Difference between revisions of "Part:BBa K4814006"
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| − | As the efficiency of FRET is largely dependent on the degree of the molecular separation and overall spatial arrangement of the two fluorophores involved, further ratification is needed to ensure the reliability of the sequences we designed for our FRET system and thereby validate the credibility of the data acquired from FRET imaging. To accomplish this, we have undertaken the development of a protein model. Our protein model involves a series of scientific methodologies, including sequence predictions, RMSD calculations, protein-protein docking, and distance measurements. We aim to predict and elucidate the interaction between ATRIP-eGFP and RPA1-mCherry, shedding light on the properties exhibited by the two fluorescent proteins as they interact, to investigate the system’s efficiency and further validate our FRET-based approach. | + | As the efficiency of FRET is largely dependent on the degree of the molecular separation and overall spatial arrangement of the two fluorophores involved, further ratification is needed to ensure the reliability of the sequences we designed for our FRET system and thereby validate the credibility of the data acquired from FRET imaging. To accomplish this, we have undertaken the development of a protein model. |
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| + | Our protein model involves a series of scientific methodologies, including sequence predictions, RMSD calculations, protein-protein docking, and distance measurements. We aim to predict and elucidate the interaction between ATRIP-eGFP and RPA1-mCherry, shedding light on the properties exhibited by the two fluorescent proteins as they interact, to investigate the system’s efficiency and further validate our FRET-based approach. | ||
By docking the fluorophores (eGFP, mCherry, eCFP, YFP) with the respective DNA damage response (DDR) proteins (ATRIP, RPA1), we plan to gain insight into their arrangements, their respective feasibilities, and their binding configurations, and then dock the bound structures together to further our understanding. | By docking the fluorophores (eGFP, mCherry, eCFP, YFP) with the respective DNA damage response (DDR) proteins (ATRIP, RPA1), we plan to gain insight into their arrangements, their respective feasibilities, and their binding configurations, and then dock the bound structures together to further our understanding. | ||
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<html><center><p>E = 0.40E<sub>rep</sub> +− 0.40E<sub>att</sub> + 600E<sub>elec</sub> +2.00E<sub>DARS</sub></p></center></html> | <html><center><p>E = 0.40E<sub>rep</sub> +− 0.40E<sub>att</sub> + 600E<sub>elec</sub> +2.00E<sub>DARS</sub></p></center></html> | ||
A total of 30 models were generated through the docking simulations. Subsequently, we focused our analysis on the top 10 models with the highest scores. Remarkably, all of these models exhibited a range of FRET effectiveness within the distance range of 10-100Å, indicating that our designed bio-reporter system is feasible in terms of configuration and proximity. | A total of 30 models were generated through the docking simulations. Subsequently, we focused our analysis on the top 10 models with the highest scores. Remarkably, all of these models exhibited a range of FRET effectiveness within the distance range of 10-100Å, indicating that our designed bio-reporter system is feasible in terms of configuration and proximity. | ||
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| + | (Blue: ATRIP-EGFP; Green: RPA1-mCherry) | ||
<html><img src=https://static.igem.wiki/teams/4814/wiki/cp6.png style="width: 750px;"></html> | <html><img src=https://static.igem.wiki/teams/4814/wiki/cp6.png style="width: 750px;"></html> | ||
Revision as of 13:39, 12 October 2023
ATRIP-EGFP
- NOTE: This part is used together with part BBa_K4814007 (RPA1-mCherry) as a FRET pair.
FRET is using fluorescent proteins as probes to detect the interaction of targeted proteins. The distance-dependent process transfers energy from an excited molecular fluorophore (the donor) to another fluorophore (the acceptor) through intermolecular long-range dipole–dipole coupling once the desired proteins bind (Sekar, R. B. and Periasamy, A., 2003). The critical Förster radius (typically 3-6 nm) at angstrom distances (10–100 Å) can be calculated to increase the accuracy and ensure precise energy transfer. (Alan Mulllan, n.d.) By using FRET, we can therefore observe the interaction of two proteins by measuring the lifetime of the fluorescent proteins attached to them.
As the aim of this design is to detect DNA damages in mammalian cells, we have used CMV promoter and the Lenti virus vector. Please refer to BBa_K4814004 and BBa_K4814005 (ATRIP and RPA1) for detailed explanation of the two proteins involved in the DNA damage checkpoint process.
The EGFP is derived from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC146266/ (same as BBa_K1875003), a mammalian codon optimized enhanced GFP.
3D Protein Docking Modeling
As the efficiency of FRET is largely dependent on the degree of the molecular separation and overall spatial arrangement of the two fluorophores involved, further ratification is needed to ensure the reliability of the sequences we designed for our FRET system and thereby validate the credibility of the data acquired from FRET imaging. To accomplish this, we have undertaken the development of a protein model.
Our protein model involves a series of scientific methodologies, including sequence predictions, RMSD calculations, protein-protein docking, and distance measurements. We aim to predict and elucidate the interaction between ATRIP-eGFP and RPA1-mCherry, shedding light on the properties exhibited by the two fluorescent proteins as they interact, to investigate the system’s efficiency and further validate our FRET-based approach.
By docking the fluorophores (eGFP, mCherry, eCFP, YFP) with the respective DNA damage response (DDR) proteins (ATRIP, RPA1), we plan to gain insight into their arrangements, their respective feasibilities, and their binding configurations, and then dock the bound structures together to further our understanding.
ClusPro
We used ClusPro 2.0[4][5][6][7] next, utilizing its CPU, to perform molecular docking simulations. The docking calculations were carried out with hydrophobic-favored coefficients to enhance the accuracy of the results.
E = 0.40Erep +− 0.40Eatt + 600Eelec +2.00EDARS
(Blue: ATRIP-EGFP; Green: RPA1-mCherry)
Figure 1. ClusPro hydrophobic-favored model no.6, with an angstrom distance of 56.5Å
Figure 2. ClusPro hydrophobic-favored model no.7, with an angstrom distance of 97.4Å
HDOCK
In addition to ClusPro, we opted for HDOCK to dock our predicted structures in hopes that the results from these simulations would be able to co-validate each other. In the case of any disparities in the outcomes of these two algorithms, it would be meaningful to compare the different scores, parameters and configurations that they may provide. Each HDOCK model comes with two scores, a docking score and a confidence score: The docking scores are calculated by a knowledge-based iterative scoring function. More negative docking scores indicate more likely binding models. However, since the score has not been calibrated to experimental data, it should not be interpreted as the actual binding affinity of two molecules. The confidence score is determined based on the docking score and is designed to indicate the likelihood of binding between the protein-protein/RNA/DNA complexes. Generally, when the confidence score is above 0.7, the two molecules would be very likely to bind in this pose.[8] The calculation of the confidence score is defined as follows:
Confidence_score = 1.0/[1.0+e0.02*(Docking_Score+150)]
Below are the docking scores and confidence scores for the top ten models, which are ranked by their docking scores:</p>| Rank | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 |
|---|---|---|---|---|---|---|---|---|---|---|
| Docking Score | -252.39 | -239.71 | -231.76 | -228.53 | -221.35 | -217.78 | -217.14 | -215.96 | -214.32 | -213.43 |
| Confidence Score | 0.8857 | 0.8574 | 0.8369 | 0.8279 | 0.8064 | 0.7950 | 0.7930 | 0.7890 | 0.7835 | 0.7805 |
Figure 3. The pose with the 1st highest score generated by HDOCK, with an angstrom distance od 132.5Å.
Figure 4. The pose with the 10th highest score generated by HDOCK, with an angstrom distance of 12.7Å.
Using PyMOL to measure the distance
Based on a comprehensive literature review, FRET can be an accurate measurement of molecular proximity within the range of angstrom distances (10–100 Å). Using PyMOL, we analyzed the results of both ClusPro and HDOCK by calculating the angstrom distance between the two fluorophores attached to ATRIP and RPA in the poses generated by these algorithms. Remarkably, all of the top 10 ClusPro models exhibited a range of FRET effectiveness within the distance range of 56.5-97.4Å. The results in HDOCK displayed a wider spectrum, ranging from 12.7Å to 132.5Å. It is important to emphasize that the scores given by ClusPro and HDOCK are not directly correlated with the distances determined by PyMOL; poses with higher scores do not necessarily indicate a larger or smaller degree of separation. However, these highly-ranked poses are more likely to form, so analysing their distance is relatively meaningful as it encompasses a substantial portion of the poses generated.
Experimental Results
Aggregation after UV treatment (Only ATRIP-EGFP)
After exposing the cells to a UVB dosage of 100 J/m^2, we observed aggregation of the EGFP signal (Fig. 5 and 6). Interestingly, fluorescence was detected in both the Green and Red channels. It is important to note that the emission of GFP is dependent on its fluorescence spectra, as mentioned in studies by Sattarzadeh, A. et al. (2015) and Licea-Rodriguez, J. (2019). This fluorescence could potentially be attributed to GFP emitting at around 560 nm.
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