introduction to bioinformatics - shandong university · 7 introduction to bioinformatics english...

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Introduction to BioinformaticsEnglish Courses for Graduate Students

Dr. rer. nat. Jing Gong

Cancer Research center

Medicine School of Shandong University

2011.9.21


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Chapter 2

Databases


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Why Do “WE” Need Databases?

What’s that?

gcattacttgatctaatca

ataggatctaatctttactagaacgccttgatctaatca

ttgcaa

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Why Do We Need Databases?

gcattacttgatctaatca

ataggatctaatctttactagaacgccttgatctaatca

ttgcaa

This is the entire HIV1 genome containing total 9752 nucleotides with only 9 genes.

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Why Do We Need Databases?Human Genome : 3 Gbp = 3,000,000,000 bp

5000bp/page 600pages/book 1000 x 3cm/book600,000 pages 1000 books = 30m bookshelf

Over 1000 species :

1000 x 30m-bookshelves

200 x 5 layers/bookshelf

医学院图书馆 450,000 册

26.6m

= 2 x

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Why Do We Need Databases?10cm

14.6

cm

x 1000

All sequenced genomes:

26.6m

1TB

= 1000GB

= 1,000,000MB

= 1,000,000,000KB

= 1.000,000,000,000B

collect access

manage

update

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Biological Databases - A biological database is a collection of data that is organized so that its contents can easily be accessed, managed, and updated.

History of Biological Databases

insulin = MALWMRLLPLLALLALWGPDPAAAFVNQHLCGSHLVEALYLVCGERGFFYTPKTRREAEDLQVGQVELGGGPGAGSLQPLALEGSLQKRGIVEQCCTSICSLYQLENYCN

Frederick Sanger (1918-)nobel prize 1958

The first biological database was created within a short period after the Insulin protein sequence was made available in 1956.

Biological databases make it possible to answer today’s biological questions by enabling us to analyze sequences that may have been determined as many as 30 years ago, when the whole technology emerged.

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History of Biological DatabasesAround mid 1960’s, the first nucleic acid sequence of Yeast tRNA with 77 bases was found out by Holley. During this period, three dimensional structure of proteins were studiedand the well known Protein Data Bank was developed as the first protein structure database with only 10 entries in 1972. This has now grown into a large database with over 75,000 entries.

Robert W. Holley (1922-1993)

nobel prize 1968

John CowderyKendrew (1917-1997)

nobel prize 1962

Max Ferdinand Perutz (1914-2002)

nobel prize 1962

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History of Biological DatabasesAt beginning, the initial databases of protein sequences were maintained at the individual laboratories. The development of a consolidated formal database known as Swiss-Prot protein sequence database was initiated in 1986. Now it has about 530,000 protein sequences from more than 12,000 organisms.

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History of Biological DatabasesThe Los Alamos National Laboratory (USA) established the Los Alamos Sequence Database in 1979, which culminated in 1982 with the creation of the public GenBank. Later, the nucleotide sequence database of European Molecular Biology Laboratory (EMBL) and the DNA Data Bank of Japan (DDBJ) were created. Today these three databases represent the largest and fundamental biological databases and they together called International Nucleotide Sequence Database Collaboration (INSDC).

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Protein Structure DB


Classification of Biological DatabasesProtein Database

Primary Protein Database

INSDCUniProt

Protein Sequence DB

Secondary Protein Database

Nucleotide DatabasePrimary Nucleotide Database

Secondary Nucleotide Database

Specific Database

>2000

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INSDCUniProt

Protein Sequence DB




Specific Database

>2000

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Nucleotide DatabasesPrimary Nucleotide Database

is produced and maintained by the National Center for Biotechnology Information ( NCBI ). The NCBI is a part of the National Institutes of Health ( ) in the United States ( ).

GenBank receive sequences produced in laboratories throughout the world. In about30 years since its establishment, Its data were accessed and cited by millions of researchers around the world. GenBankcontinues to grow at an exponential rate, doubling every 18 months. Release producedin 2008, contained over 99 billion nucleotidebases in more than 98 million sequences.

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The European Molecular Biology Laboratory (EMBL) is supported by 20 European ( ) member states and one associate member state, Australia ( ). It consists of five facilities: the main Laboratory in Heidelberg ( ), outstations in Hinxton ( , the European Bioinformatics Institute (EBI)), Hamburg ( ), Grenoble ( ), and Monterotondo ( ).

The EMBL Nucleotide Sequence Database constitutes Europe'sprimary nucleotide sequence resource. Main sources for DNA

and RNA sequences are direct submissions from individual researchers, genome sequencing projects and patent applications. The current release contains 212 millions sequence entries comprising 326 billions nucleotides.


Nucleotide DatabasesPrimary Nucleotide Database

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The DNA Data Bank of Japan (DDBJ) is a biological database that collects DNA sequences. It is located at the National Institute of Genetics ( ) in the Shizuoka (静冈) of Japan.


Nucleotide Databases

DDBJ began data bank activities in 1986 at NIG and remains the only nucleotide sequence data bank in Asia. Although DDBJ mainly receives its data from Japanese researchers, it can accept data from contributors from any other country. The current release contains 138 millions sequence entries and 128 billions bases.

Primary Nucleotide Database

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The International Nucleotide Sequence Database Collaboration (INSDC) consists of a joint effort to collect and disseminate databases containing DNA and RNA sequences

New and updated data on nucleotide sequences contributed by research teams to each of the three databases are synchronized on a daily basis through continuous interaction between the staff at each the collaborating organizations.

Primary Nucleotide Database

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Nucleotide DatabasesReading into Genes and GenomesAll living organisms can be sorted into one of two groups depending on the fundamental structure of their cells. These two groups are the prokaryotes (organisms lacking a true nucleus) and the eukaryotes (organisms having a true nucleus).

Nucleotide sequences are universal, but the structure of genes they encode is markedly different between prokaryotes and eukaryotes.

archaea prokaryotic cell eukaryotic cell

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Nucleotide DatabasesReading into Genes and GenomesBesides prokaryotes and eukaryotes, there is the third class of living organisms, archaea. They are bacteria-like organisms living in extreme conditions. In bioinformatic context, prokaryotes and archaea are very much the same.

archaea prokaryotic cell eukaryotic cell

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• They are microscopic organisms.• Their genomes is single, circular DNA molecule.• Their gene density is approximately one gene per 1,000 base pairs.• Their genome contains few useless

part (70% is coding for proteins).• Their genes do not overlap.• Their genes are transcribed to mRNA

right after a control region, called promoter.• These mRNA are collinear with the genome sequence.• Protein sequences are derived by translating the longest open reading frame

(ORF) spanning the gene-transcript sequence.


Nucleotide DatabasesReading into Genes and GenomesProkaryotes (archaea) have the following properties in common:

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= x 6 reading frames

Reading Frame - a reading frame is a way of breaking a DNA sequence into three letter codons which can be translated in amino acids.

x 3 x 3

ATG Met (M)

TAA TAG TGA

ORF (Open Reading Frame) - a DNA sequence that contains a start codon but does not contain a stop codon in a given reading frame.

ORF


Nucleotide DatabasesNucleotide DatabasesReading into Genes and Genomes

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Nucleotide DatabasesReading into Genes and GenomesProkaryotes (archaea) have the following properties in common:

• They are microscopic organisms.• Their genomes is single, circular DNA molecule.• Their gene density is approximately one gene per 1,000 base pairs.• Their genome contains few useless

part (70% is coding for proteins).• Their genes do not overlap.• Their genes are transcribed to mRNA

right after a control region, called promoter.• These mRNA are collinear with the genome sequence..• Protein sequences are derived by translating the longest open reading frame

spanning the gene-transcript sequence.

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Nucleotide DatabasesReading into Genes and Genomes

According to these common properties, database entries describing a coding prokaryotic sequence should include three important features:

• The coordinates of some promoter elements• The coordinates of the RBS• The coordinates of the ORF boundaries.

Not all genes encode proteins. For some of them, the function is directly carried out by the transcribed RNA molecule, including tRNA, rRNA and a few others.

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Nucleotide DatabasesReading into Genes and GenomesEukaryotes have the following properties in common:

• Their genome consists of multiple linear pieces of DNA called chromosomes.• Their genome size is much bigger than in prokaryotes.• Their gene density is much lower than that for prokaryotes.• Their genome is not efficient, containing many useless parts .• Genes on opposite DNA strands might overlap, although that’s a relatively rare

occurrence. • Their genes are transcribed right after a control region called a promoter, but

sequence elements located far away can have a strong influence on this process. • Gene sequences are not collinear with the final messenger RNA (mRNA) and

protein sequences. Only small bits (the exons) are retained in the mature mRNA that encodes the final product.

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Nucleotide DatabasesReading into Genes and GenomesA few points between prokaryotes and eukaryotes:

yesnoHas mRNA introns?noyesIs gene collinear?5%70%cording region content

one gene / 1,000 bp0.5-91 million bpProkaryotes

10–670,000 million bpgenome sizeOne gene / 100,000 bp (human)gene density

Eukaryotes

Pro.

Eu.

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Nucleotide DatabasesMaking sense of GenBank entry of a prokaryotic gene: E. coli dUTPase

X017141

2 3

http://www.ncbi.nlm.nih.gov/X01714

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1

2

3

X01714http://www.ncbi.nlm.nih.gov/

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LOCUS gives us the locus name, the size of the nucleotide sequence in base pairs, the nature of the molecule, its topology and the last updated date.



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DEFINITION provides a short definition of the gene that corresponds to the entry sequence. Here, it’s the E. coli dut gene. This gene can encode the enzyme dUTPase. The full name of dUTPase is deoxyuridine 5’- triphosphate nucleotidohydrolase(脱氧尿苷焦磷酸酶).


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ACCESSION lists the accession number - a unique identifier within and across various databases. Here, the accession number is X01714.


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VERSION fills you in on synonymous or past ID numbers.


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KEYWORDS introduces a list of terms that broadly characterize the entry. You can use these terms as keywords for certain database searches.


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SOURCE reveals the common name of the relevant organism to which the sequence belongs.


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ORGANISM gives a more complete identification of the organism, complete with its technical taxonomic classification.


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REFERENCE introduces a section where the credits for the sequence determination are given (different parts of the sequences can be credited to different authors). The REFERENCE section contains multiple parts: AUTHORS, TITLE, JOURNAL, and PUBMED.


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COMMENT contains free-formatted text, such as acknowledgments or information that doesn’t fit in the previous sections.


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FEATURES describes the gene regions and the associated biological properties that have been identified in the nucleotide sequence. This entire section is under the control of the FEATURES keyword, such as source, promoter, etc.


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source indicates the origin of specific regions of the sequence. This is useful when you want to distinguish cloning vectors from host sequences.In X01714, the whole sequence comes from E. coli genomic DNA.


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promoter shows the coordinates of a promoter element. In X01714, a -35 region is indicated from position 286 to 291 in the nucleotide sequence.


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misc feature (miscellaneous feature) indicates the putative location of the transcription start (mRNA synthesis). For X01714, this is from positions 322 to 324.


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RBS (Ribosome Binding Site) indicates the location of the last upstream element. For X01714, this is at position 330 to 333.


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CDS (CoDing Segment) introduces a complex section that describes the gene’s open reading frame (ORF).


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The first line indicates the coordinates of the ORF from its initial ATG to the last nucleotide of the first stop codon TAA.


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Each of the following lines gives the name of a protein product, indicates the reading frame to use(here, 343 is the first base of the first codon), the genetic code to apply, and a number of IDs for the protein sequence.


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/translation introduces the conceptual amino-acid sequence of the coding segment. This sequence is a computer translation that uses the coordinates,reading frame, and genetic code indicated in the preceding lines.


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misc feature contains lines that point out putative stem-loop structures and repeats. These are potential regulatory elements of the dUTPase gene.


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This entry exhibits an extra putative gene, indicatedby an additional RBS element and a second CDS section. GenBank entries containing more than one gene are frequent.


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The last section is the nucleotide sequence section.It starts with the ORIGIN keyword and finishes with the end-of-entry line introduced by two slash marks (//). Each line of nucleotide sequence starts withthe position number of the first nucleotide in that line. Each line contains 60 nucleotides.


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1. Way

2. Way


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U902231

2 3

Making sense of GenBank entry of an eukaryotic mRNA: human dUTPase

U90223http://www.ncbi.nlm.nih.gov/

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Nucleotide DatabasesMaking sense of GenBank entry of an eukaryotic mRNA: human dUTPase


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A common problem in sequence databases: annotations may be incomplete.

A word to the wise: You should never expect GenBank (or any sequence database) annotations to be up-to-date.



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In the FEATURES section, the CDS indicates a coding region (63-821) sequence that corresponds to the mitochondrial form of human dUTPase, following the conceptual amino-acid translation of the ORF.



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The sig peptide keyword indicates the location of a mitochondrial targeting sequence, and the mat peptide keyword provides the exact boundaries of the mature peptide.



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Nucleotide DatabasesMaking sense of GenBank entry of an eukaryotic genomic entry

AF018430

1

2 3AF018430

http://www.ncbi.nlm.nih.gov/

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AF018430

This specifies that the entry encompasses exon 3 of the gene.


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AF018430

SEGMENT indicates that this current GenBank entry is the second segment of a super entry made of four. You need all four entries to reconstruct the complete mRNA sequence used as a template for producing the protein.


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AF018430

The /map in the source section indicatesthat the sequence belongs to chromosome 15, and was more precisely mapped on the long arm (q) of this chromosome, within the q21.1 cytogenetic band.


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AF018430

The gene keyword introduces complex-looking formulas. Their purpose is to describe precisely the reconstruction of the various mRNAs spread over several separate entries.

The < at the beginning of the formula indicates that the gene might actually start before the indicated position,

the > at the end of the formula indicates that the gene might actually continue beyond the indicated position.


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AF018430http://www.ncbi.nlm.nih.gov/

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AF018430http://www.ncbi.nlm.nih.gov/

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AF018430

The exon keyword indicates the position of the sole exon present in this sequence.


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DUT [gene] human [organism]

1

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Using a Gene-Centric Databasehttp://www.ncbi.nlm.nih.gov/DUT [gene] human [organism]

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Nucleotide DatabasesUsing a Gene-Centric Database

The top of the entry provides a general description of what this gene is all about and what function its products are known to perform, as well as a large variety of links to other databases or NCBI files.

http://www.ncbi.nlm.nih.gov/DUT [gene] human [organism]http://www.ncbi.nlm.nih.gov/DUT [gene] human [organism]http://www.ncbi.nlm.nih.gov/

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A schematic view of theHuman DUT gene structure

DUT [gene] human [organism]http://www.ncbi.nlm.nih.gov/

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Other sections provide information on potential interactions with other gene products, protein functions, a list of all corresponding sequence entries in GenBank and a large variety of links to other databases or NCBI files, etc.

DUT [gene] human [organism]http://www.ncbi.nlm.nih.gov/

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Nucleotide DatabasesWorking with complete viral genomes: HIV-1

http://www.ncbi.nlm.nih.gov/HIV-1


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69




70




71




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Global summary of the HIV-1 genome

This clickable picture indicates the identity and respective positions of all the genes.


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Nucleotide DatabasesWorking with complete viral genomes: HIV-1A live map - allows you to zoom

in/out on any genome region, down to the nucleotide sequence level.

Viruses commonly have the same nucleotide sequence involved in the making of two different amino-acid sequences


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The Protein List page - you canretrieve the DNA and protein sequences in different formats, GenBank format, or FASTA format.


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Nucleotide Databases http://www.tigr.org/

Working with complete bacterial genomes at TIGR

The Institute for Genome Research (TIGR) is home to a team of scientists who pioneered the field of bacterial genomics.

TIGR is founded in 1992 by Craig Venter and is now a part of the J. Craig Venter Institute.

In 1995, the scientists of TIGR produced the two first complete bacterial genomes. Since then, they have contributed to more than 700 complete bacterial genomes, with more on the way.

TIGR offers a site that is quite complementary to the NCBI resource because it keeps track of all ongoing bacterial genome sequencing projects (not only of the completed ones).

TIGR home page: http://www.tigr.org/ http://www.jcvi.org/

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78




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Nucleotide DatabasesWorking with complete bacterial genomes at TIGR

http://cmr.tigr.org/

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81




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Nucleotide Databases http://img.jgi.doe.gov/Microbes from the environment at DoE

The U.S. Department of Energy (DoE) is also a main player in microbial genomics. Its Joint Genome Institute specializes in the study of organisms that are either

(a) important for preserving our environment, or

(b) offering some new perspective in solving the incoming worldwide energy crisis (such as cheap ways of producing hydrogen).

DoE home page: http://img.jgi.doe.gov/

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Nucleotide DatabasesMicrobes from the environment at DoE

http://img.jgi.doe.gov/

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1

2

3


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Nucleotide Databases http://img.jgi.doe.gov/

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88




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A live display of the microbe gene content in the range 1 to 500,000.


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Nucleotide DatabasesExploring the Human Genome

Human Genome – 3 billion nucleotides spread over 23 chromosomes.

If you want to make sense of human data, you must have clear ideas on thecurrent state of the data:

• The complete nucleotide sequence of the human genome is now at hand.

• This sequence was obtained in raw format; the next challenge is the annotation of the raw data, creating a detailed and accurate FEATURES table of the human genome.

• Throughout the world, new information is generated daily on human gene properties and functions, using a wide array of techniques.

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Nucleotide Databases http://www.ensembl.org/Exploring the Human Genome : the Internet home page of Ensembl

Ensembl is a joint project between the European Bioinformatics Institute (EBI) and the Sanger Institute.

Together they’ve developed an integrated database and software system to produce and maintain automatic annotations for the genomes of animals with a special attention to our closest relatives: the vertebrates.

Ensembl home page: http://www.ensembl.org/

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Nucleotide DatabasesExploring the Human Genome : the Internet home page of Ensembl

http://www.ensembl.org/

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A schematic image of the various human chromosomes


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the Chromosome 15 data subset


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GenBank Entry U90223 for human dUTPase gene


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Human DUT ID card - everything you ever wanted to know about this gene can be found.


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Establishing the G+C content of your sequence

The GC content of a molecule of DNA is the percentage of the total nitrogenous base in the DNA that is either guanine or cytosine. GC content is a very interesting property of DNA sequences because it is correlated to repeats and gene deserts. DNA with high GC-content is more stable than DNA with low GC-content. In PCR experiments, the GC-content of primers are used to predict their annealing temperature to the template DNA. A higher GC-content level indicates a higher melting temperature.

ORIGIN cagagaaaat caaaaagcag gccacgcaggaccccgatat cgtcgcaggc gttgccgcacttgccgccga aacaaataat gtggaagaatacgcccggca aaaacgtatc cgtaaaaaccttgatctgat ctgcgcgaac gatgtttccc//

http://www.genomatix.deTools for Nucleotide Sequences

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Establishing the G+C content of your sequence : Genomatix

Tools for Nucleotide Sequenceshttp://www.genomatix.de

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http://1.51.212.243/X01714.fasta

Tools for Nucleotide Sequences

http://1.51.212.243/X01714.fastahttp://1.51.212.243/X01714.fasta

http://www.genomatix.de

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105




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4 different nucleotides16 different dinucleotides64 different trinucleotides (3-tuples)256 different 4-tuples1024 different 5-tuples4096 different 6-tuples (hexamer)

Identifying hexamers (6-tuples) with unexpected high frequencies in a set of sequences (such as promoter regions) is often the starting point for discovering regulatory sequence motifs.

The EMBOSS server (EBI), offers an online version of the program wordcount that allows you to compute the word frequency in your DNA sequence for any size. http://emboss.bioinformatics.nl


Counting long words in DNA sequences : Wordcount

Tools for Nucleotide Sequenceshttp://emboss.bioinformatics.nl

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Counting long words in DNA sequences : : Wordcount


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[email protected]


http://1.51.212.243/X01714.fasta

http://emboss.bioinformatics.nl

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Protein-coding genes have vastly different structures in microbes and multi cellular organisms.

In microbes, each protein is encoded by a simple DNA segment, from start to end, called an open reading frame (ORF).

In animal and plant genes, proteins are encoded in several pieces called exons, separated by non-coding DNA segments called introns.


Finding Protein-Coding Regions

prokaryotes (archaea) eukaryotes


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Finding Protein-Coding Regions : ORF Finder at NCBIhttp://www.ncbi.nlm.nih.gov


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Finding Protein-Coding Regions : ORF Finder at NCBI

Tools for Nucleotide Sequenceshttp://www.ncbi.nlm.nih.gov

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AE008569

1 5000

1

2

3AE008569 : Rickettsia conoriigenome (bacterium)


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1

2


117




or

http://www.ncbi.nlm.nih.gov

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This program is also good for finding protein-coding regions for higher organisms, if your sequence is a cDNA.

cDNA – don’t include intronsand they have a simple, microbe-like ORF structure.


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Finding Protein-Coding Regions : GeneMarkhttp://exon.gatech.edu

The simplest ORF finding programs can probably correctly identify 85% percent of the protein-coding regions you may be interested in. However, in some cases, you may need to : • Finding very short proteins• Resolving uncertain cases where overlapping ORFs are predicted in

different reading frames, on the direct and reverse strand, for instance• Pinpoint the exact Start codon (the most distal ATG isn’t always the

correct one)

GeneMark - searches for coding regions using a criterion that’s a bit more sophisticated than “it has to be an uninterrupted reading frame longer than a certain length.” This program also takes into account the statistical properties of your sequence and associates some sort of a probabilistic quality index to each candidate’s ORFs.


120


Finding Protein-Coding Regions : GeneMark

Tools for Nucleotide Sequenceshttp://exon.gatech.edu

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Finding Protein-Coding Regions : GeneMark

http://1.51.212.243/AE008569.seq


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PDF


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Finding Protein-Coding Regions : MZEF

If you’re looking at a human genomic sequence, your first question should be: Do I have a protein-coding exon somewhere in there?

In eukaryotic DNA sequence, exons are separated by non-coding introns.According to what molecular biologists have worked out, a protein codingexon is an ORF flanked by two specific signals known as splice sites. Several programs exist that can recognizethese exons.

MZEF - developed by Dr. Michael Zhang at Cold Spring Harbor Lboratory on beautiful Long Island (USA).

http://rulai.cshl.eduTools for Nucleotide Sequences

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Tools for Nucleotide Sequenceshttp://rulai.cshl.edu

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[email protected]

http://1.51.212.243/AF018429.fastahttp://1.51.212.243/AF018429.fasta


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Beijing Gene Finder (BGF) - http://tlife.fudan.edu.cn/bgf (eukaryotes)GeneFinder - http://cgap.nci.nih.gov/Genes/GeneFinderGENEID - http://genome.crg.es/software/geneidGenlang - http://arete.ibb.waw.pl/PL/html/gene_lang.htmlGENSCAN - http://genes.mit.edu/GENSCAN.html (eukaryotes)Glimmer - http://www.cbcb.umd.edu/software/glimmer (prokarytoes, archaea)GlimmerM - http://www.cbcb.umd.edu/software/glimmerm (eukaryotes)GrailEXP - http://compbio.ornl.gov/grailexp……

Finding Protein-Coding Regions


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Information Page

131





INSDCUniProt

Protein Sequence DB




Specific Database

>2000

132


Protein DatabasesPrimary Protein Sequence Databases

UniProt Knowledgebase (UniProtKB) is a central protein database of ExPASy maintained by Swiss Institute of Bioinformatics (SIB) and European Bioinformatics Institute (EBI), consisting of two sections:

UniProtKB/Swiss-Prot - a reviewed, manually annotated, non-redundant protein sequence database. It combines informationextracted from scientific literature and biocurator- evaluatedcomputational analysis.

UniProtKB/TrEMBL - contains high-quality computationally analyzed records, which are enriched with automatic annotation. It was introduced in response to increased dataflow resulting from genome projects, as the time- and labour-consuming manual annotation process of UniProtKB/Swiss-Prot could not be broadened to include all available protein sequences.

133


Protein DatabasesPrimary Protein Sequence Databases

The Protein Information Resource (PIR), is an integrated public bioinformatics resource to support genomic and proteomic research, and scientific studies.

In 2002, PIR along with its international partners, EBI and SIB, were awarded a grant from NIH to create UniProt, a single worldwide database of protein sequence and function, by unifying the PIR-PSD, Swiss-Prot, and TrEMBL databases.

134


Protein DatabasesReading a UniprotKB/Swiss-Prot Entry

Proteins are much simpler objects than genes.

• Proteins correspond to relatively small sequences (350 amino acids long, on the average).

• Unlike genes, proteins have clear beginnings and clear ends.

• Proteins are defined on a single strand.

• Whatever modifications occur between the ORF sequence and the mature protein, the amino acids they contain remain in the same order.

Use the human epidermal growth factor receptor (EGFR) as an example.

UniprotKB/Swiss-Prot home page (ExPASy) : http://expasy.org/

http://expasy.org/

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http://expasy.org/

1

2 3

P00533

human epidermal growth factor receptor (EGFR)

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P00533http://expasy.org/

137



P00533

General InformationEntry Name, Accession Number, Secondary Accession Number, Last Modification Date.

http://expasy.org/

138



P00533

The E.C. number (2.7.10.1) encodes the biochemical reaction that this protein performs. E.C. stands for Enzyme Nomenclature Committee. It can provides you a complete understanding of this protein enzymatic function.

http://expasy.org/

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140




141



P00533

This section provides a simple list of terms relevant to your current protein. Clicking any one of these keywords brings out a list of all Swiss-Prot entries that contain the same term. With the increasing size of the database, it seems that this type of query is not useful anymore.

http://expasy.org/

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http://expasy.org/P00533

Other proteins it interacts with

143




Description of the existence of related protein sequence(s) produced by alternative splicing of the same gene, alternative promoter usage, ribosomal frame-shifting or by the use of alternative initiation codons.

144




145




or

146




or

147




148




Only the entry, whose 3D structure was experimentally determined and submitted to the PDB, has this secondary structure annotation. (No computational result here!)

149




150




The Cross-References section contains links to entries in other databases that contain some information about this protein.

151




Information Page

152




Each line begins with a two-character line code, which indicates the type of data contained in the line.

153




OptionalReference cross-reference(s)RX

OptionalReference comment(s)RC

Once or moreReference positionRP

Once or moreReference numberRN

OptionalOrganism hostOH

OnceTaxonomy cross-referenceOX

Once or moreOrganism classificationOC

OptionalOrganelleOG

Once or moreOrganism speciesOS

OptionalGene name(s)GN

Once or moreDescriptionDE

Three timesDateDT

Once or moreAccession number(s)AC

Once; starts the entryIdentificationID

Occurrence in an entryContentLine

code

Once; ends the entryTermination line//

Once or moreSequence datablanks

OnceSequence headerSQ

Once or moreFeature table dataFT

OptionalKeywordsKW

OnceProtein existencePE

OptionalDatabase cross-referencesDR

OptionalComments or notesCC

Once or moreReference locationRL

OptionalReference titleRT

Once or more (Optional if RG line)Reference authorsRA

Once or more (Optional if RA line)Reference groupRG

Occurrence in an entryContentLine code

154


Protein DatabasesPrimary Protein Structure Databases

The Protein Data Bank (PDB) is a repository for the 3D structural data of large biological molecules, such as proteins and nucleic acids (mainly proteins). The data, typically obtained by X-ray crystallography or NMR spectroscopy and submitted by biologists and biochemists from around the world. The structures in PDB are freely accessible on the Internet via the websites of its member organizations (PDBe, PDBj, and RCSB). The PDB is overseen by an organization called the Worldwide Protein Data Bank (wwPDB).

The Structural Classification of Proteins (SCOP) and CATH Protein Structure Classification (CATH) categorize structures according to type of structures stored in PDB and assumed their evolutionary relations.

Secondary Protein Structure Databases

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Protein DatabasesReading a PDB Entry: E. coli dUTPase protein

http://www.rcsb.org3H6X

3H6XE coli dUTPase protein

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Protein Databases http://www.rcsb.org3H6X

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记事本

158


159

Protein Databases


Reading a PDB Entry: E. coli dUTPase proteinhttp://www.rcsb.org

3H6X

Title Section

This section contains records used to describe the experiment and the biological macromolecules present in the entry. Keywords in this section include:

HEADER, OBSLTE, TITLE, SPLIT, CAVEAT, COMPND, SOURCE, KEYWDS, EXPDTA, AUTHOR, REVDAT, SPRSDE, JRNL, REMARK.

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Protein Databases



3H6X

HEADER identifies a PDB entry through the idCode field. This record also provides a classification for the entry. Finally, it contains the date when the coordinates were deposited to the PDB archive.

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Protein Databases



3H6X

TITLE contains a title for the entry. It is also the title of the cited publication.

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Protein Databases



3H6X

COMPND describes the macromolecular contents of an entry.

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Protein Databases



3H6X

SOURCE specifies the biological and chemical source of each biological molecule in the entry.

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Protein Databases



3H6X

KEYWDS contains a set of terms relevant to the entry, which can be used for keyword search across databases.

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Protein Databases



3H6X

EXPDTA identifies the experimental technique used:

X-RAY DIFFRACTIONFIBER DIFFRACTIONNEUTRON DIFFRACTIONELECTRON CRYSTALLOGRAPHYELECTRON MICROSCOPY SOLID-STATE NMR SOLUTION NMR SOLUTION SCATTERING

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Protein Databases



3H6X

AUTHOR contains the names of the people responsible for the contents of the entry.

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Protein Databases



3H6X

REVDAT contains a history of the modifications made to an entry since its release.

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Protein Databases



3H6X

JRNL contains the primary literature citation that describes the experiment which resulted in the deposited coordinate set.

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Protein Databases



3H6X

REMARK presents experimental details, annotations, comments, and information not included in other records.

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Protein Databases



3H6X

Primary Structure Section

This section contains the sequence of residues in each chain of the macromolecule(s).

DBREF, SEQADV, SEQRES, MODRES

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Protein Databases



3H6X

Heterogen Section

This section contains the complete description of non-standard residues in the entry.

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Protein Databases



3H6X

Secondary Structure SectionThis section describes helices, sheets, and turns found in protein and polypeptide structures.

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Protein Databases



3H6X

Connectivity Annotation Section

This section specifies the existence and location of disulfide bonds and other linkages.

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Protein Databases



3H6X

Crystallographic and Coordinate Transformation Section

This section describes the geometry of the crystallographic experiment and the coordinate system transformations.

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Protein Databases



3H6X

The most important part!!!

Coordinate SectionThis section contains the collection of atomic coordinates.

X Y Z

Atom index

Residue index

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Protein Databases



3H6X

Connectivity Section

This section provides information on atomic connectivity.

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Protein Databases



3H6X

Bookkeeping Section

This section provides some final information about the file itself.

A *.pdb file always ends with this “END”.

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Maestro

VMD

Pymol




3H6X.pdb

Chapter 4 Structure

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Protein DatabasesFinding out more about your protein : RESID

http://www.ebi.ac.uk/RESID

RESID, the post-translational modification database maintained by John Garavelli at the European Bioinformatics Institute (EBI).

Finding out more about your protein : RESIDhttp://www.ebi.ac.uk/RESID

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Protein Databases


Myristoylation (豆蔻酰化 )


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Protein Databases



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Protein DatabasesFinding out more about your protein : RESID

http://www.ebi.ac.uk/RESID

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Protein DatabasesFinding out more about your protein : KEGG

http://www.genome.jp/kegg

KEGG - the Kyoto Encyclopedia of Genes and Genomes, was initiated by the Japanese human genome program in 1995. KEGG can be regarded as a "computer representation" of the biological system. Its collection includes genomes, enzymatic pathways, and biological chemicals. The PATHWAY database records networks of molecular interactions in the cells, and variants of them specific to particular organisms.

Home page of KEGG : http://www.genome.jp/kegg

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Compound

Enzyme

Pathway

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Protein Databases

Compoundrelevant Pathways

Enzyme


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Protein Databases http://www.genome.jp/kegg

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Finding out more about your protein : KEGGhttp://www.genome.jp/keggProtein Databases

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Toll-like Receptor (TLR) - recognize pathogen-associated molecular patterns (PAMPs) on invading organisms but not on hosts and are the first line of defense in innate immunity.


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Removing vector sequenceshttp://www.genome.jp/keggProtein Databases

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http://www.genome.jp/keggProtein Databases

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TLR4

LIPID of LPS

MD2

Park et al. 2009

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http://www.genome.jp/keggProtein Databasesautoimmunity caused by over-activity of TLRs : Systemic Lupus Erythematosus (SLE) 系统性红斑狼疮

Agonist Antagonist

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Protein Databases http://expasy.org

ProtParam - a program you can use online on the ExPASy server, is a convenient way to estimate every simple physico-chemical property, include the molecular weight, theoretical pI, amino acid composition, atomic composition, extinction coefficient, estimated half-life, instability index, aliphatic index and grand average of hydropathicity.

Finding out more about your protein : ProtParam

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http://expasy.orgProtein DatabasesFinding out more about your protein : ProtParam

http://expasy.orgFinding out more about your protein : ProtParam

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Protein Databases http://expasy.orgFinding out more about your protein : ProtParam

Protein DatabasesFinding out more about your protein : ProtParam


P05130

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P05130

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P05130

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Protein DatabasesFinding out more about your protein: WebLogo

Sequence logos - are a graphical representation of an amino acid or nucleic acid multiple sequence alignment developed by Tom Schneider and Mike Stephens. Each logo consists of stacks of symbols, one stack for each position in the sequence. The overall height of the stack indicates the sequence conservation at that position, while the height of symbols within the stack indicates the relative frequency of each amino or nucleic acid at that position. In general, a sequence logo provides a richer and precise description of, for example, a binding site.

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WebLogo - is a web based application designed to make the generation of sequence logos easy and painless. WebLogo has featured in over 150 scientific publications. http://weblogo.berkeley.edu

http://weblogo.berkeley.edu

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http://1.51.212.243/promoter.seqs

http://weblogo.berkeley.edupromoter.seqs

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http://1.51.212.243/promoter.seqs

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In the promoter region of genes, we usually found a special fragment, called TATA box (also called Goldberg-Hogness box). The TATA box has the core DNA sequence 5'-TATAAA-3' or a variant. It is usually found as the binding site of RNA polymerase II.

http://correlogo.abcc.ncifcrf.gov


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Protein DatabasesFinding out more about your protein: MEME

Sequence Motif - a nucleotide or amino-acid sequence pattern that is widespread and has, or is conjectured to have, a biological significance.

An example is the N-glycosylation site motif:

Asn, followed by anything but Pro, followed by either Ser or Thr, followed by anything but Pro

This pattern can be written as N{P}[ST]{P}(Regular expression), where N=Asn, P=Pro, S=Ser, T=Thr; {X} means any amino acid except X; and [XY] means either X or Y. The notation [XY] does not give any indication of the probability of X or Yoccurring in the pattern. Observed probabilities can be graphically represented using sequence logos.

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The MEME Suite - Motif-based sequence analysis tools.

The MEME Suite allows you to:• discover motifs on groups of related DNA or protein sequences, • search sequence databases using motifs, • compare a motif to all motifs in a database of motifs. Home page : http://meme.sdsc.edu/meme/intro.html

http://meme.sdsc.edu/meme/intro.html

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http://meme.sdsc.edu/meme/intro.html

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http://1.51.212.243/meme.seqs

http://meme.sdsc.edu/meme/intro.htmlmeme.seqs

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meme.seqshttp://meme.sdsc.edu/meme/intro.html


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Protein Databases meme.seqshttp://meme.sdsc.edu/meme/intro.html

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Protein DatabasesFinding out more about your protein

The Nuclear Protein Database (NPD) - a searchable database of information on proteins that are localized to the nucleus of vertebrate cells. http://npd.hgu.mrc.ac.uk/user

SignalP 3.0 server - predicts the presence and location of signal peptide cleavage sites in amino acid sequences from different organisms. http://www.cbs.dtu.dk/services/SignalP

Phospho.ELM - a database of S/T/Y phosphorylation sites. http://phospho.elm.eu.org

SYSTERS - protein family database of large-scaleprotein clustering based on sequence similarity

More tools and databases, please see Information Page

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