An introduction to sequence similarity ("homology") searching

Abstract

Sequence similarity searching, typically with BLAST, is the most widely used and most reliable strategy for characterizing newly determined sequences. Sequence similarity searches can identify "homologous" proteins or genes by detecting excess similarity- statistically significant similarity that reflects common ancestry. This unit provides an overview of the inference of homology from significant similarity, and introduces other units in this chapter that provide more details on effective strategies for identifying homologs.

Figure 1

The distribution of real and expected similarity scores. The human dual specificity protein phosphatase 12 (DUS12_HUMAN) was compared to 38,114 human RefSeq proteins using the SSEARCH program. The distribution of bit-scores for all 38,114 alignments is shown (squares, □) as well as the mathematically expected distribution of normalized similarity scores (z-scores, or standard deviations above and below the mean 0) based on the size of the database, using the extreme-value distribution. The close agreement between the observed and expected distribution of scores reflects the observation that the distribution of unrelated sequence scores is indistinguishable from random (mathematically generated) scores, so sequences with significant sequence similarity can be inferred to be not-unrelated, or homologous.