Linear Sequence Analysis. 3-D Structure Analysis
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1 Linear Sequence Analysis What can you learn from a (single) protein sequence? Calculate it s physical properties Molecular weight (MW), isoelectric point (pi), amino acid content, hydropathy (hydrophilic v. hydrophobic regions) Does not take into account post-translational modifications of protein, so are usually not 100% accurate Identify sequence motifs and families Signal sequences, transmembrane domains, coiled-coils, posttranslational modification sites, secondary structure (nonhomologous) Domains, functional motifs (homologous) 3-D Structure Analysis Visualization Domain structure, global fold, active sites, point mutations, SNPs, splice sites Evaluate structure quality Calculate physical properties Surface areas, distances, side-chain conformations, contact maps Structural alignment (ie similarity to other structures) Prediction Physical properties: binding affinity, pka s stability, specificity 3D structure (homology modeling, fold recognition, de novo) Advanced: protein design, docking of two proteins, active site modeling
2 Sequence Databases SwissProt (ExPASy) Highly curated, updated less frequently TrEMBL (ExPASy) Translated nucleotide sequences Automatic translation, fast but less info UniProt (EBI) Unified Protein Resource Combines SwissProt, TrEMBL, PIR sequences Sequence Analysis Sites For protein sequences and tools to analyze them, the two major centers are: ExPASy : Expert Protein Analysis System Many tools: Databases: SwissProt, TrEMBL NCBI : Entrez Protein and Domains PIR: Protein Information Resource (folded into UniProt consortium; no longer major resource site)
3 More Sequence Databases Non-redundant NR (NCBI), UniRef (PIR/EBI) Reference RefSeq (NCBI) re-annotated by NCBI Domains/Families Pfam protein families (Sanger Center + 4 mirror sites) SMART Simple Modular Architecture Research Tool CDD Conserved protein Domain Database (NCBI), combines Pfam, SMART, and COGs databases InterPro (based on UniProt, at EMBL-EBI) Many others Structure Databases Experimental: PDB: Protein Data Bank Families: SCOP, CATH, Dali database, Homstrad Models/Predictions ModBase SwissModel NOTE: All these databases are described in January Database issue of Nucleic Acids Research (plus other kinds of databases). Also, links to them
4 Protein Sequence Analysis Tools ExPASy Proteomics Tools Calculate physical properties Predict sequence motifs what ExPASy calls Topology : localization, TM domains Signal sequences, postranslational modifications Search pattern and profile collections PredictProtein and Meta-PP A meta-server providing access to many servers with one submission form Secondary Structure Prediction Three good methods: Psipred Sam-T02/T04/T06 PhD (PredictProtein) Compare a couple methods Use the three-state predictions
5 SEQUENCE <--> STRUCTURE <--> FUNCTION Evolutionary selection operates on function Structure is more closely linked to function than is sequence, so structure tends to be more conserved than sequence. Need to search farther in sequence space to find proteins with related structures and functions. Detecting Remote Similarities Remote similarities can more easily be detected by comparing protein sequences DNA sequences change faster than protein sequences (wobble position, redundant codons) 4 letter DNA code vs. 20 letter amino acid code means that matches by chance are more likely in DNA; The protein code has more information in it!
6 Detecting Homology NEAR Evolutionary Distance FAR DNA Sequence BLASTn BLASTp Protein Sequence PSIBLAST Protein Structure Fold Recognition SIMILARITY METHODS Similar Sequences Share Similar Structures Compare all pairs of proteins in the same family (pairs for which homology is very probable) Homologs do not necessarily share much sequence similarity. Proteins with >30% sequence identity almost always share the same fold More structurally similar All other immunoglobulins Sauder et al., (2000) Proteins 40:6
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