Picasso: generating a covering set of protein family profiles.

Abstract

Evolutionary classification leads to an economical description of protein sequence data because attributes of function and structure are inherited in protein families. This paper presents Picasso, a procedure for deriving a minimal set of protein family profiles that cover all known protein sequences. Picasso starts from highly overlapping sequence neighbourhoods revealed by all-on-all pairwise Blast alignment. Overlaps are reduced by merging sequences or parts of sequences into multiple alignments. For maximum unification, the multiple alignments must reach into the twilight zone of sequence similarity. Sensitive and selective profile-profile comparison allows unification down to about 15% pairwise sequence identity. Families unified through a short conserved sequence motif are associated with multiple full-length alignments describing different subfamilies. Domains that are mobile modules are identified based on their association with different sets of neighbours. The result is 10000 unified domain families (excluding singletons) representing functionally related proteins and recovering classical prolific domain types in high numbers. The classification is useful, for example, in developing strategies for efficient database searching and for selecting targets to complete the map of all 3-D structures.