ArticleProteome science2013
HMPAS: Human Membrane Protein Analysis System.
Article in Proteome science, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 10 citations in OpenAlex.
- VARIDT 3.0: the phenotypic and regulatory variability of drug transporter.Nucleic acids research · 2024Article
- VARIDT 2.0: structural variability of drug transporter.Nucleic acids research · 2022Article
- The Cancer Surfaceome Atlas integrates genomic, functional and drug response data to identify actionable targets.Nature cancer · 2021Article
- Guardians of the Cell: State-of-the-Art of Membrane Proteins from a Computational Point-of-View.Methods in molecular biology (Clifton, N.J.) · 2021Article
- VARIDT 1.0: variability of drug transporter database.Nucleic acids research · 2020Article
- Plasma Exosome Profiling of Cancer Patients by a Next Generation Systems Biology Approach.Scientific reports · 2017Article
- The human transmembrane proteome.Biology direct · 2015Article
- SCMMTP: identifying and characterizing membrane transport proteins using propensity scores of dipeptides.BMC genomics · 2015Article
Corrections and comments
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Authors and funding
2 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMembrane proteins perform essential roles in diverse cellular functions and are regarded as major pharmaceutical targets. The significance of membrane proteins has led to the developing dozens of resources related with membrane proteins. However, most of these resources are built for specific well-known membrane protein groups, making it difficult to find common and specific features of various membrane protein groups.
methodsWe collected human membrane proteins from the dispersed resources and predicted novel membrane protein candidates by using ortholog information and our membrane protein classifiers. The membrane proteins were classified according to the type of interaction with the membrane, subcellular localization, and molecular function. We also made new feature dataset to characterize the membrane proteins in various aspects including membrane protein topology, domain, biological process, disease, and drug. Moreover, protein structure and ICD-10-CM based integrated disease and drug information was newly included. To analyze the comprehensive information of membrane proteins, we implemented analysis tools to identify novel sequence and functional features of the classified membrane protein groups and to extract features from protein sequences.
resultsWe constructed HMPAS with 28,509 collected known membrane proteins and 8,076 newly predicted candidates. This system provides integrated information of human membrane proteins individually and in groups organized by 45 subcellular locations and 1,401 molecular functions. As a case study, we identified associations between the membrane proteins and diseases and present that membrane proteins are promising targets for diseases related with nervous system and circulatory system. A web-based interface of this system was constructed to facilitate researchers not only to retrieve organized information of individual proteins but also to use the tools to analyze the membrane proteins.
conclusionsHMPAS provides comprehensive information about human membrane proteins including specific features of certain membrane protein groups. In this system, user can acquire the information of individual proteins and specified groups focused on their conserved sequence features, involved cellular processes, and diseases. HMPAS may contribute as a valuable resource for the inference of novel cellular mechanisms and pharmaceutical targets associated with the human membrane proteins. HMPAS is freely available at http://fcode.kaist.ac.kr/hmpas.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.