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Open Access Highly Accessed Research article

Properties and identification of antibiotic drug targets

Tala M Bakheet1 and Andrew J Doig2*

Author Affiliations

1 Faculty of Life Sciences, The University of Manchester, Michael Smith Building, Oxford Road, Manchester M13 9PT, UK

2 Manchester Interdisciplinary Biocentre, The University of Manchester, 131 Princess Street, Manchester M1 7DN, UK

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BMC Bioinformatics 2010, 11:195  doi:10.1186/1471-2105-11-195

Published: 20 April 2010

Additional files

Additional file 1:

Gene Ontology Terms. Pie charts for frequencies of Gene Ontology terms for E. coli targets, bacterial targets and non-targets. Supplemental Figure 1a - Distribution of molecular functions at level 1 for E. coli targets. Supplemental Figure 1b - Distribution of molecular functions at level 1 for bacterial targets. Supplemental Figure 1c - Distribution of molecular functions at level 1 for non-targets. Supplemental Figure 1d - Distribution of molecular functions at level 2 for E. coli targets. Supplemental Figure 1e - Distribution of molecular functions at level 2 for bacterial targets. Supplemental Figure 1f - Distribution of molecular functions at level 2 for non-targets. Supplemental Figure 1g - Distribution of biological processes at level 1 for E. coli targets. Supplemental Figure 1h - Distribution of biological processes at level 1 for bacterial targets. Supplemental Figure 1i - Distribution of biological processes at level 1 for non-targets. Supplemental Figure 1j - Distribution of biological processes at level 2 for E. coli targets. Supplemental Figure 1k - Distribution of biological processes at level 2 for bacterial targets. Supplemental Figure 1l - Distribution of biological processes at level 2 for non-targets. Supplemental Figure 1m - Distribution of cellular components at level 2 for E. coli targets. Supplemental Figure 1n - Distribution of cellular components at level 2 for bacterial targets. Supplemental Figure 1o - Distribution of cellular components at level 2 for non-targets.

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Additional file 2:

New predicted antibiotic targets. E. coli proteins with target-like properties. Results from applying SVM trained on distinguishing bacterial targets from non-targets.

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Additional file 3:

Predicted bacterial protein targets with sequence similarity to human proteins. Predicted bacterial protein targets (Additional File 2) were run with BLAST against the human proteome. All significant sequence matches are recorded here.

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Additional file 4:

New predicted targets with high similarity to essential genes. Predicted bacterial protein targets was subjected to a BLAST search against the E. coli essential genes. The 64 targets that have a high similarity to an essential gene are listed here, along with their p-values, identities and BLAST scores.

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Additional file 5:

Comparison to global functional atlas of E. coli. Hu et al. analysed E. coli orphan proteins, giving many new functional assignments [11]. In particular, they assigned 191 to categories associated with antibiotic drug targets. Here we compare our predicted target proteins to this global functional atlas, giving 40 common proteins that are particularly promising targets.

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Additional file 6:

Bacterial targets and non-targets data sets. Non-redundant bacterial targets and non-targets data sets.

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Additional file 7:

Non-redundant putative essential genes. Essential genes are those that are not able to recover from a random insertion disruption [32]. 603 non-redundant putative essential genes are listed here, downloaded from the National Microbial Pathogen Data resource (NMPDR) http://www.nmpdr.org/FIG/wiki/view.cgi/Main/EssentialGenes webcite.

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