Summary of the main results

Wild type simulations

First of all, the equilibration (stabilization of temperature, pressure and density) was accurate for both states of LOV2 domain.

• For dark state, see here

• For light state, see here

Secondly, we analyzed many important characteristics of the system:

- RMSD was analyzed of all residues' alpha carbon, which shows us that the protein was stable and that our simulation was apparently trustable.

• For dark state, see here

• For light state, see here

- RMSF was analyzed for residues' side chains. We were able to localize, helped by some differential analysis some residues that move much more than :others, which would mean that these moving residues were possibly implicated in the movement transmission that induces the general conformational change of the protein :upon light activation. The movement of these residues were not correlated. And further analysis demonstrate that we were not able to see the conformational change (see :below).

• For dark state, see here

• For light state, see here

• For the differential analysis, see here

- The angle between the main beta sheet and the J-alpha helix of LOV2 domain was computed, and we could not see any periodic main movement neither in the :dark nor the light state.

• For the differential analysis of the angle, see here

- Side chain dihedral angle of the reactive cystein (residue 450) was computed for both state.

Interestingly, in the dark state we were able to find that the sulfur atom of this cystein point 30% of the time toward the cofactor, FMN (molecule that reacts with the protein :upon light activation) and 70% of the time toward the opposite side of the FMN.

• Important graphs and explanations, see here

These results were expected, because they confirm the in vitro results obtain by [Halavaty et al.], and this confirm once again that our simulation seems to be accurate.

In the light state, the cystein is covalently bonded with the cofactor, FMN, so the side chain dihedral angle was far more stable than in the dark state. This result was :completely expected because after a covalent bonding with a big set of atom such as the FMN, the cystein's side chain is less free to move.

• Important graphs and explanations, see here

Simulations of non-light activated LOV2 domain with specific mutations

I427F

L453G

Click on each title below to access the results.

Fusion of the LOV domain and the trpR DNA-binding domain

The first step in our computational study of the LOV domain was to fuse the 2 domains of interest in VMD, namely the LOV domain and the TrpR DNA-binding domain. It allowed to visualize the different proteins tried by Sosnick. The working protein, that we call LovTAP is the result of the fusion at PHE22 of TrpR.

Dark State simulation

This is where we run a long simulation on the dark state system and analyze the output.

In the analysis, we tried to achieve the following goals:

• find a structural change in the Jα helix based on the simulation
• find residues showing different comportment in dark and light state

Light state simulation

The light state corresponds to the photoactivated state of the LOV domain, and here are gathered results concerning the light state from a 60ns simulation starting after previous equilibration.

We mainly focused on an analysis of dihedral angles to understand the movement of useful residues.

Differential Analysis

Now that the two states are well-characterized, we want to confront the two visions of the protein. This part is thus devoted to the comparison of the two states.

After a detailed analysis based on both previous simulation, we were able to determine that the stability of the Cystein 450 is highly correlated with the creation of the covalent bound to the FMN.

Mutations

Our final goal is to find a way to make the protein more stable, or to increase its affinity: that's why we imagined some ponctual mutations on some particular residues to do so.
We picked the more mobile residues in the beta sheet, closest to the CYS450, and see if they can improve the overall stability. Here is a list of the mutations planned:

• ILE427 mutated in PHE
• LEU453 mutated in GLY

These were partly based on studies made by :

1. Zoltowski: Mechanism-based tuning of a LOV domain photoreceptor
2. Christie, Steric Interactions Stabilize the Signaling State of the LOV2 Domain of Phototropin 1

see here for more information.

We ran two other simulations after mutating the LOV domain at these residues and we discovered a much better stability of the cystein due to I427F. In this configuration, the cystein points toward the FMN in 57,2% of the cases, which is almost twice better as in the wild type protein!

Validation of the equilibration

This part brings together results validating our equilibration. This one is composed of 3 different steps:

• first a minimization, where we try to find a minimum of energy. In fact, it is essential to find a stable point on the potential energy surface in order to begin dynamics. At a minimum on the potential energy surface, the net force on each atom vanishes.

Constraints are imposed during minimization.
To minimize we need a function (provided by the forcefield) and a starting set of coordinates. The magnitude of the first derivative can be used to determine the direction and magnitude of a step (i.e. change in the coordinates) required to approach a minimum configuration. To reach the minimum the structure must be successively updated by changing the coordinates (taking a step) and checking for convergence. Each complete cycle of differentiation and stepping is known as a minimization iteration.

• a second step composed with a heating of our protein allows to increase the temperature from 5 to 300K.

• finally, we do an equilibration. This equilibration stage is required because the input structure is typically not within the equilibrium phase space of the simulation conditions, particularly in systems as complex as proteins, which can lead to false trajectories in protein dynamics.

The equilibration can itself be divided into 3 phases: - an NPT - an NVT - again an NPT
The aim of doing a minimization followed by an equilibration simulation is to generate a trajectory for the system, which will be analysed further.

This part gathers together plots confirming that our minimization-heating-equilibration were correct, and that we followed with a good file of trajectories.