×

Indexed by

Improving accuracy of biased Alchemistic simulations

Dalibor Trapl1, Carmen Cuerdo del Río1, Pavel Kříž2, Vojtěch Spiwok1*

1 Department of Biochemistry and Microbiology, University of Chemistry and Technology, Prague, Czech Republic

2 Department of Mathematics, University of Chemistry and Technology, Prague, Czech Republic

* Corresponding authors emails: spiwokv@vscht.cz
DOI10.24435/materialscloud:2020.0049/v1 [version v1]

Publication date: May 03, 2020

How to cite this record

Dalibor Trapl, Carmen Cuerdo del Río, Pavel Kříž, Vojtěch Spiwok, Improving accuracy of biased Alchemistic simulations, Materials Cloud Archive 2020.0049/v1 (2020), doi: 10.24435/materialscloud:2020.0049/v1.

Description

Alchemistic simulations are versatile tools for prediction of relative free energy differences. Accuracy of these methods depends critically on sampling of orthogonal (non-Alchemistic) degrees of freedom. Here we apply flying Gaussian method to accelerate such orthogonal degree of freedom – peptide bond cis/trans iso-merisation. The approach is demonstrated on prediction of pKa value of N-acetylproline. Isomerization of the amide bond was accelerated in this simulation by multiple orders of magnitude. Alchemistic free energy was obtained by reweighting. We also demonstrate that the accuracy of biased Alchemistic simulations can be significantly improved by a simple redefinition of the thermodynamic cycle using a flattening. Such redefinition can be applied a posteriori to improve the accuracy of biased Alchemistic simulations.

Materials Cloud sections using this data

No Explore or Discover sections associated with this archive record.

Files

File name Size Description
tiwithfg.zip
MD5md5:97d1e77589cb297a43cd80846f2bb3e6
4.0 MiB Input files (input structures, topology, Gromacs and Plumed input files, analysis scripts) for simulations used to demonstrate functionality of combined thermodynamic integration and flying Gaussian method. The method is demonstrated on N-acetylproline. Tested on OpenMPI 4.0.0, Gromacs 2018.5 and Plumed 2.5.0. Submission scripts are provided.
README.txt
MD5md5:79985d56c9e009fd48982cea23428352
7.0 KiB README.txt file with descriptions.

License

Files and data are licensed under the terms of the following license: Creative Commons Attribution 4.0 International.
Metadata, except for email addresses, are licensed under the Creative Commons Attribution Share-Alike 4.0 International license.

External references

Journal reference (Paper in which the method is described.)
D. Trapl, C. Cuerdo del Río, P. Kříž, V. Spiwok, J. Chem. Phys. (submitted).

Keywords

Alchemistic simulations Biased simulations Reweighting

Version history:

2020.0049/v1 (version v1) [This version] May 03, 2020 DOI10.24435/materialscloud:2020.0049/v1