Software

Modules for PLUMED2:


lowlearner

(version beta) [1,2] / zenodo

lowlearner is a code for learning collective variables (CVs) from standard and enhanced sampling simulations. Installation script and examples can be found in the Zenodo dataset. It is implemented as a module for PLUMED2, an engine for free energy calculations of atomistic systems and enhanced sampling. The code requires PLUMED to be linked with LibTorch v1.8.

To use the module, you need enable lowlearner by adding the --enable-modules=lowlearner or --enable-modules=all to the PLUMED configure command. You can follow the instructions given here.

For example:

> ./configure --enable-modules=lowlearner
> make -j 4
> make install

You can ask questions or join the development discussion on PLUMED Google group.


maze

(version 1.0) [3,4] / github

maze is a code that implements enhanced sampling methods for sampling the reaction pathways of ligand unbinding. It can be installed as a module in PLUMED similarly to the lowlearner module.

During its development, maze was funded by the National Science Center grants no. 2015/19/N/ST3/02171, 2016/20/T/ST3/00488, and in part by 2016/23/B/ST4/01770.

References
  1. J. Rydzewski, and O. Valsson
    Multiscale Reweighted Stochastic Embedding: Deep Learning of Collective Variables for Enhanced Sampling
    J. Phys. Chem. A 125, 6286 (2021)
    doi:10.1021/acs.jpca.1c02869 / arXiv:2007.06377 / Zenodo:4756093 / plumID:21.023

  2. J. Rydzewski, M. Chen, T. K. Ghosh, O. Valsson
    Reweighted Manifold Learning of Collective Variables from Enhanced Sampling Simulations
    J. Chem. Theory Comput. 18, 7179 (2022)
    doi:10.1021/acs.jctc.2c00873 / arXiv:2207.14554 / plumID:21.023

  3. J. Rydzewski
    maze: Heterogeneous Ligand Unbinding along Transient Protein Tunnels
    Comp. Phys. Commun. 247, 106865 (2020)
    doi:10.1016/j.cpc.2019.106865 / arXiv:1904.03929 / plumID:19.056

  4. J. Rydzewski, and O. Valsson
    Finding Multiple Reaction Pathways of Ligand Unbinding
    J. Chem. Phys. 150, 221101 (2019)
    doi:10.1063/1.5108638 / arXiv:1808.08089 / plumID:19.066