lec05 - 1 CSE 427 Computational Biology BLAST Alignment...

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Unformatted text preview: 1 CSE 427 Computational Biology BLAST Alignment score significance PCR and DNA sequencing 2 The Plan BLAST Scoring Another Bio Interlude: PCR & Sequencing 3 A Protein Structure: (Dihydrofolate Reductase) !! 4 Sequence Evolution Nothing in Biology Makes Sense Except in the Light of Evolution Theodosius Dobzhansky , 1973 Changes happen at random Deleterious/neutral/advantageous changes unlikely/possibly/likely spread widely in a population Changes are less likely to be tolerated in positions involved in many/close interactions, e.g. enzyme binding pocket protein/protein interaction surface 5 BLAST: Basic Local Alignment Search Tool Altschul, Gish, Miller, Myers, Lipman, J Mol Biol 1990 The most widely used comp bio tool Which is better: long mediocre match or a few nearby, short, strong matches with the same total score? score-wise, exactly equivalent biologically, later may be more interesting, & is common at least, if must miss some, rather miss the former BLAST is a heuristic emphasizing the later speed/sensitivity tradeoff: BLAST may miss former, but gains greatly in speed 6 BLAST: What Input: a query sequence (say, 300 residues) a data base to search for other sequences similar to the query (say, 10 6- 10 9 residues) a score matrix (r,s), giving cost of substituting r for s (& perhaps gap costs) various score thresholds & tuning parameters Output: all matches in data base above threshold E-value of each 7 BLAST: How Idea: find parts of data base near a good match to some short subword of the query Break query into overlapping words w i of small fixed length (e.g. 3 aa or 11 nt) For each w i , find (empirically, ~50) neighboring words v ij with ungapped score (w i , v ij ) > thresh 1 Look up each v ij in database (via prebuilt index) -- i.e., exact match to short, high-scoring word Extend each such seed match (bidirectional) Report those scoring > thresh 2 , calculate E-values 8 BLAST: Example deadly de (11) -> de ee dd dq dk ea ( 9) -> ea ad (10) -> ad sd dl (10) -> dl di dm dv ly (11) -> ly my iy vy fy lf ddgearlyk . . . dd ge 10 ea r ly 18 7 (thresh 1 ) query DB hits 10 (thresh 2 ) BLOSUM 62 A R N D C Q E G H I L K M F P S T W Y V A 4-1 -2 -2 0 -1 -1 0 -2 -1 -1 -1 -1 -2 -1 1-3 -2 R-1 5 0 -2 -3 1 0 -2 0 -3 -2 2 -1 -3 -2 -1 -1-3 -2 -3 N-2 6 1 -3 1 -3 -3 0 -2 -3 -2 1-4 -2 -3 D-2 -2 1 6-3 2 -1 -1 -3 -4 -1 -3 -3 -1 0 -1-4 -3 -3 C 0 -3 -3 -3 9-3 -4 -3 -3 -1 -1 -3 -1 -2 -3 -1 -1-2 -2 -1 Q-1 1 0 -3 5 2 -2 0 -3 -2 1 0 -3 -1 0 -1-2 -1 -2 E-1 2 -4 2 5-2 0 -3 -3 1 -2 -3 -1 0 -1-3 -2 -2 G 0 -2 0 -1 -3 -2 -2 6-2 -4 -4 -2 -3 -3 -2 0 -2-2 -3 -3 H-2 1 -1 -3 0 -2 8-3 -3 -1 -2 -1 -2 -1 -2-2 2 -3 I-1 -3 -3 -3 -1 -3 -3 -4 -3 4 2 -3 1 0 -3 -2 -1-3 -1 3 L-1 -2 -3 -4 -1 -2 -3 -4 -3 2 4-2 2 0 -3 -2 -1-2 -1 1 K-1 2 0 -1 -3 1 1 -2 -1 -3 -2 5-1 -3 -1 0 -1-3 -2 -2 M-1 -1 -2 -3 -1 0 -2 -3 -2 1 2 -1 5 0 -2 -1 -1...
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This note was uploaded on 04/22/2008 for the course CSC 427 taught by Professor Ruzzo during the Winter '08 term at University of Washington.

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lec05 - 1 CSE 427 Computational Biology BLAST Alignment...

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