Abstract: Disclosed are computational methods, and associated hardware and software products for identifying a set of target pockets for broad-spectrum drug development based on a provided set of protein motifs. A method of identifying the provided set protein motifs based on a plurality of protein motifs in also disclosed herein. Additional methods for generating a plurality of protein motifs based on both aligned protein structure and sequences are disclosed herein.

Abstract: Disclosed are computational methods of clustering a set of protein structures based on local and pair-wise global similarity values. Pair-wise local and global similarity values are generated based on pair-wise structural alignments for each protein in the set of protein structures. Initially, the protein structures are clustered based on pair-wise local similarity values. The protein structures are then clustered based on pair-wise global similarity values. For each given cluster both a representative structure and spans of conserved residues are identified. The representative protein structure is used to assign newly-solved protein structures to a group. The spans are used to characterize conservation and assign a “structural footprint” to the cluster.