Sumary - Identifying distantly related proteins

Protein sequence comparison is the most powerful tool available today for inferring structure and function from sequence because of the constraints of protein evolution---a protein fold into a functional structure. Protein sequence similarity can routinely be used to infer relationships between proteins that last shared a common ancestor 1--2.5 billion years ago. Our ability to identify distantly related proteins has improved over the past five years with the development of accurate statistical estimates, which have provided better normalization methods, and with the use of optimized scoring parameters. In using sequence similarity to infer homology, one should remember:

• Always compare protein sequences if the genes encode proteins. Protein sequence comparison will typically double the look back time over DNA sequence comparison.
• While most sequences that share statistically significant similarity are homologous, many distantly related homologous sequences do not share significant homology. (Low complexity regions display significant similarity in the absense of homology). Homologous sequences are usually similar over an entire sequence or domain. Matches that are more than 50% identical in a 20--40 amino acid region occur frequently by chance.
• Homologous sequences share a common ancestor, and thus a common protein fold. Depending on the evolutionary distance and divergence path, two or more homologous sequences may have very few absolutely conserved residues. However, if homology has been inferred between A and B, between B and C, and between C and D, A and D must be homologous, even if they share no significant similarity.
• Similarity searching techniques can be improved either by increasing the ability of a method to recognize distantly related sequences---increased sensitivity---or by lowering scores for unrelated sequences---increased selectivity. Since there are generally 1000-times more unrelated than related sequences in a sequence database, improvements that reduce the scores of unrelated sequences can have dramatic effects. The most dramatic improvements in comparison methods recently have used this approach.