In Silico Pharmacology

, 5:1

Study of intra–inter species protein–protein interactions for potential drug targets identification and subsequent drug design for Escherichia coli O104:H4 C277-11

  • Shakhinur Islam Mondal
  • Zabed Mahmud
  • Montasir Elahi
  • Arzuba Akter
  • Nurnabi Azad Jewel
  • Md. Muzahidul Islam
  • Sabiha Ferdous
  • Taisei Kikuchi
Original Research

DOI: 10.1007/s40203-017-0021-5

Cite this article as:
Mondal, S.I., Mahmud, Z., Elahi, M. et al. In Silico Pharmacol. (2016) 5: 1. doi:10.1007/s40203-017-0021-5


Protein–protein interaction (PPI) and host–pathogen interactions (HPI) proteomic analysis has been successfully practiced for potential drug target identification in pathogenic infections. In this research, we attempted to identify new drug target based on PPI and HPI computation approaches and subsequently design new drug against devastating enterohemorrhagic Escherichia coli O104:H4 C277-11 (Broad), which causes life-threatening food borne disease outbreak in Germany and other countries in Europe in 2011. Our systematic in silico analysis on PPI and HPI of E. coli O104:H4 was able to identify bacterial d-galactose-binding periplasmic and UDP-N-acetylglucosamine 1-carboxyvinyltransferase as attractive candidates for new drug targets. Furthermore, computational three-dimensional structure modeling and subsequent molecular docking finally proposed [3-(5-Amino-7-Hydroxy-[1,2,3]Triazolo[4,5-d]Pyrimidin-2-Yl)-N-(3,5-Dichlorobenzyl)-Benzamide)] and (6-amino-2-[(1-naphthylmethyl)amino]-3,7-dihydro-8H-imidazo[4,5-g]quinazolin-8-one) as promising candidate drugs for further evaluation and development for E. coli O104:H4 mediated diseases. Identification of new drug target would be of great utility for humanity as the demand for designing new drugs to fight infections is increasing due to the developing resistance and side effects of current treatments. This research provided the basis for computer aided drug design which might be useful for new drug target identification and subsequent drug design for other infectious organisms.


Drug resistance Host–pathogen interactions Homology modeling Molecular docking Protein structure 



Enterohemorrhagic E. coli


Host–pathogen interactions


Protein–protein interactions


Database of Interacting Proteins


Domain interaction map


Host–Pathogen Interaction Database


Structural Classification of Proteins


Protein Structural Interactome map


Database of Essential Genes


KEGG Automatic Annotation Server


Kyoto Encyclopedia of Genes and Genomes


Protein Data Bank


Structural Analysis and Verification Server


Computed Atlas of Surface Topography of proteins


Absorption, Distribution, Metabolism, Excretion and Toxicity


Human intestinal absorption


Blood brain barrier

Supplementary material

40203_2017_21_MOESM1_ESM.xlsx (92 kb)
Supplementary material 1 (XLSX 92 kb)
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Supplementary material 2 (XLSX 121 kb)
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Supplementary material 3 (XLSX 194 kb)
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Supplementary material 4 (XLSX 170 kb)
40203_2017_21_MOESM5_ESM.doc (76 kb)
Supplementary material 5 (DOC 75 kb)
40203_2017_21_MOESM6_ESM.doc (290 kb)
Supplementary material 6 (DOC 290 kb)

Copyright information

© Springer-Verlag Berlin Heidelberg 2017

Authors and Affiliations

  • Shakhinur Islam Mondal
    • 1
    • 2
  • Zabed Mahmud
    • 1
  • Montasir Elahi
    • 3
  • Arzuba Akter
    • 2
    • 4
  • Nurnabi Azad Jewel
    • 1
  • Md. Muzahidul Islam
    • 1
  • Sabiha Ferdous
    • 1
  • Taisei Kikuchi
    • 5
  1. 1.Department of Genetic Engineering and BiotechnologyShahjalal University of Science and TechnologySylhetBangladesh
  2. 2.Division of Microbiology, Department of Infectious Diseases, Faculty of MedicineUniversity of MiyazakiMiyazakiJapan
  3. 3.Department of Diagnosis, Prevention and Treatment of DementiaJuntendo University Graduate School of MedicineBunkyōJapan
  4. 4.Department of Biochemistry and Molecular BiologyShahjalal University of Science and TechnologySylhetBangladesh
  5. 5.Division of Parasitology, Faculty of MedicineUniversity of MiyazakiMiyazakiJapan

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