Collective variables (CVs) are functions of the coordinates of a molecular system and provide a means to project its conformational state onto a lower-dimensional space. By stimulating the dynamics of a judiciously chosen set of CVs, one can obtain an enhanced sampling of the configuration space, including regions that are otherwise difficult to access. The system's free energy as a function of these CVs can be used to characterize the relative stability of different states and to identify pathways connecting them.
CVPack is a Python package that provides pre-defined CVs for the powerful molecular dynamics engine OpenMM. All these CVs are subclasses of OpenMM's Force class and, as such, can be directly added to a CustomCVForce or used to define a BiasVariable for Metadynamics.
The CVs implemented in CVPack are listed in the table below.
CVPack is available as a conda package on the mdtools channel. To install it, run:
conda install -c conda-forge -c mdtools cvpackOr:
mamba install -c mdtools cvpackTo use CVPack in your own Python script or Jupyter notebook, simply import it as follows:
import cvpackDocumentation for the latest CVPack version is available on Github Pages.
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