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Structural approaches for the DNA binding motifs prediction in Bacillus thuringiensis sigma-E transcription factor (σETF)

  • Yee Ying Lim
  • Theam Soon Lim
  • Yee Siew ChoongEmail author
Original Paper

Abstract

The sigma-E transcription factor (σETF) can be found in most of the bacteria cells including Bacillus thuringiensis. However, the cellular regulatory mechanisms of these transcription factors in the mass production of δ-endotoxins during sporulation stage are yet to be revealed. In addition, the recognition of DNA towards σETF DNA binding motifs that led to the transcription activities is also being poorly studied. Therefore, this work studied the possible DNA binding motifs of σETF by utilising in silico approaches. The structure of σETF was first built via three different computational methods. A cognate DNA sequence was then docked to the predicted σETF DNA-binding motifs. The binding free energy calculated using molecular mechanics/Poisson-Boltzmann surface area (MM-PBSA) for triplicate 50 ns simulation of σETF-DNA complex revealed favourable binding energy of DNA to σETF (average ∆Gbind = −34.57 kcal/mol) mainly driven by non-polar interactions. This study revealed that σETF LYS131, ARG133, PHE138, TRP146, ARG222, LYS225 and ARG226 are most likely the key residues upon the binding and recognition of DNA prior to transcription actives. Since determination of genome-regulating protein which recognises specific DNA sequence is important to discriminate between the proteins preferences for different genes, this study might provide some understanding on the possible σETF-DNA recognition prior to transcription initiated for the δ-endotoxins production.

Keywords

Bacillus thuringiensis DNA binding motifs Sigma-E transcription factor (σETF) protein MM-PBSA binding free energy calculation 

Abbreviations

σETF

sigma-E transcription factor

MM-PBSA

Molecular Mechanics/Poisson-Boltzmann Surface Area

Bacillis thuringiensis

B. thuringiensis

DNA

deoxyribonucleic acid

RNAP

ribonucleic acid polymerase

NCBI

National Centre of Biotechnology Information

BLASTp

protein basic local alignment search tool

DOPE

Discrete Optimized Protein Energy

HADDOCK

High Ambiguity-Driven Docking

MD

molecular dynamics

PME

particle mesh Ewald

RMSD

root mean square deviation

Notes

Acknowledgements

The first author would like to thank the Universiti Sains Malaysia for its support through USM fellowship.

Funding information

This work is supported by Universiti Sains Malaysia RUI grant (1001/CIPPM/8011051) and Higher Institutions Centre of Excellence (HICoE) Grant (311/CIPPM/44001005) from the Malaysia Ministry of Education.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Supplementary material

894_2019_4192_MOESM1_ESM.docx (1.6 mb)
ESM 1 (DOCX 1647 kb)

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© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Institute for Research in Molecular Medicine (INFORMM)Universiti Sains MalaysiaMindenMalaysia
  2. 2.Analytical Biochemistry Research CentreUniversiti Sains MalaysiaMindenMalaysia

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