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International Microbiology

, Volume 22, Issue 1, pp 7–17 | Cite as

In silico identification of potential inhibitors against shikimate dehydrogenase through virtual screening and toxicity studies for the treatment of tuberculosis

  • Mustafa Alhaji IsaEmail author
  • Rita Singh Majumdar
  • Shazia Haider
Original Article
  • 58 Downloads

Abstract

The present study attempts to identify the novel inhibitors of shikimate dehydrogenase (SD), the enzyme that catalyzes the fourth reaction in the shikimate pathway, through virtual screening and toxicity studies. Crystal structure of SD was obtained from Protein Data Bank (PDB ID 4P4G, 1.7 Å) and subjected to energy minimization and structure optimization. A total of 13,803 compounds retrieved from two public databases and used for the virtual screening based on physicochemical properties (Lipinski rule of five) and molecular docking analyses. A total of 26 compounds with good AutoDock binding energies values ranging between − 12.03 and − 8.33 kcal/mol was selected and further filtered for absorption distribution metabolism excretion and toxicity analyses (ADMET). In this, eight compounds were selected, which satisfied all the ADME and toxicity analysis properties. Three compounds with better AutoDock binding energies values (ZINC12135132, − 12.03 kcal/mol; ZINC08951370, − 10.04 kcal/mol; and ZINC14733847, 9.82 kcal/mol) were considered for molecular dynamic (MD) simulation and molecular generalized born surface area (MM-GBSA) analyses. The results of the analyses revealed that the two ligands (ZINC12135132 and ZINC08951370) had better inhibitory activities within their complexes, after the 50-ns MD simulation, which suggested that the complexes formed stable conformation. It is noteworthy that compounds identified by docking, MD simulation, and MM-GBSA methods could be a drug for tuberculosis which required further experimental validation.

Keywords

MTB SD Virtual screening ADMET and MD simulation 

Notes

Acknowledgments

The corresponding author of this paper is very much thankful to Prof. B. Jayaram, (Supercomputing Facility for Bioinformatics & Computational Biology, IIT Delhi), Prof. Pawan Dhar (Jawaharlal Nehru University), Dr. Kalaiarasan P. (Jawaharlal Nehru University), Prof. N.B. Singh (Sharda University), and Mr. Shashank Shekhar, (IIT Delhi) for their tremendous support through providing facilities during the research.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Supplementary material

10123_2018_21_MOESM1_ESM.docx (576 kb)
ESM 1 (DOCX 575 kb)

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Mustafa Alhaji Isa
    • 1
    Email author
  • Rita Singh Majumdar
    • 2
  • Shazia Haider
    • 2
  1. 1.Department of Microbiology, Faculty of SciencesUniversity of Maiduguri P.M.B.MaiduguriNigeria
  2. 2.Department of Biotechnology, School of Engineering and TechnologySharda UniversityGreater NoidaIndia

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