Modelling of amilCP

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Modelling

Rational Design & AlphaFold

When working with chromoproteins, one recurring problem is the slow maturation rate of the chromoprotein. This means that the time from the expression of the protein to the eventual coloring of the protein can be problematic. On a molecular level, this problem has been attributed to a slow oxidation of the chromophore in the center of the protein. In order to address this problem, methods such as random mutagenesis and directed evolution have long been used to attempt to reduce this rate-determining step. However, in order to perform rational design, known fast-folding proteins, known as superfolders, can be used as reference. One such superfolder, which might work as a reference, is a chromoprotein found in the phylum Arthropoda known as Turbo Green Fluorescent Protein (TurboGFP). Researchers have also found correlations between the unique pore in the general beta-barrel scaffold of TurboGFP and the overall maturation rate of the chromoprotein. The researchers are therefore hinting at the increased influx of oxygen through the pore as the reason behind the increased maturation rate of this particular GFP. Since all known GFP chromoproteins share a general beta-barrel scaffold, we wanted to see if an induced pore in our slower-maturing chromoprotein would result in a faster-maturing mutant. In order to create such a variant, the X-ray crystallographic electron density maps provided in the paper by TurboGFP were used as reference and aligned to AmilCP to find suitable and equivalent positions in the secondary structure for pore-inducement in our own AmilCP protein. Mutations of amino acids in the same secondary structure elements found in TurboGFP were then simulated by mutating the amino acids in AmilCP and then performing an AlphaFold stimulation of the mutant protein. If the predicted electron density maps showed a “hole” in the modeled beta-barrel, an AmilCP mutant candidate was created. In total, four different final mutant candidates, all at position 195, were deemed promising. Leucine, which is the native amino acid, was mutated to Isoleucine, Valine, Alanine and Glycine respectively.

Molecular Dynamic Simulations

Lab work

Methods

Results & Conclusions