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Sequence Based Analysis Tutorial NIH Proteomics Workshop Cecilia Arighi, Ph.D. Protein Information Resource at Georgetown University Medical Center Retrieval, Sequence Search & Classification Methods Retrieve protein info by text / UID Sequence Similarity Search BLAST, FASTA, Dynamic Programming Family Classification Patterns, Profiles, Hidden Markov Models, Sequence Alignments, Neural Networks Integrated Search and Classification System 2 Sequence Similarity Search (I) Based on Pair-Wise Comparisons Dynamic Programming Algorithms Global Similarity: Needleman-Wunch Local Similarity: Smith-Waterman Heuristic Algorithms FASTA: Based on K-Tuples (2-Amino Acid) BLAST: Triples of Conserved Amino Acids Gapped-BLAST: Allow Gaps in Segment Pairs PHI-BLAST: Pattern-Hit Initiated Search PSI-BLAST: Position-Specific Iterated Search 3 Sequence Similarity Search (II) Similarity Search Parameters Scoring Matrices – Based on Conserved Amino Acid Substitution Dayhoff Mutation Matrix, e.g., PAM250 (~20% Identity) Henikoff Matrix from Ungapped Alignments, e.g., BLOSUM 62 Gap Penalty Search Time Comparisons Smith-Waterman: 10 Min FASTA: 2 Min BLAST: 20 Sec 4 Feature Representation Features of Amino Acids: Physicochemical Properties, Context (Local & Global) Features, Evolutionary Features Alternative Amino Acids: Classification of Amino Acids To Capture Different Features of Amino Acid Residues Alphabet AA Identity Exchange Group Charge/Polarity Hydrophobicity Structural 2D Propensity Size 20 6 4 3 3 3 Features Sequence Identity EvolutionSubstitution Charge and Polarity Hydrophobicity Surface Exposure Secondary Structure Membership A,C,D,E,F,G,H,I,K,L,M,N,P,Q,R,S,T,V,W,Y {HRK}{DENQ}{C}{STPAG}{MILV}{FYW} {HRK} {DE} {CTSGNQY} {PMLIVFW} {DENQRK} {CSTPGHY} {AMILVFW} {DENQHRK} {CSTPAGWY} {MILVF} {AEQHKMLR} {CTIVFYW} {SGPDN} 5 Substitution Matrix Likelihood of One Amino Acid Mutated into Another Over Evolutionary Time Negative Score: Unlikely to Happen (e.g., Gly/Trp, -7) Positive Score: Conservative Substitution (e.g., Lys/Arg, +3) High Score for Identical Matches: Rare Amino Acids (e.g., Trp, Cys) 6 Secondary Structure Features a Helix Patterns of Hydrophobic Residue Conservation Showing I, I+3, I+4, I+7 Pattern Are Highly Indicative of an a Helix (Amphipathic) b Strands That Are Half Buried in the Protein Core Will Tend to Have Hydrophobic Residues at Positions I, I+2, I+4, I+6 7 BLAST BLAST (Basic Local Alignment Search Tool) Extremely fast Robust Most frequently used It finds very short segment pairs (“seeds”) between the query and the database sequence These seeds are then extended in both directions until the maximum possible score for extensions of this particular seed is reached 8 BLAST Search From BLAST Search Interface Table-Format Result with BLAST Output and SSEARCH (SmithWaterman) Pair-Wise Alignment Links to iProClass and UniProtKB reports Link to NCBI taxonomy Link to PIRSF report Click to see SSearch alignment Click 9 to see alignment Blast Result & Pairwise Alignment BLAST Aligment 10 Classification What is classification? Why do we need protein classification? Different levels of classification Basis for functional protein classification How to classify a protein of unknown function? 11 Classification Databases Protein motif Protein domain 3-D structure Whole-protein C - x(2,4) - C - x(3) - [LIVMFYWC] - x(8) - H - x(3,5) - H The 2 C's and the 2 H's are zinc ligands Group proteins according to the presence of a common Group proteins according to Group proteins according to domain common domain common 3D structure architecture and length 12 Family Classification Methods Based on Other Classification Information Multiple Sequence Alignment (ClustalW) ProSite Pattern Search Profile Search Hidden Markov Models (HMMs) Domain (Pfam); Whole protein (PIRSF) Neural Networks 13 How do you build a tree? Pick sequences to align Align them Verify the alignment Keep the parts that are aligned correctly Build and evaluate a phylogenetic tree Integrated Analysis 14 Multiple Sequence Alignment: CLUSTALW Pairwise alignment: Calculate distance matrix Mean number of differences per residue Unrooted Neighbor-Joining Tree Branch length drawn to scale Rooted NJ Tree (guide tree) Root place at a position where the means of the branch lengths on either side of the root are equal Progressive Alignment guided by the tree Alignment starts from the tips of the tree towards the root Thompson et al., NAR 22, 4675 (1994). 15 PIR Multiple Alignment and Tree From Text/Sequence Search Result or CLUSTAL W Alignment Interface 16 17 PIR Pattern Search Signature Patterns for Functional Motifs From Text/Sequence Search Result or Pattern Search Interface Alignment of a region involved in catalytic activity A P-[IV]-[WY]-x(3)-H-[MR]-V-x(3,4)-Q-x(1,2)-D-x(4,5)-G-A-N Create Pattern and search in database: P-[IV]-[WY]-x(3)-H-[MR]-V-x(3,4)-Q-x(1,2)-D-x(4,5)-G-A-N Test sequence against PROSITE database B O05689 18 Pattern Search Result (I) A. One Query Pattern Against UniProtKB or UniRef100 DBs Display the query pattern Indicate pattern sequence region(s) Links to iProClass and UniProtKB reports Link to NCBI taxonomy Link to PIRSF report 19 Pattern Search Result (II) B. One Query Sequence Against PROSITE Pattern Database 20 Profile Method Profile: A Table of Scores to Express Family Consensus Derived from Multiple Sequence Alignments Num of Rows = Num of Aligned Positions Each row contains a score for the alignment with each possible residue. Profile Searching Summation of Scores for Each Amino Acid Residue along Query Sequence Higher Match Values at Conserved Positions 21 Prosite PS50157 profile for Zinc finger C2H2 22 1 PIRSF scan Search One Query Protein Against all the Full-length and Domain HMM models for the fully curated PIRSFs by HMMER The matched regions and statistics will be displayed. Shows PIRSF that the query belongs to Statistical data for all domains Statistical data per domain Alignment with consensus sequence 23 Creation and Curation of PIRSFs 24 Integrated Bioinformatics System for Function and Pathway Discovery Data Integration Associative Analysis User Input Input (Local Data, Search (Gene/Protein Criteria, Report Format) Expression Data) Output (Analysis Results, Biological Interpretation) Integrated Bioinformatics System Data Mining Tools Sequence Analysis Pipeline (Retrieval, Visualization, Analysis, Correlation) (Family Classification & Feature Identification) Graphical User Interface (Browsing, Querying, Navigation) Data Warehouse (Gene, Protein, Family, Function, Structure, Pathway, Interaction) 25 Query Sequence UniProt Family Classification & Functional Analysis BLAST Search HMM Domain Search Analytical Pipeline Top-Matched Superfamilies/Domains HMM Motif Search Pattern Search SignalP/TMHMM Predicated Superfamilies/Domains/Motifs/Sites/SignalPeptides/TMHs SSEARCH CLUSTALW Superfamily/Domain/Motif Alignments Family Relationships & Functional Features 26 Integrated Bioinformatics System Gene Expression Data Proteomic Data Integrated Protein Knowledge System Clustering Global Bioinformatics Analysis of 1000’s of Genes and Proteins Gene/Peptide-Protein Mapping Expression Pattern Protein List Functional Analysis Pathway Discovery, Target Identification (Sequence Analysis & Information Retrieval) Comprehensive Protein Information Matrix Visualization & Statistical Analysis Pathway Discovery (Browsing, Sorting, Visualization & Statistical Analysis) Clustered Matrix Clustered Graph Pathway Map Process Hierarchy 27 Lab Section 28 Rat eye lens phosphoproteomics in normal and cataract Kamei et al., Biol. Pharm. Bull., 2005. Normal pI (+) More phosphorylated spots in cataract sample. Digestion and MS from Spot 16 gave these peptides: Mw (-) Cataract MDVTIQHPWFKR ALGPFYPSR CSLSADGMLTFSG YRLPSNVDQSALS We want to identify the protein(s) that contain these peptides Use Peptide Search 29 Peptide Search Restrict search to an organism 30 Peptide Search & Results Species restricted search Sorting arrows Links to iProClass and UniProtKB reports Link to NCBI taxonomy Search in UniProtKB, 23 proteins Link to PIRSF report Matching peptide highlighted in the sequence 31 Batch Retrieval Results (I) • Retrieve multiple proteins in from iProClass using a specific identifier or a combination of them • Provides a means to easily retrieve and analyze proteins when the identifiers come from different databases Retrieve more sequences 32 Blast Similarity Search What proteins are related to rat CRYAA? • Perform sequence similarity search >P24623 http://pir.georgetown.edu/pirwww/search/blast.shtml 33 Pairwise Alignment 35 PIR Text Search (http://pir.georgetown.edu/search/textsearch.shtml) UniProtKBDatabase and unique UniParc sequences Let’s search for human crystallins PIR protein family classification database 36 Let’s look for crystallins which have 3D structure Refine your search or start over Display PDB ID 37 Domain Display allows to compare simultaneously Pfam domains present in multiple proteins Share same domain architecture Let’s perform a multiple alignment on the sequences containing PF00030 38 Multiple Alignment 39 Interactive Phylogenetic Tree and Alignment Beta B1 and gamma crystallins share the same domains, SCOP fold and share significant sequence similarity suggesting that they are 40 related Pattern Search (I) Select P07320 and perform a pattern search Search for proteins containing this pattern (PS00225) in rat 41 Pattern Search Result Beta and gamma Crystallins have multiple copies of this pattern 42 PIRSF provides a single platform where all the previous analysis has been done by curators Pfam domains assigned with high confidence Validation tag Represents extent of manual curation Link to PIRSF report 43 Taxonomic Distribution Alpha-crystallin is exclusively found in metazoans Domain Architecture Multiple Alignment 44 PIRSF scan 45 PIRSF report (I): a single platform to study proteins Subfamily level 46 PIRSF report (II) Cross-links to other databases http://www.geneontology.org/ 47 alpha-Crystallin and Related Proteins Alpha crystallin beta chain HSPs Alpha crystallin alpha chain 48