SOSUI: classification and secondary structure prediction system for membrane proteins

@article{Hirokawa1998SOSUICA,
  title={SOSUI: classification and secondary structure prediction system for membrane proteins},
  author={Takatsugu Hirokawa and S. Boon-Chieng and Shigeki Mitaku},
  journal={Bioinformatics},
  year={1998},
  volume={14 4},
  pages={
          378-9
        }
}
UNLABELLED The system SOSUI for the discrimination of membrane proteins and soluble ones together with the prediction of transmembrane helices was developed, in which the accuracy of the classification of proteins was 99% and the corresponding value for the transmembrane helix prediction was 97%. AVAILABILITY The system SOSUI is available through internet access: http://www.tuat.ac.jp/mitaku/sosui/. CONTACT sosui@biophys.bio.tuat. ac.jp. 
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SOSUIsignal: Software System for Prediction of Signal Peptide and Membrane Protein
TLDR
A system is developed, which combines a novel system for the signal peptide prediction with the previous system SOSUI, and two kinds of amino acid indices were developed forThe signal sequence prediction and the discrimination between signal peptides and signal anchors.
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This prediction system SOSUImp1 comprised of two filtering layers could discriminate very accurately among five types of proteins: cytoplasmic soluble proteins and secretory proteins, MP1 with and without a signal peptide, and multi spanning membrane proteins.
Features of transmembrane helices useful for membrane protein prediction
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The membrane protein prediction system SOSUI was improved on the basis of the asymmetric profiles of hydrophobicity and amphiphilicity, resulting in the accuracy of 98% for positive dataset and 96% for negative one of prokaryotes, and the comparable accuracy was obtained also for eukaryotes.
Proportion of membrane proteins in proteomes of 15 single-cell organisms analyzed by the SOSUI prediction system.
Structure Prediction of Proteins with Transmembrane Helices
TLDR
This work developed a protein structure prediction system comprised of two modules: classification and secondary structure prediction of membrane proteins, and the determination of lateral and rotational positioning of transmembrane helices (TMH) in proteins, based on the physicochemical consideration.
COMPUTATIONAL MODEL FOR PREDICTION OF TRANSMEMBRANE HELICES IN HIV Anubha Dubey *
TLDR
This work has analyzed HIV protein dataset using the SOSUI system which not only predicts transmembrane helix regions but also classifies them whether the protein is soluble or membrane.
On the Prediction of Transmembrane Helical Segments in Membrane Proteins
TLDR
A method based on discrete wavelet transform is developed to predict the number and location of transmembrane helical segments in membrane proteins and the obtained results indicate that the proposed method has higher prediction accuracy.
Evaluation of methods for the prediction of membrane spanning regions
TLDR
This work presents an evaluation of the performance of the currently best known and most widely used methods for the prediction of transmembrane regions in proteins and shows that TMHMM is currently the best performing trans Membrane prediction program.
Classification of Membrane Proteins by Types of Transmembrane Helices Using SOSUI System
TLDR
Four kinds of dataset are analyzed including two set of all amino acid sequences from proteomes, using the SOSUI system which not only predicts transmembrane helix regions but also classifies them by the strength of interaction with lipid membranes.
Bioinformatic approaches for the structure and function of membrane proteins.
TLDR
A brief review of the diverse computational methods for predicting membrane protein structure and function, including recent progress and essential bioinformatics tools is provided, in the hope that this review will be instructive to users studying membrane protein biology in their choice of appropriate bioInformatics methods.
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