7.91 Lecture #1 Introduction to Bioinformatics

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1 7.91 Lecture #1 Introduction to Bioinformatics Focus on Kinases Michael Yaffe & Pairwise Sequence Comparisons ARDFSHGLLENKLLGCDSMRWE.::..:::..:::: :::. GRDYKMALLEQWILGCD-MRWD Reading: This lecture: Mount pp.1-7, 29-35, 45-48, Next lecture: Mount pp. 8-9, 65-89, , +more The Protein Data Bank (PDB - is the single worldwide repository for the processing and distribution of 3-D biological macromolecular structure data. Berman, H. M., J. Westbrook, Z. Feng, G. Gilliland, T. N. Bhat, H. Weissig, I. N. Shindyalov, and P. E. Bourne. The Protein Data Bank. Nucleic Acids Research 28 (2): (PDB Advisory Notice on using materials available in the archive:

2 Outline Review of biological fundamentals Genetics example Biological databases/ncbi resources Simplified sequence analysis where to start Simple sequence comparisons Definitions of related sequences Concepts and types of alignments the good, the bad, and the ugly Dot matrix alignments Computational efficiency Recursion and dynamic programming Substitution matrices: PAM, BLOSUM, Gonnet

3 Outline (cont) Gaps Applied dynamic programming: global alignments: Needleman-Wunsch Applied dynamic programming: local alignments Smith-Waterman Basic statistics of sequence alignments

4 Review of biological fundamentals Genetic material gene as a concept DNA as hereditary material DNA RNA Protein Critical cell functions

5 DNA structure A G C T U Bases

6 DNA structure A T G C Base pairing

7 DNA structure Nucleoside Nucleotide

8 DNA structure 5 3

9 DNA structure 5 3

10 DNA structure

11 RNA structure

12 Transcription OH 3 5 DNA OH RNA OH 5 3

13 Protein structure

14 Nonpolar, Hydrophobic R-groups H O H O H O H O H O H 3 N + C C H H O - 3 N + C C H CH O - 3 N + C C H H O - 3 N + 3 N + C C C C 3 CH CH O - H CH O C CH3 CH3 CH 3 CH 3 CH2 Glycine (Gly, G) Alanine (Ala, A) Valine (Val, V) CH 3 Leucine (Leu, L) Isoleucine (IIe, I) C C H O H O H O H O H 3 N + C C H 3 N + H 3 N + C C H 2 N + C C O CH - O - 2 CH2 CH 2 CH2 NH O - H 2 C CH 2 CH 2 O - S CH 3 Phenylalanine (Phe, F) Proline (Pro, P) Methionine (Met, M) Tryptophan (Trp, W) Polar, Hydrophillic R-groups H O H 3 N + C C O - CH2 OH Serine (Ser, S) H H O H O H O H O O H H H 3 N + C C H O - 3 N + C C H O - 3 N + C C 3 N + 3 N + C C C C O O - O CH2 CH - CH - CH2 CH2 2 OH CH C CH 3 SH 2 OH NH 2 O C NH 2 O Threonine (Thr, T) Cysteine (Cys, C) Tyrosine (Tyr, Y) Asparagine (Asn, N) Glutamine (Gln, Q) Electrically charged Acidic H O H 3 N + H C C O O - H C C CH2 3 N + H 3 N + O - CH2 C - O O CH 2 C - O O Glutamic acid (Glu, E) Aspartic acid (Asp, D) Basic H O H O C C H 3 N + C C CH2 O - CH2 O - CH 2 CH 2 CH 2 CH 2 CH 2 NH NH + 3 C NH + 2 Lysine (Lys, K) NH 2 Arginine (Arg, R) Aspartic acid (Asp, D) Arginine (Arg, R) O H C H 3 N + C O - CH2 NH NH + Histidine (His, H)

15 Codon Table (5')...pNpNpN...(3') in mrna Base at 5' End of Codon U Middle Base of Codon C A G Base at 3' End of Codon U phe (UUU) ser tyr cys U phe ser tyr cys C leu ser termination termination A leu ser termination trp G C leu leu leu pro pro pro his his gln arg arg arg U C A leu pro gln arg G A ile thr asn ser U ile thr asn ser C ile thr lys arg A met (and initiation) thr lys arg G G val val ala ala asp asp gly gly U C val ala glu gly A val ala glu gly G

16 DNA structure 3 5 Sense strand Anti-Sense strand 5 Convention: Sense strand Read 5 Æ 3 3 Reverse Complement

17 Genetics experiment: Isolate a yeat mutant that has increased chromosome number phenotype Can rescue the phenotype with a piece of DNA corresponds to a site of mutation in the yeasts DNA genotype CGTTTTTCCTGTAAAGCGCTTAATTTGTTTACCATTCTATAAAAACCTTGAGCTAAGGCCAACTGATGCA ATTGCTCAAGTGAATGCATAAACAAAGCAAGATCATTCTTAGCGCAAAAAAAACTGGGATTTTGAAATAC AACAAAAGAAAGAAGTAAAAAGGGAATGCAACGCAATAGTTTAGTAAATATCAAACTAAACGCTAATTCG CCATCGAAAAAGACCACAACAAGACCAAATACGTCCAGGATCAATAAACCATGGAGAATATCCCATTCGC CGCAGCAAAGAAACCCGAATTCAAAAATACCTTCACCTGTAAGAGAAAAATTGAACAGATTACCTGTAAA CAATAAGAAGTTTTTGGATATGGAAAGCTCCAAAATTCCATCACCTATAAGGAAAGCGACTTCTTCCAAA ATGATACACGAAAATAAGAAGCTACCTAAATTTAAATCCCTATCACTCGATGACTTTGAACTGGGGAAGA AATTAGGAAAGGGTAAATTCGGTAAAGTTTATTGCGTTCGGCACAGGAGTACAGGATATATTTGCGCACT GAAAGTAATGGAGAAGGAAGAAATAATAAAGTATAATTTACAGAAACAATTCAGAAGGGAGGTAGAAATA CAAACATCGCTAAATCATCCGAATCTAACTAAATCATACGGCTATTTTCATGATGAAAAAAGAGTGTACC TGCTAATGGAATACTTAGTCAATGGGGAAATGTATAAACTATTGAGGTTACACGGACCCTTCAACGATAT TTTAGCATCAGATTATATTTATCAAATTGCCAATGCCCTAGATTATATGCATAAAAAGAATATTATTCAT AGAGATATTAAACCTGAAAATATACTAATAGGGTTCAATAATGTCATTAAGTTAACGGACTTCGGATGGA GTATAATAAATCCGCCAGAAAATAGAAGGAAAACTGTCTGTGGGACAATTGACTACCTTTCTCCAGAAAT GGTGGAGTCAAGGGAATATGATCACACTATAGATGCATGGGCTCTTGGCGTCCTGGCGTTTGAACTACTG ACCGGTGCCCCTCCGTTCGAAGAAGAAATGAAAGATACTACATATAAAAGGATAGCAGCACTGGATATCA AAATGCCCAGTAACATTTCTCAGGATGCGCAAGATTTAATACTTAAACTACTAAAATACGACCCCAAAGA TAGAATGCGCCTTGGAGACGTAAAAATGCATCCTTGGATACTAAGAAACAAGCCCTTTTGGGAAAATAAG CGGTTATAGAATTAAAGTATGACAGAATCGTTTGAAGGGCACTATTAATCACTCCCGCACATATCACATA ATACTAAGTATCCATTTCTAATATTTCATTACTCTTTTCGGCATCGTATATTGCGATATTTGATTAAATT TTCTTGTTCATTTTTTCCTCTTTTCTTTCGCCTTTGTCGAAAGAAAAGAGGAAAACAAGCTGAAAATTGC TATGCATTAAAGTAGCAGATTTACTTTGTTGAGTTGGTTCTGATCAATAATAAGAGTAATGAAAGAAAGC AAAAAAATGGCTAAAGATAATTTAACTAATTTGCTCTCTCAATTGAACATTCAATTGTCTCAA

18 The National Center for Biotechnology Information Created as a part of NLM in 1988 Establish public databases Perform research in computational biology Develop software tools for sequence analysis Disseminate biomedical information

19 Molecular Databases Primary Databases Original submissions by experimentalists Database staff organize but don t add additional information Example: GenBank Derivative Databases Human curated compilation and correction of data Example: SWISS-PROT, NCBI RefSeq mrna Computationally Derived Example: UniGene Combinations Example: NCBI Genome Assembly

20 What is GenBank? NCBI s Primary Sequence Database Nucleotide only sequence database Archival in nature GenBank Data Direct submissions individual records (BankIt, Sequin) Batch submissions via (EST, GSS, STS) ftp accounts sequencing centers Data shared three collaborating databases GenBank DNA Database of Japan (DDBJ). European Molecular Biology Laboratory Database (EMBL) at EBI.

21 STSs BACs X Chromosome 163 Mb Relationships of chromosomes to genome sequencing markers. The X chromosome is about 163 Mb in length. In this diagram, there are 16 overlapping BAC clones that span the entire length. In reality, 1,48 BACs were needed to span the X chromosome. Arrows (top) mark STSs scattered throughout the chromosome and on overlapping BACs.

22 GenBank: NCBI s Primary Sequence Database Release 133 December 23 19,88,11 Records 28,57,99,166 Nucleotides 11, + Species full release every two months incremental and cumulative updates daily available only through internet ftp://ftp.ncbi.nih.gov/genbank/ 17.7 Gigabytes of data

23 GenBank Divisions Bulk Sequence Divisions PAT EST STS GSS HTG HTC CON Patent Expressed Sequence Tags Sequence Tagged Sites Genome Survey Sequences High Throughput Genome High Throughput cdna Contig Traditional Divisions BCT INV MAM PHG PLN PRI ROD SYN UNA VRL VRT

24 The International Sequence Database Collaboration NIH Submissions Updates NCBI Entrez GenBank EMBL Submissions Updates NIG CIB getentry DDBJ Submissions Updates SRS EBI EMBL

25 Web Access Text Entrez Sequence BLAST Structure VAST

26 Genetics experiment: Isolate a yeat mutant that has increased chromosome number phenotype Can rescue the phenotype with a piece of DNA corresponds to a site of mutation in the yeasts DNA genotype CGTTTTTCCTGTAAAGCGCTTAATTTGTTTACCATTCTATAAAAACCTTGAGCTAAGGCCAACTGATGCA ATTGCTCAAGTGAATGCATAAACAAAGCAAGATCATTCTTAGCGCAAAAAAAACTGGGATTTTGAAATAC AACAAAAGAAAGAAGTAAAAAGGGAATGCAACGCAATAGTTTAGTAAATATCAAACTAAACGCTAATTCG CCATCGAAAAAGACCACAACAAGACCAAATACGTCCAGGATCAATAAACCATGGAGAATATCCCATTCGC CGCAGCAAAGAAACCCGAATTCAAAAATACCTTCACCTGTAAGAGAAAAATTGAACAGATTACCTGTAAA CAATAAGAAGTTTTTGGATATGGAAAGCTCCAAAATTCCATCACCTATAAGGAAAGCGACTTCTTCCAAA ATGATACACGAAAATAAGAAGCTACCTAAATTTAAATCCCTATCACTCGATGACTTTGAACTGGGGAAGA AATTAGGAAAGGGTAAATTCGGTAAAGTTTATTGCGTTCGGCACAGGAGTACAGGATATATTTGCGCACT GAAAGTAATGGAGAAGGAAGAAATAATAAAGTATAATTTACAGAAACAATTCAGAAGGGAGGTAGAAATA CAAACATCGCTAAATCATCCGAATCTAACTAAATCATACGGCTATTTTCATGATGAAAAAAGAGTGTACC TGCTAATGGAATACTTAGTCAATGGGGAAATGTATAAACTATTGAGGTTACACGGACCCTTCAACGATAT TTTAGCATCAGATTATATTTATCAAATTGCCAATGCCCTAGATTATATGCATAAAAAGAATATTATTCAT AGAGATATTAAACCTGAAAATATACTAATAGGGTTCAATAATGTCATTAAGTTAACGGACTTCGGATGGA GTATAATAAATCCGCCAGAAAATAGAAGGAAAACTGTCTGTGGGACAATTGACTACCTTTCTCCAGAAAT GGTGGAGTCAAGGGAATATGATCACACTATAGATGCATGGGCTCTTGGCGTCCTGGCGTTTGAACTACTG ACCGGTGCCCCTCCGTTCGAAGAAGAAATGAAAGATACTACATATAAAAGGATAGCAGCACTGGATATCA AAATGCCCAGTAACATTTCTCAGGATGCGCAAGATTTAATACTTAAACTACTAAAATACGACCCCAAAGA TAGAATGCGCCTTGGAGACGTAAAAATGCATCCTTGGATACTAAGAAACAAGCCCTTTTGGGAAAATAAG CGGTTATAGAATTAAAGTATGACAGAATCGTTTGAAGGGCACTATTAATCACTCCCGCACATATCACATA ATACTAAGTATCCATTTCTAATATTTCATTACTCTTTTCGGCATCGTATATTGCGATATTTGATTAAATT TTCTTGTTCATTTTTTCCTCTTTTCTTTCGCCTTTGTCGAAAGAAAAGAGGAAAACAAGCTGAAAATTGC TATGCATTAAAGTAGCAGATTTACTTTGTTGAGTTGGTTCTGATCAATAATAAGAGTAATGAAAGAAAGC AAAAAAATGGCTAAAGATAATTTAACTAATTTGCTCTCTCAATTGAACATTCAATTGTCTCAA

32 Using Entrez An integrated database search and retrieval system

33 Entrez: Database Integration Word weight PubMed abstracts Phylogeny Taxonomy Genomes 3-D Structur e VAST BLAST Nucleotide sequences Protein sequences BLAST

34 The (ever) Expanding Entrez System UniGene PubMed Nucleotide Protein Journals Structure CDD Genome SNP Entrez PopSet 3D Domains UniSTS Taxonomy OMIM ProbeSet Books

35 Entrez Databases PubMed Biomedical literature Books Online textbooks Nucleotide GenBank, EMBL, DDBJ, RefSeq, PDB Protein [GenBank, EMBL, DDBJ], RefSeq, SWISS-PROT, PIR, PRF, PDB Genome Complete genomes Taxonomy Organisms in NCBI sequence databases Structure MMDB: experimental 3D structures Domains CDD: conserved protein domains 3D Domains Compact 3D protein domains in MMDB OMIM Online Mendelian Inheritance in Man SNP Single nucleotide polymorphisms UniSTS Sequence Tagged Site markers ProbeSet Gene expression and microarray datasets PopSet Population study datasets UniGene Gene-based expressed sequence clusters

36 A Traditional GenBank Record Definition =Title ACCESSION VERSION Version Number U7163 U GI:46243 Accession Number GI Number NCBI s Taxonomy

FASTA Format FASTA Definition Line >gi 46243 gb U7163.

37 FASTA Format FASTA Definition Line >gi gb U SCU7163 > gi number Locus Name Database Identifiers gb GenBank emb EMBL dbj DDBJ sp SWISS-PROT pdb Protein Databank pir PIR prf PRF ref RefSeq Accession number

38 Abstract Syntax Notation: ASN.1 GenPept GenBank ASN.1 FASTA Protein FASTA Nucleotide

39 /************************************************************************ * * asn2ff.c * convert an ASN.1 entry to flat file format, using the FFPrintArray. * *********************************** Toolbox Sources ***************************************/ #include <accentr.h> #include "asn2ff.h" #include "asn2ffp.h" #include "ffprint.h" #include <subutil.h> ftp> open ftp.ncbi.nih.gov #include <objall.h> #include <objcode.h>. #include <lsqfetch.h> #include <explore.h> #ifdef ENABLE_ID1 #include <accid1.h> #endif FILE *fpl; NCBI Toolbox. ftp> cd toolbox ftp> cd ncbi_tools ftp://ftp.ncbi.nlm.gov/toolbox/ncbi_tools Args myargs[] = { {"Filename for asn.1 input","stdin",null,null,true,'a',arg_file_in,.,,null}, {"Input is a Seq-entry","F", NULL,NULL,TRUE,'e',ARG_BOOLEAN,.,,NULL}, {"Input asnfile in binary mode","f",null,null,true,'b',arg_boolean,.,,null}, {"Output Filename","stdout", NULL,NULL,TRUE,'o',ARG_FILE_OUT,.,,NULL}, {"Show Sequence?","T", NULL,NULL,TRUE,'h',ARG_BOOLEAN,.,,NULL},

40 /protein_id="aaa2496.1" /db_xref="gi:46244" GenPept Protein IDS

53 Why align sequences? Functional predictions based on identifying homologues. Assumes: conservation of sequence conservation of function BUT: Function carried out at level of proteins, i.e. 3-D structure Sequence conservation carried out at level of DNA 1-D sequence

54 Implicit Assumption of Evolution in Models of Sequence Homology Assume: Sequence conservation Structure conservation Note that the converse is NOT necessarily true! Structure conservation X Sequence conservation

55 Definitions Homologue: a relatively non-specific term (meaningless?) that conveys the idea that two sequences are somehow related Orthologue: Ortho = (greek) straight.implies direct descent, 1 ancestor Vav human Vav bovine Vav avian Vav elegans -or- human Vav avian Vav bovine Vav dinosaur Vav Ye olde Vav

56 Definitions Paralogue: Para = (greek) along side of.implies some type of gene duplication event Vav1 human Vav2human Vav3human -or-

57 Complex problem Chicken Vav Vav1 human Vav2human Vav3human Orthologue or Paralogue? Need to know evolutionary relationships Can try and get these from alignments as well

58 Alignments- Good Bad and Ugly HgbA-human GSAQVKGHGKKVADALTNAVAHVDDMPNALSALSDLHAHKL :+ +::+:::::+ :+++++::+: ::+::+ :: GNPKVKAHGKKVLGAFSDGLAHLDNLKGTFATLSELHCDKL HgbB-human

59 Alignments- Good Bad and Ugly HgbA-human SPURIOUS ALIGNMENT GSAQVKGHGKKVADALTNAVAHVDDMPNALSALSD----LHAHKL ::+ ++: + ++:+: ++ :+ :+ : +:+ : ++::+ GSGYLVGDSLTFVDLL--VAQHTADLLAANAALLDEFPQFKAHQE Nematode glutathione S-transferase HgbA-human GSAQVKGHGKKVADALTNAVAHV---D--DMPNALSALSDLHAHKL :+ ::+ ++ +:++ + +: :+ +:+ : NNPELQAHAGKVFKLVYEAAIQLQVTGVVVTDATLKNLGSVHVSKG Leghemoglobin, yellow lupin

60 Alignments Types: Local Global Ungapped Gapped (2 types- linear, affine) Methods: Dot matrix Dynamic Programming Word, k-tup

61 Simplest alignment representation Dot plot Model: Need a metric of similarity between amino acid pairs Simplest metric unitary matrix, identity matrix A A 1 C D E F G H C 1 D 1 E 1 F 1 G 1 H 1 I 1 K I K 1

62 Example self alignment G G 1 F D S F K F D 1 S 1 1 F 1 1 K 1 R 1 L 1 E 1 1 F 1 S 1 R L E F S E V

63 Example self alignment..with sliding window G G 1 F D S F K F D 1 S 1 1 F 1 1 K 1 R 1 L 1 E 1 1 F 1 S 1 R L E F S E V

64 Example self alignment G G 1 F D S F K F 1 1 D 1 S 1 F 1 K 1 R 1 L 1 E 1 F 1 S 1 R L E F S E V

65 Simple alignments Self alignment Dot Matrix DNA symmetric

66 Now align two different sequences * Consider other similarity matrices besides identity. Chemical similarity binary decision Amino acid conservation in aligned protein families min. similarity score (+/- window) Average of multiple scoring systems

67 Dot Matrix Alignments Sequence#1 Sequence#1 1 n 1 m Note NOT symmetric A Local Alignment

68 Dot Matrix Alignments Sequence#1 Sequence#1 1 1 n Insertion Insertion m A Global Alignment

69 General Rules for Dot Matrices Advantage let s your eyes/brain do the work VERY EFFICIENT!!!! DNA comparisons long windows and high stringencies (11/7, 15/11) Proteins short windows and stringencies (1/1) EXCEPT in looking for domains then longer windows and smaller stringencies (15/5). Note we can use these types of self-aligned matrices for more than just sequence comparisons i.e. distance between side Cα atoms in 3d-structures etc.maybe later in the course!

70 Computational Efficiency Measure efficiency in cpu run time and memory O() = big-oh notation Both scale as size of the problem, measured in number of units, n, in the problem, i.e. run time is f(n). Analyse the asymptotic worst-case running time. Sometimes just do the experiment and measure it. If problem scales as square of the number of units in the problem O(n 2 ) (=order n-squared)

71 Examples O(n k ) is polynomial time as long as K<3..tractable Consider our un-gapped dot matrix Global alignment: 1 m 1 n essentially an O(mn) problem

72 O.K. Examples O(n) better than O(n log(n)), better than O(n 2 ), better than O(n 3 ) Terrible Examples O(k n ) = exponential time.horrible!!!! NP problems- no known polynomial time Solutions = non-deterministic polynomial Problems.

11 questions for a total of 120 points

Your Name: BYS 201, Final Exam, May 3, 2010 11 questions for a total of 120 points 1. 25 points Take a close look at these tables of amino acids. Some of them are hydrophilic, some hydrophobic, some positive