Title

SOSUI-GramN: high performance prediction for sub-cellular localization of proteins in Gram-negative bacteria

Authors

Kenichiro Imai^{1, 2, 3*}, Naoyuki Asakawa¹, Toshiyuki Tsuji¹, Fumitsugu Akazawa¹, Ayano Ino¹, Masashi Sonoyama¹ and Shigeki Mitaku¹

Affiliation

¹Department of Applied Physics, Graduate School of Engineering, Nagoya University, Furocho, Chikusa-ku, Nagoya 464-8606, Japan; ² Toyota Physical and Chemical Research Institute, Nagakute-cho, Aichi 480-1192, Japan; ³ Present address: Computational Biology Research Center, AIST, Tokyo 135-0064, Japan

Email

imai@bp.nuap.nagoya-u.ac.jp; * Corresponding author

Article Type

Hypothesis

Date

received July 04, 2008; accepted July 06, 2008; published July 14, 2008

Abstract

A predictive software system, SOSUI-GramN, was developed for assessing the subcellular localization of proteins in Gram-negative bacteria. The system does not require the sequence homology data of any known sequences; instead, it uses only physicochemical parameters of the N- and C-terminal signal sequences, and the total sequence. The precision of the prediction system for subcellular localization to extracellular, outer membrane, periplasm, inner membrane and cytoplasmic medium was 92.3%, 89.4%, 86.4%, 97.5% and 93.5%, respectively, with corresponding recall rates of 70.3%, 87.5%, 76.0%, 97.5% and 88.4%, respectively. The overall performance for precision and recall obtained using this method was 92.9% and 86.7%, respectively. The comparison of performance of SOSUI-GramN with that of other methods showed the performance of prediction for extracellular proteins, as well as inner and outer membrane proteins, was either superior or equivalent to that obtained with other systems. SOSUI-GramN particularly improved the accuracy for predictions of extracellular proteins which is an area of weakness common to the other methods.

Keywords

subcellular localization of proteins; Gram-negative bacteria; physicochemical parameters; amino acids

Citation

Imai et al., Bioinformation 2(9): 417-421 (2008)

Edited by

P. Kangueane

ISSN

0973-2063

Publisher

Biomedical Informatics

License

This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.