**From:** Artur Hermano (*artur.hermano_at_hotmail.com*)

**Date:** Sat Mar 17 2018 - 16:41:44 CDT

**Next message:**Strenic Computations: "VMD/NMAD on AWS"**Previous message:**João Ribeiro: ""'Hands-on" Workshop on Computational Biophysics at Pittsburgh, PA, May 21-25, 2018"**In reply to:**Brian Radak: "Re:"**Messages sorted by:**[ date ] [ thread ] [ subject ] [ author ] [ attachment ]

Hello Mr. Radak

I am sorry for the late response.

Actually I am more interested in calculating the statistical error of an ABF simulation like the authors describe on pages 11 and 12 of this paper: https://dx.doi.org/10.1021%2Fjp506633n

I aim at having error bars like the two graphs in page 12, but so far I haven't figured out how to obtain this data. I already have a converged curve for the binding free energy, but no error estimates.

Thank you so much for your considerations!

-- Artur Hermano Mestrando em Biologia Computacional e Sistemas Instituto Oswaldo Cruz ________________________________ From: owner-namd-l_at_ks.uiuc.edu <owner-namd-l_at_ks.uiuc.edu> on behalf of Brian Radak <brian.radak_at_gmail.com> Sent: Thursday, March 15, 2018 10:24 To: namd-l; Srijita Paul Subject: Re: namd-l: I think you are looking for the mean acceptance probability, that is, the average probability with which an exchange is accepted. You can compute this in two different ways which, to my knowledge, are essentially equivalent for any reasonably large number of REMD cycles: 1) take the expectation of the Metropolis criterion P = min[1, exp(-Delta_ij)] where Delta_ij contains the observed energies and temperatures -- this method is cumbersome and requires sifting through a lot of data 2) just divide the number of success by the number of attempts = (50 / 450) = 0.11 = 11% The reasonableness of the observed value depends on what your exchange scheme is. I assume that your script implements a nearest neighbor sampling? If the neighbors are chosen stochastically with equal probabilities, then 11% is very close to optimal. If the neighbors are chosen in the deterministic "up/down" strategy then something closer to 20% is preferred. If you are unhappy with your acceptance probability you have two options: 1) assume that you have bad statistics and keep running until the performance numbers change or 2) start over and choose more replicas over the temperature range. HTH, BKR On Thu, Mar 15, 2018 at 7:44 AM, Srijita Paul <srijitap91_at_gmail.com<mailto:srijitap91_at_gmail.com>> wrote: Hi, Can anybody explain me the output file obtained from a remd simulation .job0.restart900.0.tcl. array set replica {index.b 4 index 3 temperature.a 283.48 exchanges_attempted 450 loc.a 4 temperature.b 289.07 temperature 286.26 exchanges_accepted 50 loc.b 18 index.a 2} exchanges_attempted 450 exchanges_accepted 50 Is it a good result for remd? How can I find acceptance probability for my system?

**Next message:**Strenic Computations: "VMD/NMAD on AWS"**Previous message:**João Ribeiro: ""'Hands-on" Workshop on Computational Biophysics at Pittsburgh, PA, May 21-25, 2018"**In reply to:**Brian Radak: "Re:"**Messages sorted by:**[ date ] [ thread ] [ subject ] [ author ] [ attachment ]

*
This archive was generated by hypermail 2.1.6
: Tue Dec 31 2019 - 23:19:46 CST
*