{"action":"created","issue":{"url":"https://api.github.com/repos/choderalab/pymbar/issues/224","repository_url":"https://api.github.com/repos/choderalab/pymbar","labels_url":"https://api.github.com/repos/choderalab/pymbar/issues/224/labels{/name}","comments_url":"https://api.github.com/repos/choderalab/pymbar/issues/224/comments","events_url":"https://api.github.com/repos/choderalab/pymbar/issues/224/events","html_url":"https://github.com/choderalab/pymbar/issues/224","id":150102102,"number":224,"title":"Can I use PyMBAR on NAMD accelerated MD simulations to generate a 2D PMF?","user":{"login":"kkastner","id":18597930,"avatar_url":"https://avatars.githubusercontent.com/u/18597930?v=3","gravatar_id":"","url":"https://api.github.com/users/kkastner","html_url":"https://github.com/kkastner","followers_url":"https://api.github.com/users/kkastner/followers","following_url":"https://api.github.com/users/kkastner/following{/other_user}","gists_url":"https://api.github.com/users/kkastner/gists{/gist_id}","starred_url":"https://api.github.com/users/kkastner/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/kkastner/subscriptions","organizations_url":"https://api.github.com/users/kkastner/orgs","repos_url":"https://api.github.com/users/kkastner/repos","events_url":"https://api.github.com/users/kkastner/events{/privacy}","received_events_url":"https://api.github.com/users/kkastner/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"milestone":null,"comments":1,"created_at":"2016-04-21T15:06:06Z","updated_at":"2016-04-21T18:24:30Z","closed_at":null,"body":"I wanted to know if it is possible to use PyMBAR to generate a 2D Potential of Mean Force (PMF) graph using energies obtained from NAMD. The energies need to be reweighted though as I used accelerated MD (aMD). I wanted to combine the PMFs of two simulations containing the same protein but different ligands, and they are both huge simulations (~100,000 atoms each). Is it possible to do all of this using PyMBAR?"},"comment":{"url":"https://api.github.com/repos/choderalab/pymbar/issues/comments/213050031","html_url":"https://github.com/choderalab/pymbar/issues/224#issuecomment-213050031","issue_url":"https://api.github.com/repos/choderalab/pymbar/issues/224","id":213050031,"user":{"login":"mrshirts","id":4274132,"avatar_url":"https://avatars.githubusercontent.com/u/4274132?v=3","gravatar_id":"","url":"https://api.github.com/users/mrshirts","html_url":"https://github.com/mrshirts","followers_url":"https://api.github.com/users/mrshirts/followers","following_url":"https://api.github.com/users/mrshirts/following{/other_user}","gists_url":"https://api.github.com/users/mrshirts/gists{/gist_id}","starred_url":"https://api.github.com/users/mrshirts/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/mrshirts/subscriptions","organizations_url":"https://api.github.com/users/mrshirts/orgs","repos_url":"https://api.github.com/users/mrshirts/repos","events_url":"https://api.github.com/users/mrshirts/events{/privacy}","received_events_url":"https://api.github.com/users/mrshirts/received_events","type":"User","site_admin":false},"created_at":"2016-04-21T18:24:30Z","updated_at":"2016-04-21T18:24:30Z","body":"Great question.  I'm not 100% sure exactly the calculation, but let me try to follow up to reach a good point. \r\n\r\nGenerally, you have a set of Hamiltonians of interest. There are K_sampled that you actually have collected data from, and K_unsampled additional states you did not collect samples at, but that you would like to calculate thermodynamic properties at.  For example, if you are doing a PMF, the K sampled states would be the all of the harmonic restraint hamiltonians, and the unsampled state would be state without weights. You then need to be able to calculate the difference in energy of each point from the sampled state between the sampled state and the unsampled state.  With PMF's this is pretty easy, since you just need to know the distance difference that is used in the harmonic oscillator, \r\n\r\nA SECOND step would be to calculate the probability of the ligand being in each grid square in the unsampled state; essentially, you have a box function (one inside the box, zero outside) and you want to know the expectation value of that box function.\r\n\r\nNote that the grid over which you are calculating the PMF does not have to correspond to the grid that the harmonic restraints are on. You COULD approximate the PMF by just using the free energies of the harmonic restraints, but there are some approximations associated with that choice.\r\n\r\nWe have an example of how to do this in pymbar/examples/parallel-tempering-2dpmf/.\r\n\r\nI'm not sure exactly what is meant by \"combining the two PMF's\" of different ligands.  Can you write out the mathematical definition of combining? \r\n\r\n\r\n"}}