Human Proteinpedia as a Resource for Clinical Proteomics

Institute of Bioinformatics, International Tech Park, Bangalore 560 066, India.
Molecular &amp Cellular Proteomics (Impact Factor: 6.56). 07/2008; 7(10):2038-47. DOI: 10.1074/mcp.R800008-MCP200
Source: PubMed


Clinical proteomics is an emerging field that deals with the use of proteomic technologies for medical applications. With a major objective of identifying proteins involved in pathological processes and as potential biomarkers, this field is already gaining momentum. Consequently, clinical proteomics data are being generated at a rapid pace, although mechanisms of sharing such data with the biomedical community lag far behind. Most of these data are either provided as supplementary information through journal web sites or directly made available by the authors through their own web resources. Integration of these data within a single resource that displays information in the context of individual proteins is likely to enhance the use of proteomic data in biomedical research. Human Proteinpedia is one such portal that unifies human proteomic data under a single banner. The goal of this resource is to ultimately capture and integrate all proteomic data obtained from individual studies on normal and diseased tissues. We anticipate that harnessing of these data will help prioritize experiments related to protein targets and also permit meta-analysis to uncover molecular signatures of disease. Finally, we encourage all biomedical investigators to maximize dissemination of their valuable proteomic data to rest of the community by active participation in existing repositories such as Human Proteinpedia.

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    • "Processed data and the search results including the detailed protein/peptide data can be downloaded from our own resource called the Human Proteinpedia ( [74]. "
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    ABSTRACT: Arthritis refers to inflammation of joints and includes common disorders such as rheumatoid arthritis (RA) and spondyloarthropathies (SpAs). These diseases differ mainly in terms of their clinical manifestations and the underlying pathogenesis. Glycoproteins in synovial fluid might reflect the disease activity status in the joints affected by arthritis; yet they have not been systematically studied previously. Although markers have been described for assisting in the diagnosis of RA, there are currently no known biomarkers for SpA.Materials and methods: We sought to determine the relative abundance of glycoproteins in RA and SpA by lectin affinity chromatography coupled to iTRAQ labeling and LC-MS/MS analysis. We also used ELISA to validate the overexpression of VCAM-1, one of the candidate proteins identified in this study, in synovial fluid from RA patients. We identified proteins that were previously reported to be overexpressed in RA including metalloproteinase inhibitor 1 (TIMP1), myeloperoxidase (MPO) and several S100 proteins. In addition, we discovered several novel candidates that were overexpressed in SpA including Apolipoproteins C-II and C-III and the SUN domain-containing protein 3 (SUN3). Novel molecules found overexpressed in RA included extracellular matrix protein 1 (ECM1) and lumican (LUM). We validated one of the candidate biomarkers, vascular cell adhesion molecule 1 (VCAM1), in 20 RA and SpA samples using ELISA and confirmed its overexpression in RA (p-value <0.01). Our quantitative glycoproteomic approach to study arthritic disorders should open up new avenues for additional proteomics-based discovery studies in rheumatological disorders.
    Clinical Proteomics 09/2013; 10(1):11. DOI:10.1186/1559-0275-10-11
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    • "As a consequence, 2695 MS/MS results have been accumulated in Proteinpedia ( (29,30). Besides PTM, protein mutations can also be identified from the MS/MS results because they have slightly different amino acids compared to the normal proteins, which can make MS peaks shift (31). "
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    ABSTRACT: Some mutations resulting in protein sequence change might be tightly related to certain human diseases by affecting its roles, such as sickle cell anemia. Until now several databases, such as PMD, OMIM and HGMD, have been developed, providing useful information about human disease-related mutation. Tandem mass spectrometry (MS) has been used for characterizing proteins in various conditions; however, there is no system in place for finding disease-related mutated proteins within the MS results. Here, a Systematical Platform for Identifying Mutated Proteins (SysPIMP; was developed to efficiently identify human disease-related mutated proteins within MS results. SysPIMP comprises of three layers: (i) a standardized data warehouse, (ii) a pipeline layer for maintaining human disease databases and X!Tandem and BLAST and (iii) a web-based interface. From OMIM AV part, PMD and SwissProt databases, 35,497 non-redundant human disease-related mutated sequences were collected with disease information described by OMIM terms. With the interfaces to browse sequences archived in SysPIMP, X!Tandem, an open source database-search engine used to identify proteins within MS data, was integrated into SysPIMP to help support the detection of potential human disease-related mutants in MS results. In addition, together with non-redundant disease-related mutated sequences, original non-mutated sequences are also provided in SysPIMP for comparative research. Based on this system, SysPIMP will be the platform for efficiently and intensively studying human diseases caused by mutation.
    Nucleic Acids Research 12/2008; 37(Database issue):D913-20. DOI:10.1093/nar/gkn848 · 9.11 Impact Factor
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    • "Protein profiling can be performed on complex peptide or protein mixtures from whole or partially fractionated tissue extracts or biofluids such as serum (Gagnon et al., 2008; Cazares et al., 2008; Lopez et al., 2007), urine and cerebrospinal fluid, or directly on thin tissue sections (Chaurand et al., 2004; Yanagisawa et al., 2003). For the antibody-based profiling, the antibodies against predetermined protein lists that are important in a given biological process, pathway or clinical outcome are used to determine the protein signatures (Tong et al., 2008; Mathivanan and Pandey, 2008; Wang et al., 2005). The negative aspects of antibody-based Proteomics are that the assay is limited by the availability of antibodies and the need for having the prior knowledge of proteins of interest. "
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    ABSTRACT: The advent of functional genomics has been greatly broadening our view and accelerating our way in numerous medical research fields. The complete genomic data acquired from the human genome project and the desperate clinical need of comprehensive analytical tools to study complex diseases, has allowed rapid evolution of genomic and proteomic technologies, speeding the rate and number of discoveries in new biomarkers. By jointly using genomics, proteomics and bioinformatics there is a great potential to make considerable contribution to biomarker identification and to revolutionize both the development of new therapies and drug development process.
    Toxicology Letters 11/2008; 186(1):45-51. DOI:10.1016/j.toxlet.2008.10.014 · 3.26 Impact Factor
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