  Despite the significant increase in computational power, molecular modeling
of protein structure using classical all-atom approaches remains inefficient,
at least for most of the protein targets in the focus of biomedical research.
Perhaps the most successful strategy to overcome the inefficiency problem is
multiscale modeling to merge all-atom and coarse-grained models. This chapter
describes a well-established CABS coarse-grained protein model. The CABS
(C-Alpha, C-Beta and Side chains) model assumes a 2-4 united-atom
representation of amino acids, knowledge-based force field (derived from the
statistical regularities seen in known protein sequences and structures) and
efficient Monte Carlo sampling schemes (MC dynamics, MC replica-exchange, and
combinations). A particular emphasis is given to the unique design of the CABS
force-field, which is largely defined using one-dimensional structural
properties of proteins, including protein secondary structure. This chapter
also presents CABS-based modeling methods, including multiscale tools for de
novo structure prediction, modeling of protein dynamics and prediction of
protein-peptide complexes. CABS-based tools are freely available at
http://biocomp.chem.uw.edu.pl/tools
