ngLOC: software and web server for predicting protein subcellular localization in prokaryotes and eukaryotes

Abstract

BackgroundUnderstanding protein subcellular localization is a necessary component toward understanding the overall function of a protein. Numerous computational methods have been published over the past decade, with varying degrees of success. Despite the large number of published methods in this area, only a small fraction of them are available for researchers to use in their own studies. Of those that are available, many are limited by predicting only a small number of organelles in the cell. Additionally, the majority of methods predict only a single location for a sequence, even though it is known that a large fraction of the proteins in eukaryotic species shuttle between locations to carry out their function.FindingsWe present a software package and a web server for predicting the subcellular localization of protein sequences based on the ngLOC method. ngLOC is an n-gram-based Bayesian classifier that predicts subcellular localization of proteins both in prokaryotes and eukaryotes. The overall prediction accuracy varies from 89.8% to 91.4% across species. This program can predict 11 distinct locations each in plant and animal species. ngLOC also predicts 4 and 5 distinct locations on gram-positive and gram-negative bacterial datasets, respectively.ConclusionsngLOC is a generic method that can be trained by data from a variety of species or classes for predicting protein subcellular localization. The standalone software is freely available for academic use under GNU GPL, and the ngLOC web server is also accessible at http://ngloc.unmc.edu.

In silico aided thoughts on mitochondrial vitamin C transport

“…We chose (i) TargetP (Emanuelsson et al, 2000) the predictor uses a combination of neural networks to calculate a transit or SP score, and a weight matrix to locate the transit peptide cleavage sites; (ii) Mitoprot (Claros and Vincens, 1996) a feature-based method, uses a linear combination of a number of sequence characteristics such as amino-acid abundance, maximum hydrophobicity and maximum hydrophobic moment (α-helix amphiphilicity); (iii) Predotar (Small et al, 2004) the neural networkbased approach; (iv) PSORT II (Nakai and Horton, 1999) which is based on the k-nearest-neighbour method; (v) MultiLoc (Höglund et al, 2006) a support vector machine (SVM)-based approach for predicting subcellular localization, which integrates N-terminal targeting sequences, amino acid composition and protein sequence motifs; (vi) ngLOC (King et al, 2012) which is an ngram-based Bayesian classifier; (vii) YLoc (Briesemeister et al, 2010) is an interpretable web server for predicting subcellular localization which also uses GO term features; (viii) CELLO (Yu et al, 2006) is based on the multiple feature vector coding schemes.…”

“…Target P: http://www.cbs.dtu.dk/services/TargetP/ (Emanuelsson et al, 2000) Mitoprot II: http://ihg.gsf.de/ihg/mitoprot.html (Claros and Vincens, 1996) Predotar: https://urgi.versailles.inra.fr/predotar/predotar.html (Small et al, 2004) Psort II: http://psort.hgc.jp/form2.html (Nakai and Horton, 1999) MultiLoc/TargetLoc: http://abi.inf.uni-tuebingen.de/Services/ MultiLoc/ (Höglund et al, 2006) ngLOC: http://genome.unmc.edu/ngLOC/index.html (King et al, 2012) YLoc: http://abi.inf.uni-tuebingen.de/Services/YLoc/webloc.cgi (Briesemeister et al, 2010) CELLO v2.5: http://cello.life.nctu.edu.tw/ (Yu et al, 2006) The analyses were done in March and April of 2014 for Tables 2 and 3 and in August of 2014 for Table 1. All the results were confirmed in August of 2014.…”

Ca2+/Cation Antiporters (CaCA): Identification, Characterization and Expression Profiling in Bread Wheat (Triticum aestivum L.)

“…The NCBI blast server (https://blast.ncbi.nlm.nih.gov/Blast.cgi) was used for similarity analysis with other sequences in the database. The localization of the protein within the cell was predicted using pSORT (http://wolfpsort.org/), CELLO v.2.5 (http://cello.life.nctu.edu.tw/), TargetP_v1, PredSL, ngLOC and ProtComp (http://www.softberry.com/berry.phtml) servers (Emanuelsson et al, 2000; Petsalaki et al, 2006; Yu et al, 2006; Horton et al, 2007; King et al, 2012). Occurrence of signal peptide was recognized using SignalP 4.1 (http://www.cbs.dtu.dk/services/SignalP/).…”

In silico Analysis on the Possible Role of Mitochondria in Ferroptosis

“…Thus beyond the localization of GPX4 the localization of the GSH transporter protein SLC25A11 (2-oxoglutarate carrier:OGC) was also investigated by the aforementioned prediction tools. The prediction tool ngLOC that also uses gene ontology analysis [31] gave high mitochondrial localization score and other three prediction tools (TargetP, MitoProt and CELLO) give moderate scores (Table 4). PSORT II gave a low probability while Predotar and iPSORT practically gave no probability of the mitochondrial localization of SLC25A11 (Table 4).…”