Proteiinianalyysi 52930 (2 ov)

Liisa Holm

Organisaatio

• Luennot & Laskuharjoitukset – 30.3.-28.4.2005, ke, to 14-16, LS 2012– http://www.bioinfo.biocenter.helsinki.fi:8080/d

ownloads/teaching/spring2005/proteiinianalyysi/index.html

• Tentti– Bonusta aktiivisuudesta laskuharjoituksissa

• Oheislukemisto– Lesk: Introduction to bioinformatics. Oxford

University Press.

Aikataulu 30.3. ke Luento

31.3. to Luento

6.4. ke Laskuharjoitus 1

7.4. to Luento

13.4. ke Laskuharjoitus 2

14.4. to Luento

20.4. ke Laskuharjoitus 3

21.4. to Luento

27.4. ke Laskuharjoitus 4

28.4. to Tentti

Kurssin tavoitteet

• miten proteiinisekvenssejä luetaan

• proteiinien luokittelujärjestelmät

• sekvenssi – rakenne – funktio

• evoluutio

Muut kurssit

• Esitiedot: – Geneettinen bioinformatiikka 1-2 ov

• sekvenssivertailu• fylogeniapuut

• Soveltaminen:– Proteiinianalyysin harjoitustyöt 3 ov

• webbityökalujen käyttö

Johdanto

Proteiinien merkitys• Proteiinit tekevät kaiken työn solussa ja

ovat osallisina:– Geenisäätelyssä– Metaboliassa– Signaloinnissa– Tukirangassa– Kuljetuksessa– Solunjakautumisessa

http://www.websters-online-dictionary.org/definition/english/ce/cell.html

Structural proteins

• Collagen

1K6F http://www.aw-bc.com/mathews/ch06/fi6p13ad.htm

Actin and muscles

Enzymes

• Catalytic triad: Asp, Ser, His

1CHO

Transcription factors

1L3L

Ligand

DNA

Mistä proteiinit tulevat?

• DNA > RNA > proteiini– geneettinen koodi

• DNAn emäskolmikko koodaa yhtä aminohappoa• 20 aminohappoa

– lineaarinen sekvenssi• tyypillinen pituus 100-400 aminohappoa• keskimäärin noin 150 aminohappoa

Suuri yllätys …

DNA:n rakenne on hyvin säännölinenWatson & Crick (1953)

Myoglobiini

1mbn

Proteiinin rakenteesta puuttuu symmetriaKendrew & Perutz (1957)

Proteiinit ovat erikoislaatuisia polymeerejä:

• Tietyllä proteiinilla on aina sama aminohapposekvenssi– Proteiinin sekvenssi määräytyy DNA-

sekvenssin perusteella

• Tietyllä proteiinilla on aina uniikki kolmiulotteinen rakenne.– Proteiinin rakenne määräytyy

aminohapposekvenssin perusteella.

aina = biologinen aina (poikkeuksia löytyy)

Ei funktiota ilman rakennetta

• Luonnon proteiinit laskostuvat spesifiseksi kolmiulotteiseksi rakenteeksi– komplementaarinen interaktiopartnerille

• Denaturaatio tuhoaa funktion

EvoluutioSekvenssi – Rakenne - Funktio

DNA-sekvenssi

Proteiinin sekvenssi Proteiinin rakenne

Proteiinin funktioLuonnonvalinta

Sekvenssi

proteiinien identifiointi

• klassinen biokemia– proteiinin puhdistus– molekyylipaino– isoelektrinen piste– CD- ym. spektroskopia – jne.

• laskennallinen analyysi– DNA-sekvenssi geenintunnistus, eksonit/intronit

käännös proteiiniksi– sekvenssivertailut

• post-genomiikka– transkriptioprofilointi, proteiini-proteiini-interaktiot, ym.

Historiaa1953 DNA:n rakenne

1955 Ensimmäinen proteiinisekvenssi

1957 Myoglobiinin rakenne

1975 DNA:n sekvensointimenetelmät

1977 X-174 faagin ’genomi’

1995 Haemophilus influenzaen genomi

1996 Hiivan genomi

1998 Sukkulamadon genomi

2000 Ihmisen genomi

2000 Rakennegenomiikkaprojekti

Genomit

• DNA-sekvensointi– entsymaattinen synteesi, spesifiset terminaattorit– proteiinisekvenssit johdetaan DNA-sekvenssistä

• ORF, open reading frame• varmennus: linjaus tunnetun EST:n tai cDNA:n tai proteiinin

kanssa• eukaryoottien eksoni-introni-ongelma

• genomiprojektit– noin 136 organismia– eukaryootteja, arkebakteereja ja eubakteereja

Proteome coverageOrganism Biological Features proteinsS. cerevisiae

(yeast)

Genes for existence as a single-celled organism with the basic structure and organisation of the eukaryotic cell

6231

E. coli

(bacterium)

Genes for growth on external sources of energy, molecular cell transport through cell membrane, metabolic pathways and replication as a single cell

4356 - 5333

C. elegans

(Nematode)

Genes for development by a unique cell lineage, nervous system and reproduction

22515

D. melanogaster

(Fruit fly)

Model for developmental processes by hormones and cell-cell interactions

17341

H. sapiens

(human)

Duplicates many gene functions in other model organisms and in addition includes control of higher brain functions

28814

About 136 complete proteomes deduced from complete genomes.

Täydellinen proteomi

• varmuus ”puuttuvista” geeneistä

• kaikki geenit eivät ekspressoidu samaan aikaan ja samassa paikassa

• vaihtoehtoinen silmukointi, post-translationaaliset modifikaatiot: yhdestä geenistä voikin tulla monta proteiinia– glykosylaatio– fosforylaatio

Tietokantoja

• EBI – http://www.ebi.ac.uk – http://www.ebi.ac.uk/proteome

• NCBI - Entrez– http://www.ncbi.nlm.nih.gov

• nrdb, ’non-redundant database’– 490.374.618 aminohappoa– 1.504.726 sekvenssiä

Rakenne

Protein structure

• Primary structure

• Secondary structure

• Super-secondary structure

• Tertiary structure

• Quaternary structure

Secondary structure

• backbone– no amino acid side chains

• regular patterns – of hydrogen-bonds– backbone torsion angles

• types of secondary structure

–α-helix–β-sheet–...

α-Helix

β-Sheethydrogen bond pattern: n, n+4

β-sheet

http://broccoli.mfn.ki.se/pps_course_96

view from the top view from the side

β-strands

Cartoon representation

2TRX 2AAC

Supersecondary structures

• local arrangments of secondary structure elements

http://www.expasy.org/swissmod/course/text/chapter2.htm

Tertiary structure

1coh

Quaternary structure

1coh

Protein structure determination

• Protein expression– membrane proteins– aggregation

• X-Ray crystallography

• NMR (nuclear magnetic resonance)

• Cryo-EM (electron microscopy)

Structures by X-ray crystallography

➔Crystallize protein

• Collect diffraction patterns

• Improve iteratively:– Calculate electron density map

• Phase problem

– Fit amino acid trace through map

X-ray crystallography

• Crystallization

• “An art as much as a science”Charges

http://crystal.uah.edu/~carter/protein/crystal.htm

Diffraction and electron density maps

Diffraction pattern

X-ray source Crystal

Intensities

Iterative refinement

http://www.sci.sdsu.edu/TFrey/Bio750/Bio750X-Ray.html

Higher resolution =more accurate positioning of atoms

Resolution

NMR

• Create highly concentrated protein solution

• Record spectra

• Assign peaks to residues

• Calculate constraints

• Compute structure

NMR spectra

1D 2D

http://www.cryst.bbk.ac.uk/PPS2/projects/schirra/html/2dnmr.htm

Distance constraints from NMR

• From the sequence– Topology– Bond angles– Bond lengths

• From the NMR experiment– Torsion angles– Distance constraints HαR

CO

H

CO

Torsion angle

Ensemble of structures

SH3-domain

1aey

What is the true protein structure?

• X-Ray– “frozen” state of a protein

• crystal contacts✔ large protein structure

• NMR✔ protein in solution– limited in size

Molecular complexesvia X-ray

1fjg

30 S subunit of the ribosome

Protein

RNA

Cryo-EMSingle particle image reconstruction

Koning et al. (2003)

Bacteriophage MS2

Fitting X-Ray structures into density maps

GroEL-complex

1gr6

Hemoglobin

Protein structure

databases

http://www.wwpdb.org/index.html

Molekulaarinen funktio

Post-genomic view:Function = interactions

(From left to right, figures adapted from Olsen Group Docking Page at Scripps, Dyson NMR Group Web page at Scripps, and from Computational Chemistry Page at Cornell Theory Center).

Enzymes

• Catalytic triad: Asp, Ser, His

1CHO

Mechanism• Enzymes speed up chemical reactions• Enzymes are not consumed by the reaction• Stabilization of the transition state• Charge-relay cascade

Convergent evolution in serine proteases

• same reaction• same mechanism• same orientation of

catalytic residues• different structures

– Chymotrypsin:• His-57, Asp-102, Ser-195

– Subtilisin:• Asp-32, His-64, Ser-221

1cho / 1sib

Substrate specificity

Perona & Craik (1997)

Transcription factors

1L3L

Ligand

DNA

Hydrogen bonding pattern

Vannini (2002)

Funktion määritys

• Biokemiallinen analyysi

• Geneettinen analyysi, fenotyyppi

• Proteiini-proteiini-interaktio

• Työläitä menetelmiä

• Määritysmenetelmä usein räätälöitävä erikseen jokaiselle funktiolle

Evoluutio

EvoluutioSekvenssi – Rakenne - Funktio

DNA-sekvenssi

Proteiinin sekvenssi Proteiinin rakenne

Proteiinin funktioLuonnonvalinta

Application: Finding Homologs

Application:Finding Homologues

• Find Similar Ones in Different Organisms• Human vs. Mouse vs. Yeast

– Easier to do Expts. on latter!

(Section from NCBI Disease Genes Database Reproduced Below.)

Best Sequence Similarity Matches to Date Between Positionally ClonedHuman Genes and S. cerevisiae Proteins

Human Disease MIM # Human GenBank BLASTX Yeast GenBank Yeast Gene Gene Acc# for P-value Gene Acc# for Description Human cDNA Yeast cDNA

Hereditary Non-polyposis Colon Cancer 120436 MSH2 U03911 9.2e-261 MSH2 M84170 DNA repair proteinHereditary Non-polyposis Colon Cancer 120436 MLH1 U07418 6.3e-196 MLH1 U07187 DNA repair proteinCystic Fibrosis 219700 CFTR M28668 1.3e-167 YCF1 L35237 Metal resistance proteinWilson Disease 277900 WND U11700 5.9e-161 CCC2 L36317 Probable copper transporterGlycerol Kinase Deficiency 307030 GK L13943 1.8e-129 GUT1 X69049 Glycerol kinaseBloom Syndrome 210900 BLM U39817 2.6e-119 SGS1 U22341 HelicaseAdrenoleukodystrophy, X-linked 300100 ALD Z21876 3.4e-107 PXA1 U17065 Peroxisomal ABC transporterAtaxia Telangiectasia 208900 ATM U26455 2.8e-90 TEL1 U31331 PI3 kinaseAmyotrophic Lateral Sclerosis 105400 SOD1 K00065 2.0e-58 SOD1 J03279 Superoxide dismutaseMyotonic Dystrophy 160900 DM L19268 5.4e-53 YPK1 M21307 Serine/threonine protein kinaseLowe Syndrome 309000 OCRL M88162 1.2e-47 YIL002C Z47047 Putative IPP-5-phosphataseNeurofibromatosis, Type 1 162200 NF1 M89914 2.0e-46 IRA2 M33779 Inhibitory regulator protein

Choroideremia 303100 CHM X78121 2.1e-42 GDI1 S69371 GDP dissociation inhibitorDiastrophic Dysplasia 222600 DTD U14528 7.2e-38 SUL1 X82013 Sulfate permeaseLissencephaly 247200 LIS1 L13385 1.7e-34 MET30 L26505 Methionine metabolismThomsen Disease 160800 CLC1 Z25884 7.9e-31 GEF1 Z23117 Voltage-gated chloride channelWilms Tumor 194070 WT1 X51630 1.1e-20 FZF1 X67787 Sulphite resistance proteinAchondroplasia 100800 FGFR3 M58051 2.0e-18 IPL1 U07163 Serine/threoinine protein kinaseMenkes Syndrome 309400 MNK X69208 2.1e-17 CCC2 L36317 Probable copper transporter

Application:Finding Homologues (cont.)

• Cross-Referencing, one thing to another thing• Sequence Comparison and Scoring• Analogous Problems for Structure Comparison• Comparison has two parts:

(1) Optimally Aligning 2 entities to get a Comparison Score

(2) Assessing Significance of this score in a given Context

Mitä hyötyä proteiinien bioinformatiikasta voisi olla?

• kuvitteellinen virusepidemia– DNA-sekvenssi– vertailu tunnettuihin viruksiin [10]– antiviruslääkkeiden kehittely

• virukselle spesifiset proteiinit: replikaatio- tai vaippaproteiinit [01]

– tietokantahaut [15]– homologiamallitus [25] / ab initio [55]

» lääkesuunnittelu, vasta-aineterapia [50]» lääkeaineen biologinen siedettävyys [75]

sekvenssi rakenne

Aminohappojen ominaisuudet

• Proteiinit ovat itseorganisoituvia lineaarisia heteropolymeerejä, joiden sekvenssi on jalostunut luonnonvalinnassa

• 20 aminohappoa– peptidirunko– sivuketju

• sekvenssi määrää rakenteen

Amino Acid Symbol Structure*pK1

(COOH)

pK2

(NH2)pK R Group

Amino Acids with Aliphatic R-Groups

Glycine Gly - G                                       2.4 9.8  

Alanine Ala - A                                               2.4 9.9  

Valine Val - V                                                         2.2 9.7  

Leucine Leu - L                                                                        2.3 9.7  

Isoleucine Ile - I                                                                              2.3 9.8  

Non-Aromatic Amino Acids with Hydroxyl R-Groups

Serine Ser - S                                                           2.2 9.2 ~13

Threonine Thr - T                                                         2.1 9.1 ~13

Amino Acids with Sulfur-Containing R-Groups

Cysteine Cys - C                                                          1.9 10.8 8.3

Methionine Met-M                                                                             2.1 9.3  

Acidic Amino Acids and their Amides

Aspartic Acid Asp - D                                                                    2.0 9.9 3.9

Asparagine Asn - N                                                                     2.1 8.8  

Glutamic Acid Glu - E                                                                                   2.1 9.5 4.1

Glutamine Gln - Q                                                                                      2.2 9.1  

Basic Amino Acids

Arginine Arg - R

                                                                                      

 

1.8 9.0 12.5

Lysine Lys - K                                                                     2.2 9.2 10.8

Histidine His - H                                                                         1.8 9.2 6.0

Amino Acids with Aromatic Rings

Phenylalanine Phe - F                                                                     2.2 9.2  

Tyrosine Tyr - Y                                                                                  2.2 9.1 10.1

Tryptophan Trp-W                                                                               

2.4 9.4  

Imino Acids

Proline Pro - P                                       

2.0 10.6 

Aminohappojen ominaisuuksia

levels of complexity in folding

WHAT DO WE KNOW ABOUT PROTEIN FOLDING?

• water soluable proteins are "globular," tight packed, water excluded from interior, folded up.

• bond lengths and bond angles don't vary much from equilibrium positions.

• structures are stable and relatively rigid. • folding possibilities are limited, both along the backbone chain and

within the side chain groups. • folding motifs are used repetitively. • with similar proteins (say from different organisms) structure tends

to be more conserved than the exact sequence of amino acids. • although sequence must determine structure, it is not yet possible to

predict the entire structure from sequence accurately.• Net stability corresponds to a few hydrogen bonds.

Sekundaarirakenne > tutorial

• proteiini on kuin rasvapisara vedessä

• peptidirungon pooliset ryhmät muodostavat vetysidoksia– NH -- O=C

• syntyy säännönmukaisia sekundaarirakenteita

• sivuketju moduloi sekundaarirakennepreferenssejä

DSSP

Dictionary of Protein Secondary Structure: Pattern Recognition of Hydrogen-Bonded and Geometrical Features

W. Kabsch & C. Sander

Biopolymers 22, 2577-2637 (1983)

Hydrogen bonds

N H

O C

E ~ q1 q2 [ 1/r(ON) + 1/r(CH) – 1/r(CN) – 1/r(OH)Ideal H-bond is co-linear, r(NO)=2.9 A and E=-3.0 kcal/molCutoffs in DSSP allow 2.2 A excess distance and ±60º angle

-0.20e

+0.20e

-0.42e

+0.42e

Elementary H-bond patterns

• n-turn(i) =: Hbond(i,i+n), n=3,4,5

• Parallel bridge(i,j) =: [ Hbond(i-1,j) AND Hbond(j,i+1) ] OR

[ Hbond(j-1,i) AND Hbond(i,j+1) ]

• Antiparallel bridge(i,j) =: [ Hbond(i,j) AND Hbond(j,i) ] OR

[ Hbond(i-1,j+1) AND Hbond(j-1,i+1) ]

-N-C-C--N-C-C--N-C-C--N-C-C- H O H O H O H O

-N-C-C--N-C-C--N-C-C--N-C-C--N-C-C- H O H O H O H O H O

-N-C-C--N-C-C--N-C-C--N-C-C-—N-C-C-—N-C-C- H O H O H O H O H O H O

3-turn

4-turn

5-turn

N-turns

-N-C-C--N-C-C--N-C-C--N-C-C—N-C-C- H O H O H O H O H O

H O H O H O H O H O-N-C-C--N-C-C--N-C-C--N-C-C—N-C-C-

Parallel bridge

-N-C-C--N-C-C--N-C-C--N-C-C- H O H O H O H O

O H O H O H O H -C-C-N--C-C-N--C-C-N--C-C-N-

Antiparallel bridge

Antiparallel beta-sheet is significantly more stable due to the well aligned H-bonds.

Cooperative H-bond patterns

• 4-helix(i,i+3) =: [4-turn(i-1) AND 4-turn(i)]

• 3-helix(i,i+2) =: [3-turn(i-1) AND 3-turn(i)]

• 5-helix(i,i+4) =: [5-turn(i-1) AND 5-turn(i)]

• Longer helices are defined as overlaps of minimal helices

Beta-ladders and beta-sheets

• Ladder =: set of one or more consecutive bridges of identical type

• Sheet =: set of one or more ladders connected by shared residues

• Bulge-linked ladder =: two ladders or bridges of the same type connected by at most one extra residue on one strand and at most four extra residues on the other strand

3-state secondary structure

• Helix

• Strand

• Loop

• Quoted consistency of secondary structure state definition in structures between sequence-similar proteins is ~70 %

• Richer descriptions possible– E.g. phi-psi regions

Amino acid preferences for different secondary structure

• Alpha helix may be considered the default state for secondary structure. Although the potential energy is not as low as for beta sheet, H-bond formation is intra-strand, so there is an entropic advantage over beta sheet, where H-bonds must form from strand to strand, with strand segments that may be quite distant in the polypeptide sequence.

• The main criterion for alpha helix preference is that the amino acid side chain should cover and protect the backbone H-bonds in the core of the helix. Most amino acids do this with some key exceptions.– alpha-helix preference:

• Ala,Leu,Met,Phe,Glu,Gln,His,Lys,Arg

• The extended structure leaves the maximum space free for the amino acid side chains: as a result, those amino acids with large bulky side chains prefer to form beta sheet structures:– just plain large:Tyr, Trp, (Phe, Met)– bulky and awkward due to branched beta carbon:Ile, Val, Thr– large S atom on beta carbon:Cys

• The remaining amino acids have side chains which disrupt secondary structure, and are known as secondary structure breakers:– side chain H is too small to protect backbone H-bond:Gly– side chain linked to alpha N, has no N-H to H-bond;

rigid structure due to ring restricts to phi = -60: Pro– H-bonding side chains compete directly with backbone H-

bonds: Asp, Asn, Ser• Clusters of breakers give rise to regions known as loops

or turns which mark the boundaries of regular secondary structure, and serve to link up secondary structure segments.