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PhosphoSitePlus, 2014: mutations, PTMs and recalibrations
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Based on PhosphoSitePlus, two key residues at the SBP could be potentially modified, including acetylation of K14 in VPS26C and ubiquitylation of K204 in VPS35L, which could disrupt SNX17 binding.
“For example, based on PhosphoSitePlus41, two key residues at the SBP could be potentially modified, including acetylation of K14 in VPS26C and ubiquitylation of K204 in VPS35L, which could disrupt SNX17 binding.”
From Structural basis for Retriever-SNX17 assembly and endosomal sorting (2024) · cites this paper as [41]
The Abstract identifies PhosphoSitePlus as a database of acetylation and ubiquitylation sites, and the PTMVar section discusses how modifications can affect protein interactions. However, our copy does not identify VPS26C K14 or VPS35L K204 as modified sites or assess whether either modification could disrupt SNX17 binding (searched the protein names and residues). (LLM, conf=0.85)
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Cerami, E., Gao, J., Dogrusoz, U., Gross, B. E., Sumer, S. O., Aksoy, B. A., Jacobsen, A., Byrne, C. J., Heuer, M. L., Larsson, E., et al. (2012) · Cancer Discovery · doi:10.1158/2159-8290.cd-12-0095 · Cited by 17,455
Beausoleil, S. A., Villén, J., Gerber, S. A., Rush, J., & Gygi, S. P. (2006) · Nature Biotechnology · doi:10.1038/nbt1240 · Cited by 1,577
The human proteome project: current state and future direction
Legrain, P., Aebersold, R., Archakov, A., Bairoch, A., Bala, K., Beretta, L., Bergeron, J., Borchers, C. H., Corthals, G. L., Costello, C. E., et al. (2011) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m111.009993 · Cited by 352
Flagged first, then by citations
Research works printed but not linked: 28
- Miranda, 2002, Phosphorylation and mutations of Ser(16) in human phenylalanine hydroxylase. Kinetic and structural effects, J. Biol. Chem., 277, 40937, 10.1074/jbc.M112197200 · DOI
- Gelmann, 2002, Occurrence of NKX3.1 C154T polymorphism in men with and without prostate cancer and studies of its effect on protein function, Cancer Res., 62, 2654
- Reimand, 2013, Systematic analysis of somatic mutations in phosphorylation signaling predicts novel cancer drivers, Mol. Syst. Biol., 9, 637, 10.1038/msb.2012.68 · DOI
- Ryu, 2009, Genome-wide analysis to predict protein sequence variations that change phosphorylation sites or their corresponding kinases, Nucleic Acids Res., 37, 1297, 10.1093/nar/gkn1008 · DOI
- Obenauer, 2003, Scansite 2.0: proteome-wide prediction of cell signaling interactions using short sequence motifs, Nucleic Acids Res., 31, 3635, 10.1093/nar/gkg584 · DOI
- Turk, 2006, Determining protein kinase substrate specificity by parallel solution-phase assay of large numbers of peptide substrates, Nat. Protoc., 1, 375, 10.1038/nprot.2006.57 · DOI
- Hornbeck, 2012, PhosphoSitePlus: a comprehensive resource for investigating the structure and function of experimentally determined post-translational modifications in man and mouse, Nucleic Acids Res., 40, D261, 10.1093/nar/gkr1122 · DOI
- Wu, 2006, The Universal Protein Resource (UniProt): an expanding universe of protein information, Nucleic Acids Res., 34, D187, 10.1093/nar/gkj161 · DOI
- Pruitt, 2014, RefSeq: an update on mammalian reference sequences, Nucleic Acids Res., 42, D756, 10.1093/nar/gkt1114 · DOI
- Griss, 2011, Consequences of the discontinuation of the International Protein Index (IPI) database and its substitution by the UniProtKB ‘complete proteome’ sets, Proteomics, 11, 4434, 10.1002/pmic.201100363 · DOI
- Nishi, 2011, Phosphorylation in protein-protein binding: effect on stability and function, Structure, 19, 1807, 10.1016/j.str.2011.09.021 · DOI · Paper page
- Smith, 2014, Survey of phosphorylation near drug binding sites in the Protein Data Bank (PDB) and their effects, Proteins
- Bandy, 2009, Mining protein-protein interactions from published literature using Linguamatics I2E, Methods Mol. Biol., 563, 3, 10.1007/978-1-60761-175-2_1 · DOI
- Olsen, 2006, Global, in vivo, and site-specific phosphorylation dynamics in signaling networks, Cell, 127, 635, 10.1016/j.cell.2006.09.026 · DOI
- Uhlen, 2010, Towards a knowledge-based Human Protein Atlas, Nat. Biotechnol., 28, 1248, 10.1038/nbt1210-1248 · DOI · Paper page
- Wu, 2013, BioGPS and MyGene.info: organizing online, gene-centric information, Nucleic Acids Res., 41, D561, 10.1093/nar/gks1114 · DOI
- Gaudet, 2013, neXtProt: organizing protein knowledge in the context of human proteome projects, J. Proteome Res., 12, 293, 10.1021/pr300830v · DOI · Paper page
- Croft, 2014, The Reactome pathway knowledgebase, Nucleic Acids Res., 42, D472, 10.1093/nar/gkt1102 · DOI · Paper page
- Saito, 2012, A travel guide to Cytoscape plugins, Nature methods, 9, 1069, 10.1038/nmeth.2212 · DOI
- Kan, 2010, Diverse somatic mutation patterns and pathway alterations in human cancers, Nature, 466, 869, 10.1038/nature09208 · DOI
- Lienhard, 2008, Non-functional phosphorylations?, Trends Biochem. Sci., 33, 351, 10.1016/j.tibs.2008.05.004 · DOI
- Nei, 2002, The Wilhelmine E. Key 2001 Invitational Lecture. Estimation of divergence times for a few mammalian and several primate species, J. Heredity, 93, 157, 10.1093/jhered/93.3.157 · DOI
- Miller, 2008, Linear motif atlas for phosphorylation-dependent signaling, Sci. signal., 1, ra2, 10.1126/scisignal.1159433 · DOI
- Iakoucheva, 2004, The importance of intrinsic disorder for protein phosphorylation, Nucleic Acids Res., 32, 1037, 10.1093/nar/gkh253 · DOI · Paper page
- Gnad, 2011, PHOSIDA 2011: the posttranslationalmodification database, Nucleic Acids Res., 39, D253, 10.1093/nar/gkq1159 · DOI
- Calvert, 1999, Allelic and locusheterogeneity in inherited venous malformations, Hum. mol. genets, 8, 1279, 10.1093/hmg/8.7.1279 · DOI
- Veugelers, 2004, Comparative PRKAR1Agenotype-phenotype analyses in humans with Carney complex and prkar1ahaploinsufficient mice, Proc. Natl Acad. Sci. U.S.A., 101, 14222, 10.1073/pnas.0405535101 · DOI
- Vacic, 2006, Two Sample Logo: a graphicalrepresentation of the differences between two sets of sequence alignments, Bioinformatics, 22, 1536, 10.1093/bioinformatics/btl151 · DOI
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Metadata
- Authors
- Hornbeck, P. V., Zhang, B., Murray, B., Kornhauser, J. M., Latham, V., & Skrzypek, E.
- Venue
- Nucleic Acids Research
- Publisher
- Oxford University Press (OUP)
- Published
- 2014-12-16
- Volume
- 43
- Issue
- D1
- Pages
- D512-D520
- ISSN
- 1362-4962
- 0305-1048
- PMC
- PMC4383998
- Cited by
- 3,411
- References
- 3
- Language
- en
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