  In recent years, a few multiple-resolution modelling strategies have been
proposed, in which functionally relevant parts of a biomolecule are described
with atomistic resolution, while the remainder of the system is concurrently
treated using a coarse-grained model. In most cases, the parametrisation of the
latter requires lengthy reference all-atom simulations and/or the usage of
off-shelf coarse-grained force fields, whose interactions have to be refined to
fit the specific system under examination. Here, we overcome these limitations
through a novel multi-resolution modelling scheme for proteins, dubbed
coarse-grained anisotropic network model for variable resolution simulations,
or CANVAS. This scheme enables the user-defined modulation of the resolution
level throughout the system structure; a fast parametrisation of the potential
without the necessity of reference simulations; and the straightforward usage
of the model on the most commonly used molecular dynamics platforms. The method
is presented and validated on two case studies, the enzyme adenylate kinase and
the therapeutic antibody pembrolizumab, by comparing results obtained with the
CANVAS model against fully atomistic simulations. The modelling software,
implemented in python, is made freely available for the community on a
collaborative github repository.
