Statistical approach for enzyme production using response surface methodology and structure prediction of thermostable organic solvent-tolerant rand protease
Serine proteases from the Bacillus species extensively applied in the biotechnological application. So far, the broad investigation on proteases gave the basic understanding of their catalytic mechanism and their structure-function. Computational structure analysis and homology modelling can be a ke...
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| Main Author: | |
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| Format: | Thesis |
| Language: | English |
| Published: |
2017
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| Subjects: | |
| Online Access: | http://psasir.upm.edu.my/id/eprint/83021/1/FBSB%202018%2059%20ir.pdf |
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| Summary: | Serine proteases from the Bacillus species extensively applied in the biotechnological application. So far, the broad investigation on proteases gave the basic understanding of their catalytic mechanism and their structure-function. Computational structure analysis and homology modelling can be a key process for the 3D structure reconstruction which facilitates the protein-protein interaction research. Protein crystal is the basic necessity to obtain the 3D structure. The crystallisation process requires ample amount of protein. Bacillus subtilis strain Rand could only express the low amount of the protein. The Rand protease has unique characteristics and is the first thermostable and organic solvent tolerant protease that has been reported. Therefore, the structural study is needed to understand the enzyme properties. A statistical approach, response surface methodology (RSM), was performed to optimise the production of extracellular Rand protease in bioreactor stirred tank. Consequently, a face-centred, central composite design (CCD) falling under RSM was employed to enhance the protease activity further. The interactive effect of these parameters resulted in a 1.6-fold increase in protease production. An analysis of the variance showed that the adequacy of the model and verification experiments confirmed its validity. Crystallisation of the purified wild-type protein performed under microgravity conditions in space as well as in the ground. There is no crystal form observed in the ground control but, Rand protease protein successfully crystallised under microgravity conditions. A structural prediction for the Rand protease was built using the Yet Another Scientific Artificial Reality Application (YASARA) structure employing a known 3D structure (subtilisin E-propeptide complex; PDB ID: 1SCJ) as a template, which has the highest sequence similarity (96%) to the Rand protease. The predicted 3D structure of the Rand protease revealed that the topological organization of the α/β-hydrolase fold consisted of 6 α-helices and 13 β-strands. In silico study of docking, the substrate N-succinyl-alanyl-alanyl-prolyl-phenylalanine- 4-nitroanilide in Rand protease resulted in 25 clusters whereby 4 clusters observed to involve the catalytic triad of rand protease that is Asp32, His64, and Ser221. This result is in good agreement with the active site prediction and several experimental studies, which shows the same conserved catalytic triad. Molecular dynamics (MD) simulations were performed in two organic solvents with different logP values, such as pyridine (logP 0.71), benzene (logP 2.0) and pure water, for 10 ns to investigate their effect on the Rand protease structure. In conclusion, the production of Rand protease using a bioreactor through RSM could increase the yield of this enzyme compared to using a shake flask. The structure analysis confirmed the unique characteristics of this enzyme and explained the organic solvent stability of the enzyme. The predicted structure clarified the use of HIC as the first step for purification by highlighting the number of hydrophobic residues on the surface of the protein. |
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