Modulation of neuronal proteome profile in response to Japanese Encephalitis Virus infection

In this study we have reported the in vivo proteomic changes during Japanese Encephalitis Virus (JEV) infection in combination with in vitro studies which will help in the comprehensive characterization of the modifications in the host metabolism in response to JEV infection. We performed a 2-DE based quantitative proteomic study of JEV-infected mouse brain as well as mouse neuroblastoma (Neuro2a) cells to analyze the host response to this lethal virus. 56 host proteins were found to be differentially expressed post JEV infection (defined as exhibiting ≥1.5-fold change in protein abundance upon JEV infection). Bioinformatics analyses were used to generate JEV-regulated host response networks which reported that the identified proteins were found to be associated with various cellular processes ranging from intracellular protein transport, cellular metabolism and ER stress associated unfolded protein response. JEV was found to invade the host protein folding machinery to sustain its survival and replication inside the host thereby generating a vigorous unfolded protein response, subsequently triggering a number of pathways responsible for the JEV associated pathologies. The results were also validated using a human cell line to correlate them to the human response to JEV. The present investigation is the first report on JEV-host interactome in in vivo model and will be of potential interest for future antiviral research in this field

Colorectal cancer cell line proteomes are representative of primary tumors and predict drug sensitivity

Proteomics holds promise for individualizing cancer treatment. We analyzed to what extent the proteomic landscape of human colorectal cancer (CRC) is maintained in established CRC cell lines and the utility of proteomics for predicting therapeutic responses. Proteomic and transcriptomic analyses were performed on 44 CRC cell lines, compared against primary CRCs (n=95) and normal tissues (n=60), and integrated with genomic and drug sensitivity data. Cell lines mirrored the proteomic aberrations of primary tumors, in particular for intrinsic programs. Tumor relationships of protein expression with DNA copy number aberrations and signatures of post-transcriptional regulation were recapitulated in cell lines. The 5 proteomic subtypes previously identified in tumors were represented among cell lines. Nonetheless, systematic differences between cell line and tumor proteomes were apparent, attributable to stroma, extrinsic signaling, and growth conditions. Contribution of tumor stroma obscured signatures of DNA mismatch repair identified in cell lines with a hypermutation phenotype. Global proteomic data showed improved utility for predicting both known drug-target relationships and overall drug sensitivity as compared with genomic or transcriptomic measurements. Inhibition of targetable proteins associated with drug responses further identified corresponding synergistic or antagonistic drug combinations. Our data provide evidence for CRC proteomic subtype-specific drug responses. Proteomes of established CRC cell line are representative of primary tumors. Proteomic data tend to exhibit improved prediction of drug sensitivity as compared with genomic and transcriptomic profiles. Our integrative proteogenomic analysis highlights the potential of proteome profiling to inform personalized cancer medicine

Mechanisms of Loss of Functions of Human Angiogenin Variants Implicated in Amyotrophic Lateral Sclerosis

Background: Mutations in the coding region of angiogenin (ANG) gene have been found in patients suffering from Amyotrophic Lateral Sclerosis (ALS). Neurodegeneration results from the loss of angiogenic ability of ANG (protein coded by ANG). In this work, we performed extensive molecular dynamics (MD) simulations of wild-type ANG and disease associated ANG variants to elucidate the mechanism behind the loss of ribonucleolytic activity and nuclear translocation activity, functions needed for angiogenesis. Methodology/Principal Findings: MD simulations were carried out to study the structural and dynamic differences in the catalytic site and nuclear localization signal residues between WT-ANG (Wild-type ANG) and six mutants. Variants K17I, S28N, P112L and V113I have confirmed association with ALS, while T195C and A238G single nucleotide polymorphisms (SNPs) encoding L35P and K60E mutants respectively, have not been associated with ALS. Our results show that loss of ribonucleolytic activity in K17I is caused by conformational switching of the catalytic residue His114 by 99u. The loss of nuclear translocation activity of S28N and P112L is caused by changes in the folding of the residues 31 RRR 33 that result in the reduction in solvent accessible surface area (SASA). Consequently, we predict that V113I will exhibit loss of angiogenic properties by loss of nuclear translocation activity and L35P by loss of both ribonucleolytic activity and nuclear translocation activity. No functional loss was inferred for K60E. The MD simulation results were supported by hydrogen bond interactio

DLAD4U: deriving and prioritizing disease lists from PubMed literature

Abstract Background Due to recent technology advancements, disease related knowledge is growing rapidly. It becomes nontrivial to go through all published literature to identify associations between human diseases and genetic, environmental, and life style factors, disease symptoms, and treatment strategies. Here we report DLAD4U (Disease List Automatically Derived For You), an efficient, accurate and easy-to-use disease search engine based on PubMed literature. Results DLAD4U uses the eSearch and eFetch APIs from the National Center for Biotechnology Information (NCBI) to find publications related to a query and to identify diseases from the retrieved publications. The hypergeometric test was used to prioritize identified diseases for displaying to users. DLAD4U accepts any valid queries for PubMed, and the output results include a ranked disease list, information associated with each disease, chronologically-ordered supporting publications, a summary of the run, and links for file export. DLAD4U outperformed other disease search engines in our comparative evaluation using selected genes and drugs as query terms and manually curated data as “gold standard”. For 100 genes that are associated with only one disease in the gold standard, the Mean Average Precision (MAP) measure from DLAD4U was 0.77, which clearly outperformed other tools. For 10 genes that are associated with multiple diseases in the gold standard, the mean precision, recall and F-measure scores from DLAD4U were always higher than those from other tools. The superior performance of DLAD4U was further confirmed using 100 drugs as queries, with an MAP of 0.90. Conclusions DLAD4U is a new, intuitive disease search engine that takes advantage of existing resources at NCBI to provide computational efficiency and uses statistical analyses to ensure accuracy. DLAD4U is publicly available at http://dlad4u.zhang-lab.org

A landscape of nanomedicine innovations in India

Nanomedicine is one of the emerging technologies and a branch of nanotechnology finding applications in healthcare. Many countries, including India, are pursuing active research programs in nanomedicine to explore novel healthcare solutions to address specific healthcare needs of the society. At present, the government of India, through its various agencies, is funding nanomedicine research in India. It is anticipated that in the next 5 years or so, several nanomedicine-based products shall reach the market. Thereby, it becomes pertinent to evaluate the extent of India’s involvement in activities related to innovation in nanomedicine. However, a comprehensive landscape of nanomedicine innovation in India is currently lacking. This paper attempts to profile the status of research and innovation in the field of nanomedicine in India. The current study evaluates the innovation on the basis of five indicators: financial ecosystem, technology source, research translation, bibliographic data (patents and publications), and regulation. Public-private partnerships and international collaborations are also discussed in the paper. The landscape elucidates current status of nanomedicine in India and may be relevant for policy-related matters

A Computational Analysis of Multiple Sclerosis Using Protein-Protein Interaction Network

Multiple Sclerosis (MS) is an inflammatory-mediated demyelinating disease and a major cause of non-traumatic irreversible neurological disability. The underlying mechanisms by which these complications arise, remains poorly understood. Recent data suggests that alterations in genes or environmental factors directly or indirectly alter protein function, signalling cascade and thus contribute to variation in disease susceptibility. With the accumulation of high throughput data, a systematic analysis of the interaction and crosstalk between underlying pathways is important for understanding pathogenesis of such a complex disease. This study is based on the enrichment analysis of disease network for determination of functional clusters that exhibit high correlation with abnormalities in immune response and neuronal signalling. Our results show that interrogation of protein-protein interaction networks can help elucidate mechanisms underlying complex diseases

Complementary Approaches to Existing Target Based Drug Discovery for Identifying Novel Drug Targets

In the past decade, it was observed that the relationship between the emerging New Molecular Entities and the quantum of R&D investment has not been favorable. There might be numerous reasons but few studies stress the introduction of target based drug discovery approach as one of the factors. Although a number of drugs have been developed with an emphasis on a single protein target, yet identification of valid target is complex. The approach focuses on an in vitro single target, which overlooks the complexity of cell and makes process of validation drug targets uncertain. Thus, it is imperative to search for alternatives rather than looking at success stories of target-based drug discovery. It would be beneficial if the drugs were developed to target multiple components. New approaches like reverse engineering and translational research need to take into account both system and target-based approach. This review evaluates the strengths and limitations of known drug discovery approaches and proposes alternative approaches for increasing efficiency against treatment

Relative fold change in differentially expressed proteins in brain tissue post-JEV infection.

<p>Spot intensities were normalized by total valid spot intensities and mean of values from duplicate analytical gels from four biological replicates were subjected to paired <i>t</i>-test analysis. Protein spots showing altered expression between control and experimental groups (|ratio|≥1.5, <i>p</i><0.05) were marked and excised. Dark grey bars indicate spots from mock infected control sample while light grey bars indicate JEV infected sample. * = p<0.05, # = p<0.01. Data represented are means ± SD of four independent experiments.</p

Comparison of AutoDock and ParDOCK binding energy scores for NCI-65828 complexes with WT-ANG and ANG mutants.

<p>*(ANG in which there is no conformational change of the catalytic residue His114).</p