Official Project Description
Force fields aren't only a thing in far off galaxies, but are also an integral part of molecular dynamics simulations.
Principally, molecular dynamics simulations are evaluating Newton's laws of motion iteratively.
Each atom in the simulation is given a position, velocity, and has some forces acting upon it.
We then take a short step forward in time (often 2-4 femtoseconds), update the positions of each atom based on the last known position, velocity, and acceleration, before re-evaluating the forces acting upon each atom.
Repeating this millions to trillions of times (or more), gives us a physics-based movie of atoms moving which we use to give insight into the behavior of our favorite proteins. One of the fundamental steps of this process is calculating the forces on each atom.
The collective model describing how to calculate these forces is called a force field.
Through the years, many force fields have been derived and refined, each one focusing on improving certain forces or behaviors of the simulation.
While tests are usually performed when force fields are redeveloped, it is difficult to achieve robust sampling (e.g.
many observations of rare events).
Here, we are continuing our efforts to catalog the performance and accuracy of these force fields.
In this project series, we use the ebolavirus protein VP35, as our test model.
VP35 is used by ebolavirus to protect viral RNA from recognition by the immune system which the Bowman lab has extensively characterized.
Notably, we have identified a cryptic pocket which we have experimentally characterized, along with several mutations that both close and open the pocket.
This suite of data provides a robust means to characterize the ability of force fields to both identify cryptic pockets as well as the sensitivity of force fields to mutations in proteins. p18291 - amber14sb with tip3p water. p18292 - charmm36m with tip3p water. p18294 - aadisp with aadisp water. p18295 - amber99sb*-ILDN with tip4pd water.