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Prediction of the plant beta-barrel proteome: a case study of the chloroplast outer envelope.

ABSTRACT: In the postgenomic era, the transformation of genetic information into biochemical meaning is required. We have analyzed the proteome of the chloroplast outer envelope membrane by an in silico and a proteomic approach. Based on its evolutionary relation to the outer membrane of Gram-negative bacteria, the outer envelope membrane should contain a large number of beta-barrel proteins. We therefore calculated the probability for the existence of beta-sheet, beta-barrel, and hairpin structures among all proteins of the Arabidopsis thaliana genome. According to the existence of these structures, a number of candidates were selected. This protein pool was analyzed by TargetP to discard sequences with signals that would direct the protein to other organelles different from chloroplasts. In addition, the pool was manually controlled for the presence of proteins known to function outside of the chloroplast envelope. The approach developed here can be used to predict the topology of beta-barrel proteins. For the proteomic approach, proteins of highly purified outer envelope membranes of chloroplasts from Pisum sativum were analyzed by ESI-MS/MS mass spectrometry. In addition to the known components, four new proteins of the outer envelope membranes were identified in this study.

SUBMITTER: Schleiff E

PROVIDER: S-EPMC2323836 | biostudies-literature | 2003 Apr

REPOSITORIES: biostudies-literature

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Prediction of the plant beta-barrel proteome: a case study of the chloroplast outer envelope.

Schleiff Enrico E Eichacker Lutz Andreas LA Eckart Kerstin K Becker Thomas T Mirus Oliver O Stahl Tanja T Soll Jürgen J

Protein science : a publication of the Protein Society 20030401 4

In the postgenomic era, the transformation of genetic information into biochemical meaning is required. We have analyzed the proteome of the chloroplast outer envelope membrane by an in silico and a proteomic approach. Based on its evolutionary relation to the outer membrane of Gram-negative bacteria, the outer envelope membrane should contain a large number of beta-barrel proteins. We therefore calculated the probability for the existence of beta-sheet, beta-barrel, and hairpin structures among ...[more]

PMID: 12649433

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Project description:BackgroundPrediction of the transmembrane strands and topology of beta-barrel outer membrane proteins is of interest in current bioinformatics research. Several methods have been applied so far for this task, utilizing different algorithmic techniques and a number of freely available predictors exist. The methods can be grossly divided to those based on Hidden Markov Models (HMMs), on Neural Networks (NNs) and on Support Vector Machines (SVMs). In this work, we compare the different available methods for topology prediction of beta-barrel outer membrane proteins. We evaluate their performance on a non-redundant dataset of 20 beta-barrel outer membrane proteins of gram-negative bacteria, with structures known at atomic resolution. Also, we describe, for the first time, an effective way to combine the individual predictors, at will, to a single consensus prediction method.ResultsWe assess the statistical significance of the performance of each prediction scheme and conclude that Hidden Markov Model based methods, HMM-B2TMR, ProfTMB and PRED-TMBB, are currently the best predictors, according to either the per-residue accuracy, the segments overlap measure (SOV) or the total number of proteins with correctly predicted topologies in the test set. Furthermore, we show that the available predictors perform better when only transmembrane beta-barrel domains are used for prediction, rather than the precursor full-length sequences, even though the HMM-based predictors are not influenced significantly. The consensus prediction method performs significantly better than each individual available predictor, since it increases the accuracy up to 4% regarding SOV and up to 15% in correctly predicted topologies.ConclusionsThe consensus prediction method described in this work, optimizes the predicted topology with a dynamic programming algorithm and is implemented in a web-based application freely available to non-commercial users at http://bioinformatics.biol.uoa.gr/ConBBPRED.

Dataset Information

Prediction of the plant beta-barrel proteome: a case study of the chloroplast outer envelope.

Publications

Prediction of the plant beta-barrel proteome: a case study of the chloroplast outer envelope.

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