Source:NIC Workshop 2006: From Computational Biophysics to System Biology, Jan H. Meinke, Michael T. Zimmermann, Sandipan Mohanty, Ulrich H. E. Hansmann, Eds, John von Neumann Institute for Computing, Julich, 34:21-28, 2006
In this contribution we describe a successful approach to protein modeling which is based on reduced representation of protein conformational space, all-atom-refinement, evaluation and selection of the best molecular models. During the sixth CASP (Critical Assessment of protein Structure Prediction) community-wide experiment our methodology (referred further as CABS) proven to be one of the best performing methods for protein structure prediction, applied both for comparative modeling and to de novo folding. The newest applications of the CABS modeling technology include: study of protein folding thermodynamic, dynamics in the denatured state and folding pathways, structure prediction based on sparse and inaccurate experimental data and prediction of protein-protein interactions or flexible ligand docking. The CABS reduced model could be easily integrated with the all-atom approaches providing solid starting point for reliable multiscale simulations of large biomolecular systems.