The average work to move molecular scale objects closer together or further apart is difficult to predict because the calculation depends on the many other objects in the surroundings. For example, you might find if easy to cross a four-lane street of grid-locked cars (requiring a small amount of work) but nearly impossible to cross a highway with cars speeding by at 65mph (requiring a lot of work.) When the system is a protein whose overall structure is expanded or contracted, there exist a myriad possible configurations which must be included to obtain the average required work. Such a calculation is computationally expensive and likely inefficient. Instead, we have been using a method (steered molecule dynamics) developed by Schulten and coworkers based on Jarzynski's equality. It helps us compute the equilibrium work using (driven) paths far outside of equilibrium. The trouble is that the surroundings get in the way and drive the system along paths that get out of bounds quickly.
In previous work, we tamed these naughty paths by reigning them all in to a tighter region of structures. Unfortunately, this may be too aggressive. The key is to realize that not all paths are naughty. That is, that there may be more than one region of structures that contribute significantly to the calculation of the work. We found that we could include such not-quite-naughty paths and still maintain the efficiency of our adaptive steered molecular dynamics. I described the early work on ASMD in my recent ACS Webinar.
This research project was truly performed in collaboration. My recent graduate student, Gungor Ozer, did the work while he was a postdoc at Boston University. Tom Keyes hosted him there and gave great insight on the sampling approach. Stephen Quirk, as always, grounded us in the biochemistry.
The title of the article is "Multiple branched adaptive steered molecular dynamics.” The work was funded by the NSF. It was just released at J. Chem. Phys. 141, 064101 (2014). Click on the JCP link to access the article.
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