Transcript Protein Family Classification for Functional Genomics

Tutorial:
Bioinformatics Resources
BIO-TRAC 25 (Proteomics: Principles and Methods)
October 10, 2003
NIH, Bethesda, MD
Zhang-Zhi Hu, M.D.
Senior Bioinformatics Scientist,
Protein Information Resource
National Biomedical Research Foundation, GUMC
What is Bioinformatics?
Bioinformatics is the application of information technology
to the analysis, organization and distribution of biological
data in order to answer complex biological questions.
NIH Biomedical Information Science and Technology
Initiative (BISTI) Working Definition (2002) - Research,
development, or application of computational tools and
approaches for expanding the use of biological, medical,
behavioral or health data, including those to acquire, store,
organize, archive, analyze, or visualize such data.
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Bioinformatics Resources
The Molecular Biology Database Collection: An Online
Compilation of Relevant Database Resources
 2003 update: http://www3.oup.co.uk/nar/database/
 Nucleic Acids Research Database Issues (January Annually)
(2003 - http://nar.oupjournals.org/content/vol31/issue1/)
DBcat: A Catalog of > 500 Biological Databases
 http://www.infobiogen.fr/services/dbcat/
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Molecular Biology Database Collection
(http://nar.oupjournals.org/cgi/content/full/31/1/1#GKG120TB1)
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The Molecular Biology Database Collection:
2003 update (Baxevanis, A.D.)
-- An online resource of 386 key databases of 18 categories
Major sequence repositories
Comparative Genomics
Gene Expression
Gene Identification and
Structure
Genetic and Physical Maps
Genomic Databases
Intermolecular Interactions
Metabolic Pathways and
Cellular Regulation
Mutation Databases
Pathology
Protein Sequence Motifs
Proteome Resources
Retrieval Systems and
Database Structure
RNA Sequences
Structure
Transgenics
Varied Biomedical Content
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Overview
Protein Sequence Analysis
I. Sequence Similarity Search and Alignment
II. Family Classification Methods
III. Structure Prediction Methods
Molecular Biology Databases
IV. Protein Family Databases
V. Database of Protein Functions
VI. Databases of Protein Structures
Proteomic Resources
VII. 2D-gel databases
VIII. Proteomic analyses
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I. Sequence Similarity Search
Find a protein sequence: text search
Based on Pair-Wise Comparisons
 BLOSUM scoring matrix
 PAM scoring matrix
Dynamic Programming Algorithms
 Global Similarity: Needleman-Wunsch (GAP/BestFit)
 Local Similarity: Smith-Waterman (SSEARCH)
Heuristic Algorithms (Sequence Database Searching)
 FASTA: Based on K-Tuples (2-Amino Acid)
 BLAST: Triples of Conserved Amino Acids
 Gapped-BLAST: Allow Gaps in Segment Pairs (NREF)
 PHI-BLAST: Pattern-Hit Initiated Search (NCBI)
 PSI-BLAST: Iterative Search (NCBI)
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Sequence Search by Text or Unique ID
Entrez (http://www.ncbi.nlm.nih.gov/Entrez/)
(http://pir.georgetow
n.edu/pirwww/search
/textsearch.html)
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Pair-Wise
Comparisons
Scoring matrix
Global and local
Similarity: Dynamic
Programming
(Needleman-Wunsch,
Smith-Waterman)
(http://www.ebi.ac.uk/emboss/align/)
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FASTA Search
(http://pir.georgetown.edu/pirwww/search/fasta.html)
(http://www.ebi.
ac.uk/fasta33/)
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Gapped-BLAST Search
(http://pir.georgetown.edu/pirwww/search/pirnref.shtml)
(http://www.ncbi.nlm.nih.gov/BLAST/)
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A BLAST Result
PSI-BLAST Iterative Search
(http://www.ncbi.nlm.nih.gov/BLAST/)
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PSI-BLAST
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II. Family Classification Methods
Multiple Sequence Alignment and Phylogenetic Analysis
 ClustalW Multiple Sequence Alignment
 Alignment Editor & Phylogenetic Trees
Searches Based on Family Information
 PROSITE Pattern Search
 Motif and Profile Search
 Hidden Markov Model (HMMs)
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Multiple Sequence Alignment
ClustalW (http://pir.georgetown.edu/pirwww/search/multaln.html)
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Alignment Editor (Jalview)
(http://www.ebi.ac.uk/clustalw/)
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Alignment Editor (GeneDoc)
(http://www.psc.edu/biomed/genedoc/)
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Phylogenetic Analysis
Tree Programs: (http://evolution.
genetics.washington.edu/phylip.html)
Tree Searches: (http://pauling.
mbu.iisc.ernet.in/~pali/index.html)
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Phylogenetic Trees
(IGFBP Superfamily)
(Radial Tree)
(Phylogram)
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PROSITE Pattern Search
(http://pir.georgetown.edu/pirwww/search/patmatch.html)
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Profile Search
(http://bmerc-www.bu.edu/bioinformatics/profile_request.html)
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Hidden Markov Model Search
(http://www.sanger.ac.uk/Software/Pfam/search.shtml)
(http://smart.embl
-heidelberg.de)
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III. Structural Prediction Methods
Signal Peptide: SIGFIND, SignalP
Transmembrane Helix: TMHMM, TMAP
2D Prediction (a-helix, b-sheet, Coiled-coils): PHD, JPred
3D Modeling: Homology Modeling (Modeller, SWISSMODEL), Threading, Ab-initio Prediction
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Structure
Prediction:
A Guide
(http://speedy.emblheidelberg.de/gtsp/flow
chart2.html)
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Protein
Prediction
Server
(http://www.cbs.
dtu.dk/services/)
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Signal Peptide Prediction
(http://www.stepc.gr/~synaptic/sigfind.html)
(http://www.cbs.dtu.d
k/services/SignalP-2.0)
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Transmembrane Helix
(http://www.cbs.dtu.dk/services/TMHMM/)
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Protein Structure Prediction
(http://cmgm.stanford.edu/WWW/www_predict.html)
(http://restools.sdsc.edu/
biotools/biotools9.html)
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Structure Prediction Server
(http://cubic.bioc.columbia.edu/predictprotein/)
(http://www.compbio.dun
dee.ac.uk/WWW_Servers/
JPred/jpred.html)
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3D-Modelling
(http://www.salilab.org/modeller/modeller.html)
(http://www.expasy.
ch/swissmod/SWISS
-MODEL.html)
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IV. Protein Family Databases
Whole Proteins
 PIR: Superfamilies and Families
 COG (Clusters of Orthologous Groups) of Complete Genomes
 ProtoNet: Automated Hierarchical Classification of Proteins
Protein Domains
 Pfam: Alignments and HMM Models of Protein Domains
 SMART: Protein Domain Families
Protein Motifs
 PROSITE: Protein Patterns and Profiles
 BLOCKS: Protein Sequence Motifs and Alignments
 PRINTS: Protein Sequence Motifs and Signatures
Integrated Family Databases
 iProClass: Superfamilies/Families, Domains, Motifs, Rich Links
 InterPro: Integrate Pfam, PRINTS, PROSITES, ProDom, SMART
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Protein Clustering
(http://www.ncbi.nlm.nih.gov/COG/)
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Protein Domains
Pfam (http://www.sanger.ac.uk/Software/Pfam/)
SMART (http://
smart.embl-heid
elberg.de/smart/
show_motifs.pl)
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Protein Motifs
PROSITE is a database of protein families and domains. It
consists of biologically significant sites, patterns and profiles.
(http://www.expasy.ch/prosite/)
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Integrated Family Classification
InterPro: An integrated resource unifying PROSITE, PRINTS, ProDom, Pfam,
SMART, and TIGRFAMs, PIRSF. (http://www.ebi.ac.uk/interpro/search.html)
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V. Databases of Protein Functions
Metabolic Pathways, Enzymes, and Compounds
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Enzyme Classification: Classification and Nomenclature of Enzyme-Catalysed
Reactions (EC-IUBMB)
KEGG (Kyoto Encyclopedia of Genes and Genomes): Metabolic Pathways
LIGAND (at KEGG): Chemical Compounds, Reactions and Enzymes
EcoCyc: Encyclopedia of E. coli Genes and Metabolism
MetaCyc: Metabolic Encyclopedia (Metabolic Pathways)
WIT: Functional Curation and Metabolic Models
BRENDA: Enzyme Database
UM-BBD: Microbial Biocatalytic Reactions and Biodegradation Pathways
Klotho: Collection and Categorization of Biological Compounds
Cellular Regulation and Gene Networks
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EpoDB: Genes Expressed during Human Erythropoiesis
BIND: Descriptions of interactions, molecular complexes and pathways
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DIP: Catalogs experimentally determined interactions between proteins
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RegulonDB: Escherichia coli Pathways and Regulation

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KEGG Metabolic & Regulatory Pathways
KEGG is a suite of databases and associated software, integrating our current knowledge
on molecular interaction networks, the information of genes and proteins, and of chemical
compounds and reactions. (http://www.genome.ad.jp/kegg/kegg2.html)
(http://www.genome.ad.jp/dbgetbin/show_pathway?hsa00590+874)
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BioCyc (EcoCyc/MetaCyc Metabolic Pathways)
The BioCyc Knowledge Library is a collection of Pathway/Genome
Databases (http://biocyc.org/)
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Protein-Protein Interactions: DIP
(http://dip.doe-mbi.ucla.edu/)
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Protein-Protein Interaction: BIND
(http://www.bind.ca/)
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BioCarta Cellular Pathways
(http://www.biocarta.com/index.asp)
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VI. Databases of Protein Structures
Protein Structure and Classification
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PDB: Structure Determined by X-ray Crystallography and NMR
CATH: Hierarchical Classification of Protein Domain Structures
SCOP: Familial and Structural Protein Relationships
FSSP: Protein Fold Family Database
Protein Sequence-Structure Relationship
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PIR-NRL3D: Protein Sequence-Structure Database
PIR-RESID: Protein Structure/Post-Translational Modifications
HSSP: Families and Alignments of Structurally-Conserved Regions
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PDB Structure Data
(http://www.rcsb.org/pdb/)
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PDBsum:
Summary and Analysis
(http://www.biochem.ucl.
ac.uk/bsm/pdbsum)
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Protein Structural
Classification
CATH: Hierarchical
domain classification of
protein structures
(http://www.biochem.
ucl.ac.uk/bsm/cath_new/)
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Protein Structural Classification
The SCOP database aims to provide a detailed and comprehensive
description of the structural and evolutionary relationships between all
proteins whose structure is known, including all entries in the PDB.
(http://scop.mrc-lmb.
cam.ac.uk/scop/)
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VII. Proteomic Resources
GELBANK (http://gelbank.anl.gov): 2D-gel patterns from completed
genomes; SWISS-2DPAGE (http://www.expasy.org/ch2d/)
PEP: Predictions for Entire Proteomes: (http://cubic.bioc.columbia.edu/
pep/): Summarized analyses of protein sequences
Proteome BioKnowledge Library: (http://www.proteome.com): Detailed
information on human, mouse and rat proteomes
Proteome Analysis Database (http://www.ebi.ac.uk/proteome/): Online
application of InterPro and CluSTr for the functional classification of
proteins in whole genomes
Expression Profiling databases: GNF (http://expression.gnf.org/cgibin/index.cgi, human and mouse transcriptome), SMD (http://genomewww5.stanford.edu/MicroArray/SMD/, Stanford microarray data
analysis), EBI Microarray Informatics (http://www.ebi.ac.uk/microarray/
index.html , managing, storing and analyzing microarray data)
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2D-Gel Image Databases (1)
(http://gelbank.anl.gov/2dgels/index.asp)
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2D-Gel Image Databases (2)
(http://us.expasy.org/ch2d/2d-index.html)
(http://us.expasy.org/cgibin/nice2dpage.pl?P06493)
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VIII. Proteome Analysis
(http://www.ebi.ac.uk/proteome)
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Expression Profiling
Human and Mouse Transcriptome
(http://expression.gnf.org/cgi-bin/index.cgi)
(http://genome-www.
stanford.edu/serum/)
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Lab:
Visit selected websites and analyze some protein sequences of
your own choices.
- List of Bioinformatics Resources of this tutorial available:
http://pir.georgetown.edu/~huz/bioinfo_resource.html
Try some of the following sequences for analysis:
1) well characterized proteins: PIR:A26366(CYP17),
JS0747(Sp1)
2) less characterized proteins: PIR:A59000(MATER)
TrEMBL:Q9QY16(GRTH)
3) hypothetical protein: PIR:T12515, T00338 , T47130
SWISS-PROT:Q9BWT7
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