Team:SZ SHD/Model
Models
1. Swiss model: KU3, Q7, Z50, R15
The biological activity of a protein is not only determined by the primary structure of the protein molecule but also closely related to its specific spatial structure. Elucidating the process of protein folding in functional and structural details will be of great significance to evaluate their keratinotic functions.
Serine residues of Z50 (BBa_K3895003), Q7 (BBa_K3895004), KU3 (BBa_K3895005), R15 (BBa_K3895006):
According to the amino acid sequences in the enzyme active sites and associated catalytic mechanisms, proteases can be classified into seven broad groups: serine, cysteine, threonine, aspartic and glutamic proteases, metalloproteases and asparagine peptide lyases. According to the nature of their active site, keratinases belong to serine- and metalloproteases or serine metalloproteases. Moreover, the enzymatic degradation of keratin is a multistage process that requires the following steps: adsorption of the keratinases to the surface of macromolecule by electrostatic and hydrophobic interactions, followed by catalytic action [1].
Hence we used Swiss Model to predict their hydrophobic region and serine groups.(https://swissmodel.expasy.org/docs/help#colour_schemes)
| Hydrophobic | RKDENQHPYWSTGAMCFLVI | Least hydrophobic -> Most hydrophobic |
| Size | GASPVTCLINDKQEMHFRYW | Smallest -> Largest |
| Charged | ED (Negative) HKR (Positive) | |
| Polar | RKDENQ | |
| Proline | P | |
| Ser/Thr | ST | |
| Cysteine | C | |
| Aliphatic | ILV | |
| Aromatic | FYWH |
Hydrophobisity of Z50, Q7, KU3, R15:
Ramachandran Plots of KU3, Q7, Z50, R15, check whether the angle between the residues in the structure is reasonable. Generally, more than 90% of the amino acid residues located in the acceptable region can be considered as a reasonable protein structure.
Z50 Ramachandran Favoured 95.14%
Q7 Ramachandran Favoured 91.25%
KU3 Ramachandran Favoured 91.23%
R15 Ramachandran Favoured 89.80%
2. ODE functions
The expression of the 4 keratinases in E. coli under culture conditions was modeled. The principle of the central law was used to predict the expression of keratinases using ordinary differential equations, thereby assisting enzyme production.
Where α and β are integral constant.
The data of the two enzymes with better effects： KU3 and Q7, were analyzed and modeled based on experiments. According to measurements of OD values examined after incubation, models were set up with Michaelis-Menton function and response surface.
3. Michaelis-Menten function
For keratinase [E] catalyzed reaction, the relationship between keratinase and substrate [S] and products [P]:
E + S --k1--> ES complex --k3--> E + P
E + S <--k2--
V0 = k3*[ES]
Rate of formation of ES = k1 * [E]*[S]
Rate of breakdown of ES = (k2 + k3) * [ES]
At steady state, the formation and the breakdown are equal, this steady state would only be temporary.
k1 * [E]*[S] = (k2 + k3) * [ES]
rearranging:
[ES] = [E]*[S] / ( (k2 + k3)/(k1))
Let Km = (k2+k3)/k1
[ES] = [E][S]/ Km
[ET] = [E] + [ES] (The total amount of keratinse equals the free and that bound to substrate)
Substituting in [ET] - [ES] for [E]
[ES] = ([ET] - [ES]) [S]/ Km
Solving for [ES] leads to [ES] = ([ET] (([S]/ Km)/(1 + [S]/ Km ))
Which simplifies to
[ES] = ([ET] *([S]/([S] + Km )
Multiplying both sides by the kinetic constant k3 gives the velocity of the reaction
V0 = k3 * [ES] = k3*[ET] *(([S]/([S] + Km )
and substituting Vmax for k3*[ET] leads to the familiar form of the Michaelis Menten Equation
V0 = Vmax *[S]/([S] + Km )
According to this, the reaction rate of keratinases KU3 and Q7 were modeled. Based on the data, V0 of KU3 and Q7 on the artificial substrate azocasein were calculated using results within 10-30 min; and V0 of KU3 and Q7 on the natural substrates casein and gelatin were calculated using results within 0-10 min respectively. The detailed data and derivation can be checked in Measurement.
4. Response Surface Analysis
Response surface analysis and simulation as useful tools for bioprocess design and optimization [2, 3]. For most multivariable processes, such as biochemical systems, which involve many potential influencing factors, it is not always obvious to determine which are the most important. It is necessary to submit the process to the initial screening design before optimization.
The maximum simulation for azocasein is outside the experimental region, whether it's KU3 or Q7. While for casein, the simulation is of a saddle surface. The response surface for gelatin shows a maximum point, indicating the keratinase activity reached the optimum condition. All simulations show a larger increase in enzyme activity in a shorter time frame.
References
Vidmar, Beti, and Maša Vodovnik. “Microbial Keratinases: Enzymes with Promising Biotechnological Applications.” Food technology and biotechnology vol. 56,3 (2018): 312-328. doi:10.17113/ftb.56.03.18.5658
Gahlot, Dharmender K., Gyles Ifill, and Sheila MacIntyre. 2021. "Optimised Heterologous Expression and Functional Analysis of the Yersinia pestis F1-Capsular Antigen Regulator Caf1R" International Journal of Molecular Sciences 22, no. 18: 9805. https://doi.org/10.3390/ijms22189805
Kalil, S. J., F. Maugeri, and M. I. Rodrigues. "Response surface analysis and simulation as a tool for bioprocess design and optimization."
Process biochemistry 35.6 (2000): 539-550.
Bezerra, Marcos Almeida, et al. "Response surface methodology (RSM) as a tool for optimization in analytical chemistry." Talanta 76.5 (2008): 965-977.
