Basic Overview of Bioinformatics Tools and Biocomputing Applications I

1. Basic Overview of Bioinformatics Tools and Biocomputing Applications I Dr Tan Tin Wee Director Bioinformatics Centre

2. Software Tools • Data stored in retrievable forms in database systems • Data generated by machines, DNA / Protein sequencers, automated systems AutomatedMachines ResearchLabs Biological Data Analytical Tools Databases New Knowledge

3. Common Computational Analyses • Sequence Assembly • Simple sequence analysis • Translation and reverse Complement, ORF • Composition statistics (protein & DNA) • Molecular mass • Total charge and pI; local hydropathy • Simple determination of secondary structures • Restriction site analysis • Internal repeat analysis • Detection of active sites, functional residues, characteristic structures, substrates, and processing signals

4. Common Computational Analyses • Database sequence search • Multiple alignment • 2° and 3° Structure prediction; transmembrane helix detection • Structure modeling • Docking prediction and design • Hidden Markov model searches

5. Sequence Assembly • Fragmented data from DNA sequencers • Detection of Overlap • Merging of Contigs • Assembly into continuous sequence 3' 5'

6. Sequence Format Interconversion • DNA/Protein and other sequence data come in different formats. • Annotations • Different programs use different formats • Interconversion utility tools • eg. READSEQ, TOGCG, TOSTADEN, etc

7. 3. Calculate based on list of criteria ………….… …………….. …………….. ……………... Simple Sequence Analysis 1. Linear Sequence eg. DNA/ Protein 2. Open a Window - n = 1 n = variable n = sliding

8. Some Simple Sequence Analysis Applications • DNA complementary strand eg. COMPLEMENT & REVERSE • Open window size 1 • A--->T • C --->G • T ---> A • G ---> C • Slide to next Window of 1 • Proceed to end of sequence • Reverse order of complement • 5' ...ATCTCGATACTACTACG...3' • ||||||||||||||||| • 3' ...TAGAGCTATGATGATGC...5'

9. Some Simple Sequence Analysis Applications • DNA to Protein sequence translation, e.g. TRANSLATE • Open window of 3 bases • Look up Codon Usage table • Assign Amino acid residue • Slide window to next 3 bases • Proceed till stop codon detected. • Repeat whole procedure for six frames ATACTACTGAGATCTAGGCTAGTACTGCGTGCG Frame 1 Frame 2 Frame 3 Complement - Frames 4-6

10. Some Simple Sequence Analysis Applications • Detect Open Reading Frame e.g.ORF • Translate sequence, report long stretches of start and stop codons • Compositional analysis • eg. Calculate total A, T, G, C • eg. Calculate total molecular mass of protein, analysis percentages of amino acids • eg. Total Charge composition, pI

11. Some Simple Sequence Analysis Applications • Simple prediction of secondary structure of Protein sequence • decide a window size • compute for each window of amino acids statistical potential to form helix, beta sheet, turn, etc. Chou-Fasman, GOR etc algorithms • use a statistical potential chart • plot potentials in graphical or pictorial format

12. Some Simple Sequence Analysis Applications • Restriction Mapping eg. MAP, MAPPLOT,MAPSORT, PLASMIDMAP etc • Table of Restriction Enzymes and cut siteseg. EcoRI, BamHI AluIand their cut sites eg. GAATTC , AATT • Take a DNA sequence • Pattern match against the list of cut sites • For each match, assign Restriction enzyme • Calculate distance between cut sites • Display in table, graphical, or restriction map, etc gel Plasmidmap

13. Some Simple Sequence Analysis Applications • Protein sequence Motifs pattern matching eg. PROSITEMAP, MOTIFS, BLOCKS etc • Table/Database of Sequence Patterns/Motifs and their signature sequence eg. Arg-Gly-Asp (RGD) or consensus sequence (eg. PROSITE, BLOCKS db) • Take Protein sequence • Pattern match against the list of signature sites • For each match, assign potential function according to database • Display in table or graphically, or hyperlinked

14. Some Simple Sequence Analysis Applications • Peptide Cleavage Maps eg. PEPTIDESORT, PEPTIDE MAP • Table of Protease vs Cleavage sites eg. Trypsin, chymotrypsin, and Chemical cleavage sites cyanogen bromide • Pattern match with entire protein sequence • Calculate size of peptide fragments • Sort and Map, Plot as electrophoretic patterns on a log-linear simulated digest. • Compute Partial Digest patterns

15. Some Simple Sequence Analysis Applications • DOTPLOT- selfcomparison • Take a Window size • Compare against entire length of own sequence • Report matches above a threshold • Plot on Graph • Slide window, repeat till end of sequence • Detection of Internal repeats • Pairwise comparison - detection of homology Sequence A Sequence A

16. Some Simple Sequence Analysis Applications • RNA secondary structure analysis • Mfold, PlotFold, FoldRNA, Squiggles, Circles, Domes, Mountains, StemLoop • Folding of RNA into stems, loops • Calculation of energy - prediction of stability of structure • Display of structure and alternatives AUCG U G G A AUGC ---- -- -- UACG ...AUCGA AUCUC...

17. Database Searching • Text-based Database Searching -using a text string to match an annotation in a sequence database record, ie. Keyword search • Sequence-based Database Searching-using a biological sequence to match its whole or parts of its sequence to the sequences of every sequence database records

18. Text-Based Database Searching • Examples: Entrez, SRS, DBGET, AceDB- common integrated database systems • Search Concepts • Boolean Search - AND, OR, NOT • Broadening Search • Narrowing the Search • Proximity searching, soundex • Wild Card, Stemming eg. Thala* for thalasemia, thalassemia, thalassemic • Use standard string search algorithms and boolean operations, vocabulary matches

19. Text-based Database Searching • Example: To find the human homolog of the Drosophila per gene • Procedure • Web to Entrez • All Fields : enter "human" "per" • Hits returned, irrelevant - broaden search • "human" "period" - more hits • check every one, find the human RIGUI gene • Hit and miss, clever guess work, free form or controlled vocabulary (MeSH terms)?Use Boolean searches?

20. Sequence-based Database Searching • Homology Search • Global or Local Sequence Alignment • Needleman-Wunch Algorithm • Smith-Waterman Algorithm • Lipman - Pearson FASTA • Altschul's BLAST • Take a sequence, pairwise comparison with each sequence in the database

21. Sequence-based Database Searching • Basic Assumptions: • Sequences of homologous Genes/Protein diverge over time even though structure and/or function change little • Significant sequence similarity inferred as potential structural /functional similarity or common evolutionary origin • Based on well-characterised protein, infer the function of an unknown sequence at gene or protein sequence level.

22. Sequence-based Database Searching • Global Alignmentforces complete alignment of the pairwise comparison of the two input sequences • Local Alignmentlooks for local stretches of similarity and tries to align the most similar segments • Algorithms used may be similar, but output different, statistics needed to assess results

23. Sequence-based Database Searching • Alignment Scoring • Substitution score and substitution matrixPAM, BLOSUM • affine gap costs/gap penalty and gap scores • Optimal alignments, dynamic programmingNeedleman-Wunsch algorithm,Smith-Waterman algorithm (SSEARCH) • Additional heuristics - FASTA, BLAST