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.

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 FMN, and see if they can improve hte overall stability. Here is a list of the mutations planned:

• ILE427 mutated in PHE
• ILE427 mutated in LEU
• LEU453 mutated in ALA
• LEU453 mutated in GLY

These were 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.

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.