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Lesson 3 Database Similarity Search

Lesson 3 Database Similarity Search. Sequence Similarity search is a key to discover new functions. Basic assumption. Similar sequences. Similar function. WHY?. Have the required properties to undertake the function Come from the same origin. new sequence. ?. Similar function. ≈.

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Lesson 3 Database Similarity Search

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  1. Lesson 3 Database Similarity Search

  2. Sequence Similarity search is a key to discover new functions Basic assumption Similar sequences Similar function WHY? • Have the required properties to undertake the function • Come from the same origin

  3. new sequence ? Similar function ≈ Discover Function of a new sequence Sequence Database

  4. Searching Databases for similar sequences Due to the huge number and size of the databases using exact algorithm to compare a sequence (query) to all sequences in the databases is not feasible. Solution: Use a heuristic (approximate) algorithm

  5. Heuristic strategy Perform efficient search strategies Preprocess database into new data structure to enable fast accession

  6. BLAST Basic Local Alignment Search Tool • General idea - a good alignment contains subsequences of high identity (local alignment): ACGCCCGGGAGCGC CTGGGCGTATAGCCC • First, identify (most efficiently) short almost exact matches . • Next, extended to longer regions of similarity. • Finally, optimize the alignment an exact algorithm. Altschulet al 1990

  7. Similar to pairwise sequence alignments BLAST can be used for DNA/RNA (nucleotide) sequences or for proteins sequence (amino acids) • BLASTN(Nucleotide) • BLASTP(Protein)

  8. DNA/RNA vs protein alphabet DNA(4) RNA(4) Protein (20) A T G C A U G C ACDEFGHIKLMNPQRSTVWY A T=A G…. A T=A G…. A G>>A W…. WHY is it different?

  9. The 20 Amino Acids

  10. The 20 Amino Acids A G W

  11. Scoring system for amino acids mismatches

  12. BLAST(Protein Sequence Example) 1. Identify (most efficiently) short almost exact matches between the query sequence and the database. Query sequence…FSGTWYA… Words of length 3: FSG, SGT, GTW, TWY, WYA

  13. BLAST Preprocessing of the database Seq 1 FSGTWYA FSG, SGT, GTW, TWY, WAY Seq 2 FDRTSYV FDR, DRT, RTS, TSY, SYV Seq 3 SWRTYVA SWR, WRT,RTY, TYV, YVA ……. FSG SGT GTW TWY WYA YSG TGT ATW SWY WFA FTG.. SVT. GSW. TWF.. WYS…. Seq 1 BAG OF WORDS (BOW) Seq 102 Seq 3546

  14. BLAST Query sequence …FSGTWYA… Words of length 3: FSG, SGT, GTW, TWY, WYA… DATABASE FSG SGT GTW TWY WYA YSG TGT ATW SWY WFA FTG SVT GSW TWF WYS…. SEQ N INVIEIAFDGTWTCATTNAMHEWASNINETEEN

  15. BLAST 2. Extend word pairs as much as possible (No Gaps) until the local alignment score meets or exceeds a threshold or cutoffscore (t)  HSP High-scoring Segment Pairs (HSPs) Q: FIRSTLINIHFSGTWYAAMESIRPATRICKREAD D: INVIEIAFDGTWTCATTNAMHEWASNINETEEN 3. Finally, optimize the alignment using an exact algorithm. Q= query sequence, D= sequence in database

  16. Treating Gaps in BLAST >Human DNA CATGCGACTGACcgacgtcgatcgatacgactagctagcATCGATCATA >Human mRNA CATGCGACTGACATCGATCATA BLAST by definition is a local alignment tool

  17. Sometimes we want to include gaps in alignments! • Standard solution: affine gap model wx = g + r(x-1) wx : total gap penalty; g: gap open penalty; r: gap extend penalty ;x: gap length • Once-off cost for opening a gap • Lower cost for extending the gap • Changes required to algorithm

  18. Running BLAST to predict a function of a new protein >Arrestin protein (C. elegance) MFIANNCMPQFRWEDMPTTQINIVLAEPRCMAGEFFNAKVLLDSSDPDTVVHSFCAEIKG IGRTGWVNIHTDKIFETEKTYIDTQVQLCDSGTCLPVGKHQFPVQIRIPLNCPSSYESQF GSIRYQMKVELRASTDQASCSEVFPLVILTRSFFDDVPLNAMSPIDFKDEVDFTCCTLPF GCVSLNMSLTRTAFRIGESIEAVVTINNRTRKGLKEVALQLIMKTQFEARSRYEHVNEKK LAEQLIEMVPLGAVKSRCRMEFEKCLLRIPDAAPPTQNYNRGAGESSIIAIHYVLKLTAL PGIECEIPLIVTSCGYMDPHKQAAFQHHLNRSKAKVSKTEQQQRKTRNIVEENPYFR

  19. Running BLAST to predict a function of a new protein

  20. Running BLAST to predict a function of a new protein

  21. How to interpret a BLAST score: • The score is a measure of the similarity of the query to the sequence shown. How do we know if the score is significant? -Statistical significance -Biological significance

  22. How to interpret a BLAST search: For each blast score we can calculate an expectation value (E-value) The expectation value E-value is the number of alignments with scores greater than or equal to score S that are expected to occur by chance in a database search. page 105

  23. BLAST- E value: Increases linearly with length of query sequence Decreases exponentially with score of alignment Increases linearly with length of database m = length of query ; n= length of database ; s= score • K ,λ: statistical parameters dependent upon scoring system and background residue frequencies

  24. What is a Good E-value (Thumb rule) • E values of less than 0.00001 show that sequences are almost always related. • Greater E values, can represent functional relationships as well. • Sometimes a real (biological) match has an E value > 1 • Sometimes a similar E value occurs for a short exact match and long less exact match

  25. How to interpret a BLAST search: • The score is a measure of the similarity of the query to the sequence shown. How do we know if the score is significant? -Statistical significance -Biological significance

  26. (How) can we decide if two sequences really have the same function? Homolog = come from a common origin => have the same function

  27. Homologous proteins = come from a common origin => have the same function Last Universal Common Ancestor

  28. Homology Rule of thumb:-Proteins are homologous if 25%-35% identical -DNA sequences are homologous if 70% identical Can we always go by the rules?

  29. Alignment between the worm and human arrestin VERY SIGNIFICANT , NOT HIGH IDENTITY

  30. Assessing whether proteins are functional homologous High levels of a protein RBP4 (Retinol binding protein 4) and PAEP (pregnancy associated protein) were found to be correlated with pre-eclampsia High levels of a protein RBP4 (Retinol binding protein 4) were found to be correlated with childhood obesity RBP4= carrier of vitamin A in the blood PAEP= Pregnancy associated protein

  31. Are they functionally homologous??? PAEP RBP4

  32. Assessing whether proteins are functional homologous RBP4 (retinol binding) and PAEP (pregnancy protein) E value= 0.49; identity=24% Are they functionally homologous???

  33. The lipocalins protein family (each dot is a protein) PAEP RBP4 retinol-binding protein odorant-binding protein apolipoprotein D

  34. Are they functionally homologous??? PAEP RBP4 They belong to the same protein family= have a common ancestor Their functions have probably diverse

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