Haven't done something similar yet, but my first idea: Calculate a distance matrix with one of the standard distance measures for protein data for the sequences with known binding scores. Then use a simple cluster algorithm like UPGMA to find clusters with good scores and visualize these sequences in weblogo. If you want to predict binding scores, this could at least help to find some descriptors for machine learning tools.