Multiple sequence alignment results. Positions 177 (Serine) 225 (Asparagine) 255 (Histidine) on the bottom consensus sequence mark active domains which can be seen to hold constant throughout the multiple sequences.

Further validation was found using a multiple sequence alignment (shown to the right) using T-Coffee between: LC-Cutinase, 3visB, Tfu_0883 and 1jfr. The alignment showed strong homology in all active site residues as well as between two of the three residues targeted by Silva et. al. for mutation. The third targeted residue, though significantly different in Tfu_0883 compared to in LC-Cutinase, was expected to result in similar protein activity gains upon mutation to alanine. This reasoning was supported by loading both models for 3visB and 1jfr in Pymol and assessing that the residues held a similar placement above the active site. Their placement, as well as the placement of the other two targeted residues, also showed that mutation to a smaller residue, alanine, would result in better binding ability into the active site by the ligand.

Generating our own theoretical mutations

SwissDock results of best fit sites for PET in LC-Cutinase. SwissDock results for ultimate best fit position of PET in LC-Cutinase

After validating the previous mutations we wished to make our own. The first step was to generate a theoretical 3D model for LC-Cutinase. This was done by using Swiss-Model again to fit LC-Cutinase’s amino acid sequence into the structure of 3visB. The results, including the stability of each part of the sequence, are shown below. The results show generally high stability along the sequence. Also, upon overlapping this newly generated model of LC-Cutinase with 3visB’s model in Pymol we received a low RMS value of .78A. This resulting data supported the idea that the generated 3D model for LC-Cutinase was stable and fit 3visB’s structure closely. The next stage was to get our theoretical model for LC-Cutinase and the two ligands it would interact with, PET and pNPB, into the Foldit program, a protein folding simulator. In Foldit we could perform and assay theoretical point mutations for increased stability and function of the protein. However, because Foldit does not directly measure function but measures stability instead, it was necessary to load LC-Cutinase with each ligand docked correctly into the active site. This would allow changes made at the active site that increased stability due to better ligand/protein interaction to also equate to better ligand/protein binding and thus better function by the protein. We created the ligand files through Cactus and the docking of the protein with each of the two ligands was done through Swissdock. The images to the left show the overall docking results as well as the best fit ligand binding position. From here we loaded each specific ligand/protein combo into foldit and generated the following mutations with each rational.

Mutant List and Rationale

• Silva et al. Mutant Replicants
  • T96A: Increase active site and change a hydrophilic residue for a hydrophobic alanine
  • Y127A:Increase active site and change a hydrophilic residue for a hydrophobic alanine
  • V212A:Enlarge active site

• Team chosen mutants
  • S101A:Increase active site and change a hydrophilic residue for a hydrophobic alanine
  • Y95A:Greatly open active site by removal of bulky side group and increase active site's hydrophobicity
  • D98T:Enlarge active site and generated hydrogen bond
  • F125R:Enlarge active site
  • F125Y:Enlarge active site
  • F125A:Increase active site and change a hydrophilic residue for a hydrophobic alanine
  • T96G:Similar as T96A however amino acid change takes place right before a alpha helix and a replacement with a G instead of A will avoid helix breaking

Additional Photos