3D MODELLING
The aim of creating 3D models of our fusion peptide is to analyse the peptide in detail, especially its stability, structure, and bonding compatibility with PCSK9 and P2Y12R. We have utilised PyMOL Molecular Graphics System, ChimeraX, HDOCK server, DeepSTABp server, CamSOL server and AlphaFold as our main tools for research and modelling..
Structure of Fusion Peptide
Given the lack of known protein structures for our target proteins, TP1 and P5, we employed AlphaFold for the prediction of their 3D models and to make the model of fusion peptide TP1P5. To initiate the process, we utilised the modified amino acid sequence of each peptide and subjected it to AlphaFold's simulation through structure prediction in ChimeraX.
Figure 1a(left): TP1 3D model
Figure 1b(middle): P5 3D model
Figure 1c(right): TP1P5 3D model
Synthesis of TP1P5 is successful as demonstrated by the position error graph below.
Figure 2: Position error graph of TP1P5
Figure 3a(left): C-terminal of TP1P5
Figure 3b(right): N-terminal of TP1P5
Stability of Fusion Peptide
To ensure that the fusion protein is stable and suitable for consumption, we have three methods for checking the stability. First, we check the presence of disulphide bonds, then we examine the temperature and pH level at which TP1P5 still functions properly.
Finding Disulphide Bonds Using PyMOL
Disulfide bonds have classically been shown to stabilise proteins by maintaining overall structure via intermolecular and intra-domain covalent bonds between two cysteine residues. These structural disulfide bonds are essential for the stability of secreted and plasma-membrane proteins destined for the harsh oxidising extracellular environment.
Therefore, to analyse the stability of our protein, we check for the presence of disulphide bonds (highlighted in blue) using PyMOL Molecular Graphics System. TP1 has 4 disulphide bonds, while P5 has no disulphide bonds due to its small size and short length.
Figure 4a(left): TP1 3D model
Figure 4b(middle): P5 3D model
Figure 4c(right): TP1P5 3D model
Thermostability Analysis Using DeepSTABp
Increasing temperature destabilises proteins by accelerating molecular motions, whereas decreasing temperature stabilises proteins by slowing such motions. Everything else being equal, temperature thus changes the equilibrium between folded and unfolded protein states. In other words, a temperature increase can reduce the amount of correctly folded proteins.
Since proteins and enzymes denature at high temperatures, it is empirical for us to obtain thermal stability data of TP1P5. In this project we used Thermometer, a publicly available webserver, to assess the thermostability of a protein using structural information.
According to the DeepSTABp thermostability prediction model, the boiling point of TP1 is 58°c, the boiling point of P5 is 60°c, and the boiling point of TP1p5 is 57°c. Therefore, we can conclude that TP1P5 is completely thermally stable in a human digestive system.
Solubility In Different pH Levels Analysis Using CamSOL
Due to the fact that the human digestive system has different pH levels in different organs, we must ensure that TP1P5 is not destroyed before it reaches the blood vessels.
Utilising CamSOL, a sequence-based method of predicting protein solubility and generic aggregation propensity as a function of pH developed by the Yusuf Hamied Department of Chemistry, University of Cambridge. This page provides the calculation of the CamSol intrinsic solubility profile, or solubility of the unfolded state at varying pH. CamSolpH yields a solubility profile (one score per residue in the protein sequence) where regions with scores larger than 1 denote highly soluble regions, while scores smaller than -1 poorly soluble ones.
Figure 5: Graph of solubility score against varying pH level(1.00-14.00)
| pH | 1.00 | 2.00 | 3.00 | 4.00 | 5.00 | 6.00 | 7.00 | 8.00 | 9.00 | 10.00 | 11.00 | 12.00 | 13.00 | 14.00 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Score | 0.141 | 0.137 | 0.102 | 0.028 | -0.082 | -0.136 | -0.149 | -0.114 | -0.046 | 0.041 | 0.207 | 0.342 | 0.397 | 0.273 |
Table 1: Graph of solubility score against varying pH level (1.00-14.00)
As seen in the above graph, the protein is not very soluble in all pH levels found in the human body, thus concluding that the protein is stable enough to pass through to the target area without severe damage.
Binding with PCSK9 AND P2Y12R
Since TP1 and P5 are supposed to inhibit P2Y12R and PCSK9 respectively when separated, we need to confirm that the fusion did not affect the main functions of each peptide.
Finding the Binding Sites
To aid with the prediction of binding, we have to first locate the binding sites of TP1P5. We utilised PyMOL to find the molecules that bind with the P2Y12R and PCSK9 (highlighted in red).
Figure 6: TP1P5 binding sites
Simulating Binding Using HDOCK
The most common method of checking binding confidence is by using AI prediction systems which find the best combination of protein-protein docking and calculates a confidence score using the following formula.
Confidence Score = 1.0 1.0 + e(0.02Edocking + 150)
Edocking is the docking score of protein-protein complexes in PDB, which is usually around -200 or better. Roughly, when the confidence score is above 0.7, the two molecules are likely to bind; when the score is between 0.5 and 0.7, the molecules are likely to bind; when the confidence score is below 0.5, the molecules are unlikely to bind completely. Nevertheless, the confidence score should be used cautiously due to its empirical nature.
We used HDOCK server, a protein-protein and protein-DNA/RNA docking based on a hybrid algorithm of template-based modelling and ab initio free docking. Through the HDOCK server, we checked the binding confidence score of each peptide with their respective receptor and compared the results with the binding confidence score of the fusion peptide.
Figure 7a (left): Result of TP1 binding with P2Y12R
Figure 7b (right): Results of P5 binding with PCSK9
Figure 7c (left): Result of TP1P5 binding with P2Y12R
Figure 7d (right): Result of TP1P5 binding with PCSK9
The confidence score of TP1 docking with P2Y12R is remarkably lower than that of P5 and PCSK9, but it is due to the fact that TP1 only binds to a portion of P2Y12R in order to inhibit the effects of ADP. Thus, the low confidence score is reasonable and justified.