We present results obtained for anisotropic potentials for protein simulations extracted from the continually growing databases of protein structures. This work is based on the assumption that the detailed information on molecular conformations can be used to derive statistical (a.k.a. ‘knowledge-based’) potentials that can describe on a coarse-grained level the side chain–side chain interactions in peptides and proteins. The complexity of inter-residue interactions is reflected in a high degree of orientational anisotropy for the twenty amino acids. By including in this coarse-grained interaction model the possibility of quantifying the backbone–backbone and backbone–side chain interactions, important improvements are obtained in characterizing the native protein states. Results obtained from tests that involve the identification of native-like conformations from large sets of decoy structures are presented. The method for deriving orientation-dependent statistical potentials is also applied to obtain water–water interactions. Monte Carlo simulations using the new coarse-grained water model show that the locations of the minima and maxima of the oxygen–oxygen radial distribution function correspond well with experimental measurements.