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

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1 CSE 427 Computational Biology BLAST Alignment score significance PCR and DNA sequencing
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2 The Plan BLAST Scoring Another Bio Interlude: PCR & Sequencing
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A Protein Structure: (Dihydrofolate Reductase)
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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 – …
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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
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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 σ (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
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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 σ (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
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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 )
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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 0 -3 -2 0 R -1 5 0 -2 -3 1 0 -2 0 -3 -2 2 -1 -3 -2 -1 -1 -3 -2 -3 N -2 0 6 1 -3 0 0 0 1 -3 -3 0 -2 -3 -2 1 0 -4 -2 -3 D -2 -2 1 6 -3 0 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 0 -3 5 2 -2 0 -3 -2 1 0 -3 -1 0 -1 -2 -1 -2 E -1 0 0 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 0 1 -1 -3 0 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 -1 -1 1 F -2 -3 -3 -3 -2 -3 -3 -3 -1 0 0 -3 0 6 -4 -2 -2 1 3 -1 P -1 -2 -2 -1 -3 -1 -1 -2 -2 -3 -3 -1 -2 -4 7 -1 -1 -4 -3 -2 S 1 -1 1 0 -1 0 0 0 -1 -2 -2 0 -1 -2 -1 4 1 -3 -2 -2 T 0 -1 0 -1 -1 -1 -1 -2 -2 -1 -1 -1 -1 -2 -1 1 5 -2 -2 0 W -3 -3 -4 -4 -2 -2 -3 -2 -2 -3 -2 -3 -1 1 -4 -3 -2 11 2 -3 Y -2 -2 -2 -3 -2 -1 -2 -3 2 -1 -1 -2 -1 3 -3 -2 -2 2 7 -1 V 0 -3 -3 -3 -1 -2 -2 -3 -3 3 1 -2 1 -1 -2 -2 0 -3 -1 4
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10 BLAST Refinements
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