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Research Article

Evaluation of substrate specificity and catalytic promiscuity of Bacillus albus cellulase: an insight into in silico proteomic study aiming at enhanced production of renewable energy

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Received 09 May 2023, Accepted 11 Dec 2023, Published online: 21 Dec 2023
 

Abstract

Cellulases are enzymes that aid in the hydrolysis of cellulosic fibers and have a wide range of industrial uses. In the present in silico study, sequence alignment between cellulases from different Bacillus species revealed that most of the residues are conserved in those aligned enzymes. Three dimensional structures of cellulase enzymes from 23 different Bacillus species have been predicted and based on the alignment between the modeled structures, those enzymes have been categorized into 7 different groups according to the homology in their conformational folds. There are two structural contents in Gr-I cellulase namely β1-α2 and β3-α5 loops which varies greatly according to their static position. Molecular docking study between the B. albus cellulase and its various cellulosic substrates including xylanoglucan oligosaccharides revealed that residues viz. Phe154, Tyr258, Tyr282, Tyr285, and Tyr376 of B. albus cellulase are significantly involved in formation stacking interaction during enzyme-substrate binding. Residue interaction network and binding energy analysis for the B. albus cellulase with different cellulosic substrates depicted the strong affinity of XylGlc3 substrate with the receptor enzyme. Molecular interaction and molecular dynamics simulation studies exhibited structural stability of enzyme-substrate complexes which are greatly influenced by the presence of catalytic promiscuity in their substrate binding sites. Screening of B. albus in carboxymethylcellulose (CMC) and xylan supplemented agar media revealed the capability of the bacterium in degrading both cellulose and xylan. Overall, the study demonstrated B. albus cellulase as an effective biocatalyst candidate with the potential role of catalytic promiscuity for possible applications in biofuel industries.

Communicated by Ramaswamy H. Sarma

Acknowledgements

Authors are grateful to Bioinformatics Facility, Department of Biotechnology and authorities of Maharaja Sriram Chandra Bhanja Deo University, Baripada, India for the provision of computational support.

Authors’ contributions

MP conducted major part of Experiments, investigated the results, analysed data, validated the results with related previous works, and contributed writing the original manuscript and formatting. AB and SM conceptualized some part of the research and guided the writing and assisted in figure preparation. DM helped to conduct the DFT analyses in this work and to prepare related write up. HT supervised the whole work, conceptualized the research, and guided the writing & editing of the manuscript. PKDM conceptualized some parts of the manuscript and also helped in writing the manuscript.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

All data generated or analyzed during this study are included in this article.

Additional information

Funding

The author(s) reported there is no funding associated with the work featured in this article.

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