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Fig 1.

Overview of different computational steps employed for the identification of putative essential targets (non-host homologous and host homologous) from the core-proteome of 13 C. diphtheriae strains.

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Fig 1 Expand

Fig 2.

Intra-species subtractive modelomics workflow for conserved target identification in C. diphtheriae species.

The table represents the total number of protein sequences as an input data fed to the MHOLline workflow (upper red arrow). The blue arrow represents the core genes of thirteen Cd strains. The rectangular boxes show how this workflow processes and filters a large quantity of genomic data for putative drug and vaccine target identification of a pathogen.

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Fig 2 Expand

Table 1.

Strains of C. diphtheriae employed in the pan-modelome study with information on genomes statistics, disease prevalence and location of isolation.

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Table 1 Expand

Fig 3.

Efficiency of the MHOLline biological workflow for genome-scale modelome (3D models) prediction.

Predicted proteomes from the genomes of 13 C. diphtheriae strains were fed to the MHOLline workflow in FASTA format. The grey bars represent the number of input data. The remaining bars (MHOLline output data) show the number of not aligned sequences (G0, green bars), sequences for which there is a template structure available at RCSB PDB (blue bars), and sequences with acceptable template structures that were modeled in the MHOLline workflow (G2, red bars).

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Fig 3 Expand

Table 2.

Drug and/or vaccine target prioritization parameters and functional annotation of the eight essential non-host homologous putative targets.

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Table 2 Expand

Table 3.

Drug and/or vaccine target prioritization parameters and functional annotation of the fifteen essential host homologous putative targets.

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Table 3 Expand

Fig 4.

Superposition of co-crystallized and Docked ligand; Dark Khaki represents the co crystallized ligand and Dark Cyan the re-docked conformation of the ligand.

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Fig 4 Expand

Fig 5.

A-I: 3D cartoon representation of the docking analyses for the most druggable protein cavity of NP_939302.1 (glpX, Fructose 1,6-bisphosphatase II) with Jacarandic Acid (CID 73645). A-II: 3D surface representation of the docking analyses for the structures of Jacarandic Acid with glpX protein. Figs B-I, II, C-I, II & D-I, II represent same information for compounds 16-hydrazonisosteviol, ZINC13142972 and ZINC67912153 respectively, for the same protein cavity.

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Fig 5 Expand

Table 4.

Compounds/Libraries name, MolDock scores and predicted hydrogen bonds for the selected best-ranked molecules against NP_939302.1 (glpX, Fructose 1,6-bisphosphatase II).

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Table 4 Expand

Fig 6.

A-I: 3D cartoon representation of the docking analyses for the most druggable protein cavity of NP_939692.1 (nusB, Transcription antitermination protein NusB) with Jacarandic Acid (CID 73645). A-II: 3D surface representation of the docking analyses for the structures of Jacarandic Acid with nusB protein. Figs B-I, II, C-I, II and D-I, II represent same information for compounds 16-hydrazonisosteviol, ZINC00053531 and ZINC15043210 respectively, for the same protein cavity.

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Fig 6 Expand

Table 5.

Compounds/Libraries name, MolDock scores and predicted hydrogen bonds for the selected molecules against NP_939692.1 (nusB, Transcription antitermination protein NusB).

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Table 5 Expand

Fig 7.

A-I 3D cartoon representation of the docking analyses for the most druggable protein cavity of NP_938900.1 (rpsH, 30S ribosomal protein S8) with Jacarandic Acid (CID 73645). A-II: 3D surface representation of the docking analyses for the structures of Jacarandic Acid with rpsH protein. Figs B-I, II, C-I, II and D-I, II represent same information for compounds 17-hydroxyisosteviol ZINC15221730 and ZINC35457686 respectively, for the same cavity.

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Fig 7 Expand

Table 6.

Compounds/Libraries name, MolDock scores and predicted hydrogen bonds for the selected molecules against NP_938900.1 (rpsH, 30S ribosomal protein S8).

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Table 6 Expand

Fig 8.

A-I 3D cartoon representation of the docking analyses for the most druggable protein cavity of NP_938502.1 (bioB, Biotin synthase) with Rhein (CID 10168). A-II: 3D surface representation of the docking analyses for the structure of Rhein with bioB protein. Figs B-I, II, C-I, II & D-I, II represent same information for compounds 16-oxime, 17-hydroxyisosteviol, ZINC16952914 and ZINC77269615 respectively, for the same protein cavity.

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Fig 8 Expand

Table 7.

Compounds/Libraries name, MolDock scores and predicted hydrogen bonds for the selected molecules against NP_938502.1 (bioB, Biotin synthase).

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Table 7 Expand

Fig 9.

A-1 3D cartoon representation of the docking analyses for the most druggable protein cavity of NP_939612.1 (hisE, Phosphoribosyl-ATP pyrophosphatase) with Jacarandic Acid (CID 73645). A-II: 3D surface representation of the docking analyses for the structure of Jacarandic Acid with hisE protein. Figs B-I, II, C-I, II & D-I, II represent same information for compounds 16–17 dihydroxyisosteviol, ZINC05809437 and ZINC67913372 respectively, for the same protein cavity.

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Table 8.

Compounds/Libraries name, MolDock scores and predicted hydrogen bonds for the selected molecules against NP_939612.1 (hisE, Phosphoribosyl-ATP pyrophosphatase).

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Table 8 Expand

Fig 10.

A-I 3D cartoon representation of the docking analyses for the most druggable protein cavity of NP_939123.1 (smpB, SsrA-binding protein) with Rhein (CID 10168). A-II: 3D surface representation of the docking analyses for the structure of Rhein with smpB protein. Figs B-I, II, C-I, II & D-I, II represent same information for compounds 16-hydroxyisosteviol ZINC01414475 & ZINC31168211 respectively, for the same protein cavity.

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Fig 10 Expand

Table 9.

Compounds/Libraries name, MolDock scores and predicted hydrogen bonds for the selected molecules against NP_939123.1 (smpB, SsrA-binding protein).

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Table 9 Expand

Fig 11.

A-I 3D cartoon representation of the docking analyses for the most druggable protein cavity of NP_939445.1 (DIP1084, Putative iron transport membrane protein, FecCD-family) with Jacarandic Acid (CID 73645). A-II: 3D surface representation of the docking analyses for the structure of Jacarandic Acid with DIP1084, Putative iron transport membrane protein. Figs B-I, II, C-I, II & D-1, II D represent same information for compounds 16-hydrazonisosteviol ZINC13142972 and ZINC70454922 respectively, for the same protein cavity.

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Fig 11 Expand

Table 10.

Compounds/Libraries name, MolDock scores and predicted hydrogen bonds for the selected molecules against NP_939445.1 (DIP1084, Putative iron transport membrane protein, FecCD-family).

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Table 10 Expand

Fig 12.

A-1: 3D cartoon representation of the docking analyses for the most druggable protein cavity of NP_939345.1 (DIP0983, Hypothetical protein DIP0983) with Jacarandic Acid (CID 73645). A-II: 3D surface representation of the docking analyses for the structure of Jacarandic Acid with Hypothetical protein DIP0983. Figs B-I, II, C-I, II & D-I, II represent same information for compounds 17-hydroxyisosteviol, ZINC00211173 and ZINC67911471 respectively, for the same protein cavity.

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Fig 12 Expand

Table 11.

Compounds/Libraries name, MolDock scores and predicted hydrogen bonds for the selected molecules against NP_939345.1 (DIP0983, hypothetical protein DIP0983).

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Table 11 Expand