteins are involved in response to suppression of DNA replication indicate that oxidative stress is strongly intertwined with DNA replication/proliferation. Both are replete with networks of moonlighting proteins that show coordinated changes in subcellular location and that include primary protein actuators of the redox code involved in the processing of NAD⁺ /NADH, NADP⁺ /NADPH, Cys/CySS, and GSH/GSSG redox couples. Small groups of key proteins such as {KPNA2, KPNB1, PCNA, PTMA, SET} constitute "spatial switches" that modulate many nuclear processes. Much of the functional response involves subcellular protein trafficking, including nuclear import/export processes, vesicle-mediated trafficking, the endoplasmic reticulum/Golgi pathway, chaperone-assisted processes, and other transport systems. This is not visible to measurements of total protein abundance by transcriptomics or proteomics. Comprehensive pictures of cellular function will require collection of data on the subcellular transport and local functions of many moonlighting proteins, especially of those with critical roles in spatial coordination across cells. The proteome-wide analysis of coordinated changes in abundance and trafficking of proteins offered by MS-based proteomics has a unique, crucial role to play in deciphering the complex adaptive systems that underlie cellular function. © 2016 Wiley Periodicals, Inc. Mass Spec Rev.

Regional analysis and genetic association of nigrostriatal degeneration in Lewy body disease

BACKGROUND

A number of genetic loci are associated with risk for Parkinson's disease (PD) based on genome-wide association studies; however, the relationship between genetic variants and nigrostriatal degeneration, which is the structural correlate of parkinsonism, has not been reported.

OBJECTIVES

We quantified nigrostriatal dopaminergic integrity with image analysis of putaminal tyrosine hydroxylase immunoreactivity in 492 brains with Lewy body disease and used this pathologic endophenotype to explore possible association with PD genetic variants.

METHODS

The study cases had Lewy-related pathology and variable degrees of nigrostriatal degeneration. They were assigned to one of the following clinical subgroups according to their predominant clinical syndrome: parkinsonism-predominant, parkinsonism+dementia, and dementia-predominant. In addition to putaminal tyrosine hydroxylase immunoreactivity, semiquantitative scoring was used to assess substantia nigra neuronal loss. A total of 29 PD genetic risk variants were genotyped on each case.

RESULTS

When compared with controls, tyrosine hydroxylase immunoreactivity was reduced in Lewy body cases in the dorsolateral (79%) and ventromedial (57%) putamen. The dorsolateral region was better preserved in dementia-predominant cases than in cases with parkinsonism. Dorsolateral putaminal tyrosine hydroxylase immunoreactivity correlated with neuronal loss in the ventrolateral substantia nigra. Genetic analyses showed no significant association of PD risk variants with putaminal tyrosine hydroxylase immunoreactivity.

CONCLUSIONS

The results confirm regional differences in putaminal dopaminergic degeneration and vulnerability of nigrostriatal pathway in Lewy body disorders with parkinsonism. The lack of association with PD genetic risk variants suggests that they may not be associated with quantitative endophenotypes of nigrostriatal degeneration, but more likely related to the risk of disease per se. © 2017 International Parkinson and Movement Disorder Society.

The genetic background of Parkinson's disease: current progress and future prospects

Almost two decades of genetic research in Parkinson's disease (PD) have remarkably increased our knowledge regarding the genetic basis of PD with numerous genes and genetic loci having been found to cause familial PD or affect the risk for PD. Approximately 5-10% of PD patients have monogenic forms of the disease, exhibiting a classical Mendelian type of inheritance, however, the majority PD cases are sporadic, probably caused by a combination of genetic and environmental risk factors. Nowadays, six genes, alpha synuclein, LRRK2, VPS35, Parkin, PINK1 and DJ-1, have definitely been associated with an autosomal dominant or recessive PD mode of inheritance. The advent of genome-wide association studies (GWAS) and the implementation of new technologies, like next generation sequencing (NGS) and exome sequencing has undoubtedly greatly aided the identification on novel risk variants for sporadic PD. In this review, we will summarize the current progress and future prospects in the field of PD genetics.

PDON: Parkinson's disease ontology for representation and modeling of the Parkinson's disease knowledge domain

BACKGROUND

Despite the unprecedented and increasing amount of data, relatively little progress has been made in molecular characterization of mechanisms underlying Parkinson's disease. In the area of Parkinson's research, there is a pressing need to integrate various pieces of information into a meaningful context of presumed disease mechanism(s). Disease ontologies provide a novel means for organizing, integrating, and standardizing the knowledge domains specific to disease in a compact, formalized and computer-readable form and serve as a reference for knowledge exchange or systems modeling of disease mechanism.

METHODS

The Parkinson's disease ontology was built according to the life cycle of ontology building. Structural, functional, and expert evaluation of the ontology was performed to ensure the quality and usability of the ontology. A novelty metric has been introduced to measure the gain of new knowledge using the ontology. Finally, a cause-and-effect model was built around PINK1 and two gene expression studies from the Gene Expression Omnibus database were re-annotated to demonstrate the usability of the ontology.

RESULTS

The Parkinson's disease ontology with a subclass-based taxonomic hierarchy covers the broad spectrum of major biomedical concepts from molecular to clinical features of the disease, and also reflects different views on disease features held by molecular biologists, clinicians and drug developers. The current version of the ontology contains 632 concepts, which are organized under nine views. The structural evaluation showed the balanced dispersion of concept classes throughout the ontology. The functional evaluation demonstrated that the ontology-driven literature search could gain novel knowledge not present in the reference Parkinson's knowledge map. The ontology was able to answer specific questions related to Parkinson's when evaluated by experts. Finally, the added value of the Parkinson's disease ontology is demonstrated by ontology-driven modeling of PINK1 and re-annotation of gene expression datasets relevant to Parkinson's disease.

CONCLUSIONS

Parkinson's disease ontology delivers the knowledge domain of Parkinson's disease in a compact, computer-readable form, which can be further edited and enriched by the scientific community and also to be used to construct, represent and automatically extend Parkinson's-related computable models. A practical version of the Parkinson's disease ontology for browsing and editing can be publicly accessed at http://bioportal.bioontology.org/ontologies/PDON .

Compensatory mechanisms in genetic models of neurodegeneration: are the mice better than humans?

Neurodegenerative diseases are one of the main causes of mental and physical disabilities. Neurodegeneration has been estimated to begin many years before the first clinical symptoms manifest, and even a prompt diagnosis at this stage provides very little advantage for a more effective treatment as the currently available pharmacotherapies are based on disease symptomatology. The etiology of the majority of neurodegenerative diseases remains unknown, and even for those diseases caused by identified genetic mutations, the direct pathways from gene alteration to final cell death have not yet been fully elucidated. Advancements in genetic engineering have provided many transgenic mice that are used as an alternative to pharmacological models of neurodegenerative diseases. Surprisingly, even the models reiterating the same causative mutations do not fully recapitulate the inevitable neuronal loss, and some fail to even show phenotypic alterations, which suggests the possible existence of compensatory mechanisms. A better evaluation of these mechanisms may not only help us to explain why neurodegenerative diseases are mostly late-onset disorders in humans but may also provide new markers and targets for novel strategies designed to extend neuronal function and survival. The aim of this mini-review is to draw attention to this under-explored field in which investigations may reasonably contribute to unveiling hidden reserves in the organism.

Biomarkers of Parkinson's disease: present and future

Sporadic or idiopathic Parkinson's disease (PD) is an age-related neurodegenerative disorder of unknown origin that ranks only second behind Alzheimer's disease (AD) in prevalence and its consequent social and economic burden. PD neuropathology is characterized by a selective loss of dopaminergic neurons in the substantia nigra pars compacta; however, more widespread involvement of other CNS structures and peripheral tissues now is widely documented. The onset of molecular and cellular neuropathology of PD likely occurs decades before the onset of the motor symptoms characteristic of PD. The hallmark symptoms of PD, resting tremors, rigidity and postural disabilities, are related to dopamine (DA) deficiency. Current therapies treat these symptoms by replacing or boosting existing DA. All current interventions have limited therapeutic benefit for disease progression because damage likely has progressed over an estimated period of ~5 to 15years to a loss of 60%-80% of the nigral DA neurons, before symptoms emerge. There is no accepted definitive biomarker of PD. An urgent need exists to develop early diagnostic biomarkers for two reasons: (1) to intervene at the onset of disease and (2) to monitor the progress of therapeutic interventions that may slow or stop the course of the disease. In the context of disease development, one of the promises of personalized medicine is the ability to predict, on an individual basis, factors contributing to the susceptibility for the development of a given disease. Recent advances in our understanding of genetic factors underlying or contributing to PD offer the potential for monitoring susceptibility biomarkers that can be used to identify at-risk individuals and possibly prevent the onset of disease through treatment. Finally, the exposome concept is new in the biomarker discovery arena and it is suggested as a way to move forward in identifying biomarkers of neurological diseases. It is a two-stage scheme involving a first stage of exposome-wide association studies (EWAS) to profile omic features in serum to discover molecular biomarkers. The second stage involves application of this knowledge base in follow-up studies. This strategy is unique in that it promotes the use of data-driven (omic) strategies in interrogating diseased and healthy populations and encourages a movement away from using only reductionist strategies to discover biomarkers of exposure and disease. In this short review we will examine 1) advances in our understanding of the molecular mechanisms underlying PD that have led to candidate biomarkers for diagnosis and treatment efficacy and 2) new technologies on the horizon that will lead to novel approaches in biomarker development.

Proteomics reveals the importance of the dynamic redistribution of the subcellular location of proteins in breast cancer cells

At the molecular level, living cells are enormously complicated complex adaptive systems in which intertwined genomic, transcriptomic, proteomic and metabolic networks all play a crucial role. At the same time, cells are spatially heterogeneous systems in which subcellular compartmentalization of different functions is ubiquitous and requires efficient cross-compartmental communication. Dynamic redistribution of multitudinous proteins to different subcellular locations in response to cellular functional state is increasingly recognized as a crucial characteristic of cellular function that seems to be at least as important as overall changes in protein abundance. Characterization of the subcellular spatial dynamics of protein distribution is a major challenge for proteomics and recent results with MCF7 breast cancer cells suggest that this may be of particular importance for cancer cells.

Complex network-driven view of genomic mechanisms underlying Parkinson's disease: analyses in dorsal motor vagal nucleus, locus coeruleus, and substantia nigra

Parkinson's disease (PD)—classically characterized by severe loss of dopaminergic neurons in the substantia nigra pars compacta—has a caudal-rostral progression, beginning in the dorsal motor vagal nucleus and, in a less extent, in the olfactory system, progressing to the midbrain and eventually to the basal forebrain and the neocortex. About 90% of the cases are idiopathic. To study the molecular mechanisms involved in idiopathic PD we conducted a comparative study of transcriptional interaction networks in the dorsal motor vagal nucleus (VA), locus coeruleus (LC), and substantia nigra (SN) of idiopathic PD in Braak stages 4-5 (PD) and disease-free controls (CT) using postmortem samples. Gene coexpression networks (GCNs) for each brain region (patients and controls) were obtained to identify highly connected relevant genes (hubs) and densely interconnected gene sets (modules). GCN analyses showed differences in topology and module composition between CT and PD networks for each anatomic region. In CT networks, VA, LC, and SN hub modules are predominantly associated with neuroprotection and homeostasis in the ageing brain, whereas in the patient's group, for the three brain regions, hub modules are mostly related to stress response and neuron survival/degeneration mechanisms.

Animal models of neurodegenerative diseases

The prevalence of neurodegenerative diseases, such as Alzheimer's disease (AD) and Parkinson's disease (PD), increases with age, and the number of affected patients is expected to increase worldwide in the next decades. Accurately understanding the etiopathogenic mechanisms of these diseases is a crucial step for developing disease-modifying drugs able to preclude their emergence or at least slow their progression. Animal models contribute to increase the knowledge on the pathophysiology of neurodegenerative diseases. These models reproduce different aspects of a given disease, as well as the histopathological lesions and its main symptoms. The purpose of this review is to present the main animal models for AD, PD, and Huntington's disease.

Proteomics in immunity and herpes simplex encephalitis

The genetic theory of infectious diseases has proposed that susceptibility to life-threatening infectious diseases in childhood, occurring in the course of primary infection, results mostly from individually rare but collectively diverse single-gene variants. Recent evidence of an ever-expanding spectrum of genes involved in susceptibility to infectious disease indicates that the paradigm has important implications for diagnosis and treatment. One such pathology is childhood herpes simplex encephalitis, which shows a pattern of rare but diverse disease-disposing genetic variants. The present report shows how proteomics can help to understand susceptibility to childhood herpes simplex encephalitis and other viral infections, suggests that proteomics may have a particularly important role to play, emphasizes that variation over the population is a critical issue for proteomics and notes some new challenges for proteomics and related bioinformatics tools in the context of rare but diverse genetic defects.

Parkinson's disease

Parkinson's disease (PD) is the most common age-related motoric neurodegenerative disease initially described in the 1800's by James Parkinson as the 'Shaking Palsy'. Loss of the neurotransmitter dopamine was recognized as underlying the pathophysiology of the motor dysfunction; subsequently discovery of dopamine replacement therapies brought substantial symptomatic benefit to PD patients. However, these therapies do not fully treat the clinical syndrome nor do they alter the natural history of this disorder motivating clinicians and researchers to further investigate the clinical phenotype, pathophysiology/pathobiology and etiology of this devastating disease. Although the exact cause of sporadic PD remains enigmatic studies of familial and rare toxicant forms of this disorder have laid the foundation for genome wide explorations and environmental studies. The combination of methodical clinical evaluation, systematic pathological studies and detailed genetic analyses have revealed that PD is a multifaceted disorder with a wide-range of clinical symptoms and pathology that include regions outside the dopamine system. One common thread in PD is the presence of intracytoplasmic inclusions that contain the protein, α-synuclein. The presence of toxic aggregated forms of α-synuclein (e.g., amyloid structures) are purported to be a harbinger of subsequent pathology. In fact, PD is both a cerebral amyloid disease and the most common synucleinopathy, that is, diseases that display accumulations of α-synuclein. Here we present our current understanding of PD etiology, pathology, clinical symptoms and therapeutic approaches with an emphasis on misfolded α-synuclein.