Difference between revisions of "Team:Virginia/Model"

Overview

We modeled our system in silico to select a sterically feasible protecting group and to optimize a mutant leucyl-tRNA synthetase for complementarity of its catalytic site to protected leucine, and of its editing site to leucine. To select a protecting group, the team used protein-ligand docking software to compare binding affinities of several protected leucine/synthetase complexes. To perform mutagenesis on leucyl-tRNA synthetase, an integrated software script was written in the Linux shell, with inputs including a protein to mutate, a ligand, a list of residues of interest, and binding pocket location. The script runs mutagenesis, assesses mutant protein stability, then performs ligand docking. The program then ranks the outputs, acting as a streamlined mutagenesis optimization algorithm. We confirmed, using CSM software suites and iGEMDOCK, that AMP and AMS yield energetically comparable binding affinities. Lastly, we performed Michaelis-Menten modeling for the enzyme pepsin to gauge activity in nonspecific cleavage enzymes.

Leucine Synthetase Selection

Synthetase File: 4aq7

The Leucine tRNA Synthetase(LeuS) used in the following simulations was taken from the RCSB protein databank. The file used was 4aq7, a leucyl trna synthetase in its aminoacylation conformation. The following is a PyMol visualization of the protein.

AMS vs AMP

As stated in its documentation, 4aq7 used a leucyl-adenelyte analogue in order to measure the crystal structure of the protein. By analysing the file contents in PDBest, a pdb editor software, we were able to identify the analogue as leucyl-AMS.

We constructed six different molecules with ChemSketch in order to determine whether the analogue significantly altered the conformation of LeuS. The constructed molecules were AMS and AMP adenylations of Cbz-Leu, N-Methoxycarbonyl-Leu, and Leu. By testing these molecules in CSM-lig, Autodock Vina, and iGEMDOCK, we were able to confirm that AMS and AMP were similar, and that the pdb 4aq7 could be used to accurately model the LeuS.

Protecting Group

Selection - Modeling Considerations

Several programs were used to asses the viability of the different protecting groups in our system. The main programs used for this purpose were Autodock Vina, iGEMDOCK, and CSM-Lig.

Residue Selection

Literature
iGEMDOCK and Ligplot

We used a combination of docking data as simulated in iGEMDOCK and structural data visualized in Ligplot to determine additional mutational focci. iGEMDOCK is able to provide energy values for each residue by conducting an exhaustive docking search. Ligplot is capable of creating a 2D image of the binding site as detailed in the crystolography file. We selected mutations that satisfied two criteria. First, the residue had to have been shown to have a high energy during docking. Residues that returned large values in the protected leucine simulations were believed to have a high impact on the reduced viability of docking. The second criteria was that of location. Residues that protruded around the N terminus of leucine, the location the protecting group binds to, were thought to be possible sources of steric hindrance. a total of four residues that satisfied both criteria were selected.

Final Selections

The following residues were picked for mutagenesis.

Catalytic Site

• M40
• Y41
• L43
• D80

Editing

• T252

Stabilzing

• K186
• A293
• L570

MUT

Purpose

In order to generate and test a large list of mutants we build a software pipeline in linux called MUT. MUT utilizes PyRosetta, Autodock Vina, and FoldX to mutate, test, and rank protein structures based on docking scores. This program was used to quarry for the optimal mutant structure for Cbz-Leu docking.

Structure

Upon initiation, MUT asks for four main inputs, the protein pdb that will be analysed, the residues that the program will mutate, the binding pocket for docking simulations, and a ligand pdb file. MUT first performs stability testing and docking to get baseline values for the future tests before it mutates the initial PDB file. At each iteration the residue is mutated to 17 other amino acids, not including Cys or Pro as they induce kinks and are difficult to model, or itself. After mutagenesis is complete files undergo stability testing and docking to determine if the new mutant is stable and a better match for the ligand. Files that fail the tests go to the kennels.

The kennel system allows for two levels of simulation. The first and fastest way is the Reductionist approach. This method disregards all files that fail any test at any point. This method is quick, but because of the variability of docking simulations, it is likely to miss key files. The Exhaustive approach takes into consideration all possible mutations. After the Reductionist approach is complete, all files are mutated to four mutants and re-scored. This method ensures that all possible combinations of mutations is tested, but is computationally intense. This pipeline can be seen in the flowchart bellow.

After a run is complete, all files are automatically ranked and ordered by binding values (more negative the better). Once an initial ranking has be completed, the user has the option to rerun docking on the selected mutants to confirm the simulation. Should the results look bad, mutants from a lower ranking can be selected or new residues can be picked.

Output
Summary

Virginia iGEM designed a Linux-based protein engineering tool called MUT. This program is used to screen protein-ligand docking across possible protein mutants. It is written from a Centros shell, but is designed to be portable across distributions. MUT generates mutant structures, subjects the resultant proteins to stability testing, and ranks the results based on protein-ligand docking data. Three programs are used to accomplish this task: PyRosetta conducts computational mutagenesis, FoldX tests protein stability, and AutoDock Vina performs protein-ligand docking. All three of these programs are available for free with an educational license, and MUT is hosted on an open source site. MUT is designed to be configurable to any iGEM team’s needs. The user inputs to MUT a protein’s PDB file, residues of interest for mutation, a binding pocket, and a ligand. After the simulation runs, the program outputs a top ten list of mutant structures along with their files.

Source
MUT on GitHub Pepsin Modeling

Purpose
Results
Conclusions
Programs Used

Autodock Vina
PyRosetta
iGEMDOCK
FoldX
LigPlot
PyMol
ChemSketch