Making FRET predictions

Making FRET predictions#

Once a donor and acceptor ACV is calculated, we can predict a mean transfer efficiency $⟨ E ⟩$ based on the distance between the two volumes.

⟨ E ⟩ = \frac{1}{n m} \sum_{i = 1}^{n} \sum_{j = 1}^{m} \frac{1}{1 + ∥ R_{A, j} - ∥ R_{D, i} ∥^{6} / R_{0}^{6}}

Here, $R_{D, i}$ and $R_{A, j}$ are the coordinate vectors of the points $i$ and $j$ in the donor and acceptor volume [4, 5].

R0: Förster radius of the dye pair
# distances: number of distances to sample for the FRET calculation. The algorithm chooses n pairs of randomly distributed points in the donor and acceptor cloud and calculates their distance
choose the donor and acceptor cloud from the drop down
Calculate FRET: start the FRET calculation. The mean FRET efficiency $⟨ E ⟩$ , the mean inter-dye distance $⟨ R_{D A} ⟩$ as well as the distances between the mean dye positions $⟨ R_{M P} ⟩$ or the two attachment sites are displayed in the table. The FRET parameters are also saved to a JSON file.

Note

The style of the ACV clouds can be tuned with the ACV visualization settings: