To study how phosphorylation affects the binding of replication protein A (RPA) to ssDNA.
Though much work is going on experimentally, there is also an effort to contribute to this study through
simulations.
In this regard, we are modeling a few systems, which can be used to run dynamics, free energy perturbations, etc. as and when desired in the project.
Simulation can be powerful and fast, but still needs vital inputs from experimental data.
Work :
Initially, we started of with a base system from the Protein data bank, which consisted of the RPA 70 binding subunit bound to a ssDNA (sequence: CCCCCCCC).
This we call system A. Keeping this as the base we solvated the system and prepared a box wherein the RPA and DNA are at the center and there is water up to a distance of 3Ang on all sides.
This system was then subject to dynamics and minimization runs, in order to bring it to its natural state or in other words the minimum energy state. This we call system B.
The third system has one of the residues phosphorylated. One particular Serine residue (S208) was chosen and phosphorylated.
This meant replacing the serine residue by phosphoserine residue and then subjecting this to dynamics and minimization to obtain the natural state.
So, we have a phosphorylated RPA subunit bound to ssDNA at the center and water up to 3Ang on all sides to form a box that can be used for periodic boundary simulations. This we call system C.
Technical :
Technically, this meant learning in detail software called TINKER, which was used for building the systems and running dynamics on it.
Being simple software there was a need to analyze and modify the source code quite a few times, to suit our needs.
This was done to accommodate the large systems, while implementing periodic boundary conditions and most importantly during phosphorylation.
Software called SOLVATE was used during the solvation of the systems.
Software Visual Molecular Dynamics (VMD) was used for viewing and studying the systems.
Since phosphoserine is not a residue recognized by TINKER, replacing serine by phosphoserine required adding its force field parameters to TINKER and modifying its code.
Dynamics and minimizations need constant monitoring to ensure they are running and in the desired direction. Learning concepts of modeling and dynamics and to some extent biology was essential.