Software

pKa calculation with a proton transfer collective variable

For a Plumed nest archive with example input files for a path-metadynamics simulation of acetic acid dissociation and proton transfer with Plumed and CP2K click on this link. Further instructions: These CP2K/Plumed input files are for a PMD simulatation of the acetic acid de-protonation reaction in water and pKa calculation as performed in Ref. [2]. It requires PLUMED compiled with the Path-CV code (PathCV.cpp provided below) and the PTCV code (proton.cpp provided within this archive). All the parameters used are explained in the plumed input file and the article in Ref. [2].

To add the PROTON (proton transfer collective variable) functionality to your plumed, copy the Proton.cpp file found in the above Plumed nest archive in your plumed-2 distribution in the directory src/vatom/Proton.cpp. Then recompile the Plumed code (make, make install, make doc). The documentation on how to use the proton transfer CV is found in user-doc/html/index.html under Collective variables / Groups and Virtual Atoms / PROTON.

plumID:19.033

Path-metadynamics with Plumed 2.5

To use the path-metadynamics method [1] with Plumed download the PathCV.cpp file and save this file in your plumed-2 distribution in the directory src/function/PathCV.cpp. We are using Plumed version 2.5 at the moment). Secondly, add the following to the file in user-doc/bibliography.bib :

	  @article{ensing12,
            Author = {Grisell Díaz Leines and Bernd Ensing},
            Journal = {Phys. Rev. Lett.},
            Month = {Feb},
            Pages = {020601},
           Title = {Path finding on high-dimensional free energy landscapes},
           Volume = {109},
           Year = {2012}}
	  
After recompiling the code (make, make install, make doc) the documentation on how to use path-metadynamics is found in user-doc/html/index.html under Collective variables / Functions / PATHCV.

For a Plumed nest archive with example input files for path-metadynamics simulation of a proline tetramer with Plumed and Gromacs click on this link. Further instructions: This allows to run multiple-walker path-metadynamics on the right- to left-handed helix transition in tetrameric polyproline with a 3D CV-space. It can be easily adjusted to bigger systems with higher-dimensional CV-spaces. It requires PLUMED compiled with MPI and with the Path-CV code provided in the URL above. It also requires an MD engine that can run parallel replicas. We use GROMACS 5.1.4 compiled with MPI. Notice that in the PLUMED input files "WALKERS_ID" must be adjusted for the different walkers. This example is taken from the work published in Ref. [2].

plumID:19.034

References:

  1. Path finding on high-dimensional free energy landscapes. Grisell Díaz Leines and Bernd Ensing, Phys. Rev. Lett. 109 (2012), 020601 DOI: 10.1103/PhysRevLett.109.020601
  2. Advances in enhanced sampling along adaptive paths of collective variables. Alberto Pérez de Alba Ortíz , Ambuj Tiwari, Rakesh C. Puthenkalathil, and Bernd Ensing, J. Chem. Phys. 149 (2018), 072320 DOI: 10.1063/1.5027392



Trace the minimum free energy pathway in a metadynamics bias potential

The trace_irc code described in Ref. [2] can be downloaded from this link. The program can read metadynamics output files from CPMD, CP2K, and PLUMED and trace the lowest free energy pathway. A brief description is found in a README file and a list of the keywords is generate by running trace_irc.x -help. There is no manual unfortunately. In case you wish to addapt the program to read your favorite input, this should not be so hard as the C code is commented and not difficult to read. Good luck playing with it.

References:

  1. A recipe for the computation of the free energy barrier and lowest free energy path of concerted reactions. Bernd Ensing, Alessandro Laio, Michele Parrinello and Michael L. Klein, J. Phys. Chem. B 109 (2005), 6676-6687 DOI: 10.1021/jp045571i
  2. Perspective on the reactions between F- and CH3CH2F: the free energy landscape of the E2 and SN2 reaction channels. Bernd Ensing and Michael L. Klein, Proc. Natl. Acad. Sci., USA 102 (2005), 6755-6759 DOI: 10.1073/pnas.0408094102
  3. Metadynamics as a tool for exploring the free energy landscape of chemical reactions. Bernd Ensing, Marco De Vivo, Zhiwei Liu, Preston Moore, and Michael L. Klein, Acc. Chem. Res. 39 (2006), 73-81 DOI: 10.1021/ar040198i



Hybrid MD with cm3d code

Here is a pre-beta version of the cm3d molecular dynamics program including the adaptive atomistic/coarsegrained multiscale algorithm. Feel free to have a look at the code. Currently the algorithm appears to work properly and stable and we are now at the stage to profile and tune the performance of the code. In particular the parallization needs to be fixed... Also there is currently not a good manual on how to setup your own system for a hybrid MD simulation with cm3d. There is actually a short manual that lists the keywords in LaTeX format provided with the source code. I guess that the source code is the best manual at the moment. In any case, you can consider yourself as being very brave to tryout this code at its current developing stage. Reports of bugs are always gratefully appreciated. Enjoy!

  • Program: cm3d.hybridMD.tar.gz
    Save this file in a new directory and untar (tar -xzvf cm3d.hybridMD.tar.gz). Move to the "compile" directory and compile the source using/adapting one of the Makefiles, for example: "make -f Make.osx" on a Mac or "make -f Make.linux.fast" on a linux machine. A LaTeX manual is found in the directory "manual".
  • Example run: hexane.tar.gz
    Save this file in a new directory and untar (tar -xzvf hexane.tar.gz). Move into the created "hexane" directory and try to run the input using "cm3d.osx input > output" (assuming that the program was named "cm3d.osx" and is in the path). Note that with the provided input settings this simulation may take a couple of days on a fast computer.

References:

  1. Energy conservation in adaptive hybrid atomistic/coarse-grain molecular dynamics. Bernd Ensing, Steven O. Nielsen, Preston B. Moore, Michael L. Klein, and Michele Parrinello, J. Chem. Theory Comput. 3 (2007), 1100 - 1105, DOI: 10.1021/ct600323n
  2. Adaptive multiscale molecular dynamics of macromolecular fluids. Steven O. Nielsen, Preston B. Moore, and Bernd Ensing, Phys. Rev. Lett. 105 (2010), 237802 DOI: 10.1103/PhysRevLett.105.237802
  3. Recent progress in multiscale molecular dynamics simulation of soft matter. Steven O. Nielsen, Rosa E. Bulo, Preston B. Moore, Bernd Ensing, Phys. Chem. Chem. Phys. 12 (2010), 12401 - 12412 DOI: 10.1039/c004111d