Identification of potential drug targets by subtractive genome analysis of Escherichia coli O157:H7: an in silico approach

Abstract

Bacterial enteric infections resulting in diarrhea, dysentery, or enteric fever constitute a huge public health problem, with more than a billion episodes of disease annually in developing and developed countries. In this study, the deadly agent of hemorrhagic diarrhea and hemolytic uremic syndrome, Escherichia coli O157:H7 was investigated with extensive computational approaches aimed at identifying novel and broad-spectrum antibiotic targets. A systematic in silico workflow consisting of comparative genomics, metabolic pathways analysis, and additional drug prioritizing parameters was used to identify novel drug targets that were essential for the pathogen's survival but absent in its human host. Comparative genomic analysis of Kyoto Encyclopedia of Genes and Genomes annotated metabolic pathways identified 350 putative target proteins in E. coli O157:H7 which showed no similarity to human proteins. Further bio-informatic approaches including prediction of subcellular localization, calculation of molecular weight, and web-based investigation of 3D structural characteristics greatly aided in filtering the potential drug targets from 350 to 120. Ultimately, 44 non-homologous essential proteins of E. coli O157:H7 were prioritized and proved to have the eligibility to become novel broad-spectrum antibiotic targets and DNA polymerase III alpha (dnaE) was the top-ranked among these targets. Moreover, druggability of each of the identified drug targets was evaluated by the DrugBank database. In addition, 3D structure of the dnaE was modeled and explored further for in silico docking with ligands having potential druggability. Finally, we confirmed that the compounds N-coeleneterazine and N-(1,4-dihydro-5H-tetrazol-5-ylidene)-9-oxo-9H-xanthene-2-sulfon-amide were the most suitable ligands of dnaE and hence proposed as the potential inhibitors of this target protein. The results of this study could facilitate the discovery and release of new and effective drugs against E. coli O157:H7 and other deadly human bacterial pathogens.

Keywords: DNA polymerase III alpha; E. coli O157:H7; KEGG metabolic pathways; homology modeling; novel and broad-spectrum antibiotic targets.

Figure 1

A schematic representation of the workflow of computational drug target identification and prediction of putative inhibitors of the selected target. Abbreviations: BLASTP, Protein Basic Local Alignment Search Tool; TTD, Therapeutic Target Database.

Figure 2

Comparative subcellular localization of proteins from the common host-pathogen pathways and pathogen-specific pathways.

Figure 3

Percentage distribution of novel drug targets involved in different metabolic pathways or biological processes.

Figure 4

Homology modeled structure of the Escherichia coli O157:H7 Sakai strand DNA polymerase III alpha, modeled with ESyPred3D server.

Figure 5

Structure validation and energy minimization. Notes: (A) Result of PROCHECK verification program, showing number and percentages of residues in most favored regions (red); additional allowed regions (yellow); generously allowed regions (creamy white); and in disallowed regions (white). Based on an analysis of 118 structures of resolution of at least 2.0 angstroms and R-factor no greater than 20%, a good quality model would be expected to have over 90% in the most favored regions. (B) Result of the 3D structure verification tool ANOLEA. This figure shows residues in favorable energy environment (green) and residues in unfavorable energy (red). Abbreviation: ANOLEA, atomic non-local environment assessment.

Figure 6

Active site residues (shown in green) of the Escherichia coli O157:H7 Sakai strand DNA polymerase III alpha. Note: Figure prepared by CASTp server.

Figure 7

Three-dimensional representation. Notes: Three-dimensional representation of the interactive residues on the binding site of the protein when it interacts with (A) active inhibitors (ligands) respectively with CID 9809878; ZINC 5117079 and ZINC 28356629 and (B) top binding affinity molecules DB04118 and DB04698. The color indicator on the left side shows the types of interaction of particular residues.

Figure 8

Structure of top hit compounds by in silico screening. Notes: (A) DB04118 (N-Coeleneterazine), (B) DB04698 (N-(1,4-Dihydro-5H-tetrazol-5-ylidene)-9-oxo-9H-xanthene-2-sulfonamide).