LOC3D: Annotate sub-cellular localization for protein structures

Rajesh Nair; Burkhard Rost

doi:10.1093/nar/gkg514

LOC3D: Annotate sub-cellular localization for protein structures

Rajesh Nair, Burkhard Rost

Research output: Contribution to journal › Article › peer-review

35 Scopus citations

Abstract

LOC3D (http://cubic.bioc.columbia.edu/db/LOC3d/) is both a weekly-updated database and a web server for predictions of sub-cellular localization for eukaryotic proteins of known three-dimensional (3D) structure. Localization is predicted using four different methods: (i) PredictNLS, prediction of nuclear proteins through nuclear localization signals; (ii) LOChom, inferring localization through sequence homology; (iii) LOCkey, inferring localization through automatic text analysis of SWISS-PROT keywords; and (iv) LOC3Dini, ab initio prediction through a system of neural networks and vector support machines. The final prediction is based on the method that predicts localization with the highest confidence. The LOC3D database currently contains predictions for >8700 eukaryotic protein chains taken from the Protein Data Bank (PDB). The web server can be used to predict sub-cellular localization for proteins for which only a predicted structure is available from threading servers. This makes the resource of particular interest to structural genomics initiatives.

Original language	English
Pages (from-to)	3337-3340
Number of pages	4
Journal	Nucleic Acids Research
Volume	31
Issue number	13
DOIs	https://doi.org/10.1093/nar/gkg514
State	Published - 1 Jul 2003
Externally published	Yes

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title = "LOC3D: Annotate sub-cellular localization for protein structures",

abstract = "LOC3D (http://cubic.bioc.columbia.edu/db/LOC3d/) is both a weekly-updated database and a web server for predictions of sub-cellular localization for eukaryotic proteins of known three-dimensional (3D) structure. Localization is predicted using four different methods: (i) PredictNLS, prediction of nuclear proteins through nuclear localization signals; (ii) LOChom, inferring localization through sequence homology; (iii) LOCkey, inferring localization through automatic text analysis of SWISS-PROT keywords; and (iv) LOC3Dini, ab initio prediction through a system of neural networks and vector support machines. The final prediction is based on the method that predicts localization with the highest confidence. The LOC3D database currently contains predictions for >8700 eukaryotic protein chains taken from the Protein Data Bank (PDB). The web server can be used to predict sub-cellular localization for proteins for which only a predicted structure is available from threading servers. This makes the resource of particular interest to structural genomics initiatives.",

author = "Rajesh Nair and Burkhard Rost",

note = "Funding Information: We are grateful to Jinfeng Liu and Megan Restuccia (Columbia) for computer assistance and Kaz (Columbia) for valuable discussions. The work of R.N. and B.R. was supported by grant DBI-0131168 from the National Science Foundation (NSF). Last, but not least, we are grateful to Amos Bairoch (SIB, Geneva), Rolf Apweiler (EBI, Hinxton), Phil Bourne (San Diego University) and their crews for maintaining excellent databases and to all experimentalists who enabled this tool by making their data publicly available.",

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doi = "10.1093/nar/gkg514",

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PY - 2003/7/1

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N2 - LOC3D (http://cubic.bioc.columbia.edu/db/LOC3d/) is both a weekly-updated database and a web server for predictions of sub-cellular localization for eukaryotic proteins of known three-dimensional (3D) structure. Localization is predicted using four different methods: (i) PredictNLS, prediction of nuclear proteins through nuclear localization signals; (ii) LOChom, inferring localization through sequence homology; (iii) LOCkey, inferring localization through automatic text analysis of SWISS-PROT keywords; and (iv) LOC3Dini, ab initio prediction through a system of neural networks and vector support machines. The final prediction is based on the method that predicts localization with the highest confidence. The LOC3D database currently contains predictions for >8700 eukaryotic protein chains taken from the Protein Data Bank (PDB). The web server can be used to predict sub-cellular localization for proteins for which only a predicted structure is available from threading servers. This makes the resource of particular interest to structural genomics initiatives.

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LOC3D: Annotate sub-cellular localization for protein structures

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