Why do people suggest that
translated sequences be used to search for relatives in
databanks?
DNA vs Protein Sequence
DNA
is composed of only four kinds of units -A, G, C and T- and even if gaps were
not allowed, it would be anticipated that, on the average, 25% of the residues
of any two aligned sequences would be identical. In fact, there would be a
dispersion around the mean expectation, and a predictable fraction of random
cases would be as much as 35% identical. Once we decide to allow gaps in the
sequences, then the range of chance similarities between two unrelated
sequences can exceed 50%, thereby obscuring any genuine relationships that may
exist.
On
the other hand, protein sequences are composed of a 20 aa alphabet determined
by 61 degenerate codons. When the DNA sequences are translated into 21
different types of codons (20 aa and a terminator), the information is
sharpened up considerably. The 'wrong-frame' information is discarded, and
third-base degeneracies are consolidated. All in all, the signal-to-noise
ratio is greatly improved for the specific purpose of identifying protein
relatives. It is accepted that convergence phenomena in aa sequences are very
rare and thus aa similarity almost always means homology. Furthermore, aa
sequences may still show a similarity derived from common folding patterns and
function of the proteins, even while their coding DNA sequences might have
strongly diverged due to other selective pressures existent at the genome
level (e.g., G+C pressure, preferential usage of synonymous codons, etc.).
Protein evolution is governed by the constraint of maintaining a
characteristic fold which enables some function. Thus, it is possible to infer
relationships between proteins that last shared a common ancestor 1-2.5
billion years ago by conducting protein searches, doubling the lookback time
obtained performing DNA database searches.
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