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

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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.

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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

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Acknowledgements

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

Funding

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.

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Lim, Y.Y., Lim, T.S. & Choong, Y.S. Structural approaches for the DNA binding motifs prediction in Bacillus thuringiensis sigma-E transcription factor (σETF). J Mol Model 25, 301 (2019). https://doi.org/10.1007/s00894-019-4192-3

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