Project ID: plumID:24.011
Name: Computing the Committor with the Committor, an Anatomy of the Transition State Ensemble
Archive: https://github.com/alphatestK/Committor/raw/main/plumed_nest.zip
Category: methods
Keywords: committor, machine learning
PLUMED version: 2.9
Contributor: Peilin Kang
Submitted on: 22 Apr 2024
Publication: P. Kang, E. Trizio, M. Parrinello, Computing the committor with the committor to study the transition state ensemble. Nature Computational Science. 4, 451–460 (2024)

PLUMED input files

File Compatible with
ala2/data/template/plumed.dat tested on v2.10 tested on master with LOAD
chignolin/data/template/plumed_biased.dat tested on v2.10 tested on master with LOAD
chignolin/data/template/plumed_unbiased.dat tested on v2.10 tested on master with LOAD
dasa/data/template/plumed.dat tested on v2.10 tested on master with LOAD
dasa/data/template/plumed_distances.dat tested on v2.10 tested on master with LOAD
dasa/data/template/plumed_positions.dat tested on v2.10 tested on master with LOAD
mueller/iter1/plumed.dat tested on v2.10 tested on master with LOAD

Last tested: 22 Apr 2025, 09:56:51

Project description and instructions
The Müller-Brown potential’s simulations have been performed using the MD engine in the ves_md_linearexpansion module of PLUMED. The vacuum alanine dipeptide simulations have been carried out using the GROMACS v2021.5 MD engine and the Amber99-SB force field. The DASA reaction simulations have been carried out using the CP2K-8.1 software package at PM6 semi-empirical level. For the study of folding and unfolding of chignolin in explicit solvent, we performed our simulations using GROMACS v2021.5 the CHARMM22∗ force field and TIP3P water force field.

Click here to open manual pages for actions used in this project.

Submission history
[v1] 22 Apr 2024: original submission

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plumeDnest:24.011