Output of the XOM clustering: XOM [34] is a relatively new approach for dimensionality reduction and clustering of multidimensional data. We used this approach to visualise the distance relations of the 471 investigated variable motif positions by employing the distance measure defined in (5). Here, XOM delivers a two-dimensional mapping of the distance relations of all LOPs. Coloured according to the topology state in which the corresponding motif is located, three well separable clusters can be seen. The LOP distances which contribute to the cluster formation are mainly dictated by the propensities of hydrophilic, hydrophobic, and polar residues. Thus, the XOM output reflects physicochemical correspondences which also applies for the general cluster arrangement, with the cluster of LOPs mainly observed in “trans” topology states (which corresponds basically to helix caps) located between the other two clusters. Similar to the UPGMA-tree depicted in Figure 4, the XOM output points to a good separability and predictability of topology states of short sequence motifs from their amino acid sequence in variable motif positions.