Protein fold recognition (threading) involves the prediction of a protein's three-dimensional shape based on its similarity to a protein whose structure is known. Fold predictions are low resolution; no effort is made to rotate the protein's component amino acid side chains into their correct spatial orientations. Rather, the goal is to recognize the protein family member that most closely resembles the target sequence of unknown structure and to create a sensible alignment of the target to the structure (i.e., a structure-sequence alignment). To complement this structure prediction method we have implemented a low resolution molecular graphics tool. Since amino acid side chain orientation is not relevant in fold recognition, amino acid residues are represented by abstract shapes or glyphs much like Lego (tm) blocks. We also borrow techniques from coparative streamline visualization to provide clean depictions of the entire protein struture model. By creating a low resolution representation of protein structure, we are able to approximately double the amount of information on the screen. This implementation also possesses the advantage of eliminating distracting and possibly misleading visual clutter resulting from the mapping of protein alignmnt information onto a high resolution display of a known structure.