The biological activity of a protein typically depends on the presence of a small number of functional residues. Identifying these residues from the amino acid sequences alone would be useful. Classically, strictly conserved residues are predicted to be functional but often conservation patterns are more complicated. Here, we present a novel method that exploits such patterns for the prediction of functional residues. The method uses a simple but powerful representation of entire proteins, as well as sequence residues as vectors in a generalised 'sequence space'. Projection of these vectors onto a lower-dimensional space reveals groups of residues specific for particular subfamilies that are predicted to be directly involved in protein function. Based on the method we present testable predictions for sets of functional residues in SH2 domains and in the conserved box of cyclins.