The HP model is one of the most popular discretized models for attacking the protein folding problem, i.e., for the computational prediction of the tertiary structure of a protein from its amino acid sequence. It is based on the assumption that interactions between hydrophobic amino acids are the main force in the folding process. Therefore, it distinguishes between polar and hydrophobic amino acids only and tries to embed the amino acid sequence into a two- or three-dimensional grid lattice such as to maximize the number of contacts, i.e., of pairs of hydrophobic amino acids that are embedded into neighboring positions of the grid. In this paper, we propose a new generalization of the HP model which overcomes one of the major drawbacks of the original HP model, namely the bipartiteness of the underlying grid structure which severely restricts the set of possible contacts. Moreover, we introduce the (biologically well-motivated) concept of weighted contacts, where each contact gets assigned a weight depending on the spatial distance between the embedded amino acids. We analyze the applicability of existing approximation algorithms for the original HP model to our new setting and design a new approximation algorithm for this generalized model.