Assignments for Wednesday's class:

Assignment for Friday's class:


PAM versus Blosum

(illustrations of homologs that do not show significant sequence similarity in pairwise comparisons :

Jim Knox (MCB-UConn) has studied many proteins involved in bacterial cell wall biosynthesis and antibiotic binding, synthesis or destruction. Many of these proteins have identical 3-D structure, and therefore can be assumed to be homologous; however, the tests based on pairwise sequence comparisons fail to detect this homologies. (for example, enzymes with GRASP nucleotide binding sites are depicted here.)

DNA replication involves many different enzymes. Some of the proteins do the same thing in bacteria, archaea and eukaryotes; they have similar 3-D structures (e.g.: sliding clamp, E. coli dnaN and eukaryotic PCNA, see Edgell and Doolittle, Cell 89, 995-998), but again, the above tests fail to detect homology.

Helicase and F1-ATPase. Both form hexamers with something rotating in the middle (either the gamma subunit or the DNA; D. Crampton, pers. communication). The monomers have the same type of nucleotide binding fold (picture)


blast and commandline blast (the slides contain links that only become accessible, after you switched to presentation mode)

Discussion 2

E-values and multiple tests

Types of Error in a Databank search

False positives: The number of false positives are estimated in the E-value. The P-value or significance value gives the probability that a positive identification is made in error (same as with drug tests).
Danger: avoid fishing expeditions. If you do 100 tests on random data, you expect one to be positive at the 1% significance level.

You could apply the Bonferroni correction:

The significance level for the individual test is calculated through dividing the overall desired significance level by the number of parallel tests. The null-hypothesis of the overall test that is to be be rejected is that None of the individual tests is significantly different from chance. (The opposite of none being "at least one")

False negatives: Homologous sequences in the databank that are not recognized as such. If there are only 12000 different protein families, on average a sequence should have (size of the databank)/12000 matches. In other words, the number of false negatives is probably very large.

If time:

Goals class 10