Vorlesung 2004 Bioinformatik

Transkript

1 DNA und Zellen

2 Vorlesung 2004 Bioinformatik Einführung in die Molekularbiologie für Informatiker C. Frömmel

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5 DNA Desoxyribonukleinsäure

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10 Was noch ungelöst ist: Wie faltet sich z.b. MGTIIVHKGGFPFDRIIAGFKL VVCIIESSTGGLPGEWQQHNGG AQTYYCGDQNTVFAPTERIISA AGVLIKHRRSDFHTTKLMSACD

11 STRAP mit Proteasomen-Verwandten (E.coli, Hefe) (aus 143 Organismen Gille et al. J. Mol. Biol., 2003) 16% Identität und trotzdem gleich Faltung

12 Proteasom: 28 Untereinheiten Seitenansicht der Tonne Proteasom aufgeschnitten

13 Proteasom von oben Proteasom in der Mitte geschnitten

14 Proteasom (Sekundärstrukturen) Alle Untereinheiten haben einen ähnlichen Fold

15 Proteasom

16 Cyt C Cyt C mit gebundenen Wasser

17 Cytochrom C (mit Häm)

18 Nur ß-Faltblätter + Turns Antikörperfragment (mit gebundenem Antigen)

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20 Antikörper Blick von oben Sehr unterschiedliche Peptide können sich manchmal an die gleiche Bindungsregion binden (Molekulare Mimikry, Kreuzreaktivität) GAEDLQKATPDLNQKL EWGGARIGLWRIT kllkgpl D-Peptid FAB fragments CB4-1 (anti-p24)

21 Chymotrypsin

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24 Protein sein aktives Zentrum FK506 binding protein mit Ligand

25 Are you interested in process simulation? e.g. in prion growth? Pöschel, T., Brilliantov, N.V., Frömmel, C. Kinetics of Prion Growth. Biophys. Journal 85: (2003)

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27 1CSE subtilisin Carlsberg 1SBT subtilisin Are you interested molecular mimicry??

28 The needle-haystack problem Basics: optimization 7 dimensions Hoppe, A. and Frömmel, C. NeedleHaystack: A programm for the rapid recognition of local structures in large sets of atomic coordinates. J. Appl. Cryst. 36: (2003)

29 ähnlich unähnlich Ser 221 His 64 Subtilisin

30 Comparison of all activ subunits on atomic level ß1 yeast compared to ß1 (cow) similar so or so dissimilar

31 Substrat eingepasst, undenkbar grobes Modell! COO- NH3+ substrate

32 Subtilisin mit Inhibitor

33 + kleinen Ligand Thrombin + Hirudin

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43 Hämoglobin: eine Kette von vieren Hämgruppe Nur Helices und Turns

44 4 Untereinheiten (2 alpha 2 beta) ergeben ein Hämoglobinmolekül (Quartärstruktur) Bei Sauerstoffbindung ändert sich (leicht) die Struktur

45 Hämoglobin

46 Hämoglobin

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52 Bioinformatics was coming from...

53 Hanging on the structure determination of proteins (x-ray) Bioinformatics 1980

54 Later: Bioinformatics = Alignment?

55 The mouse in men Humanities in the mouse Proteasome subunit (ß,active) PRC7_MOUSE PRC7_HUMAN VHTGTTIMAVEFDGGVVVGSDSRVSAGTAVVN : VHTGTTIMAVEFDGGVVMGSDSRVSAGEAVVN RVFDKLSPLHQRIFCALSGSAADAQAIADMAAYQLELHGLELEEPPLVLA... : : : :... RVFDKLSPLHERIYCALSGSAADAQAVADMAAYQLELHGIELEEPPLVLA... 95% identical!

56 The mouse in men Humanities in the mous Time since common root Number of genes 75 Mio years Mouse men Nucleotides 2,5 GB 2,9 GB Chromosomes 19 + X 21 + X homologoues genes Similarities of orthologoues proteins Sequenzhomology (total) 99 % Mediane 78,5 % ( Paare) 40 %

57 ? Arnold Schwarzenegger =

58 All protein pairs above the curve are showing similar fold and it follows Men=Mouse Schneider and Sander, 1991

59 Service: e.g. Mapping of SNPs on protein structures * Gille & Frömmel 2001 Network: Heart insufficiency Inborne heart diseases xyz-pro= myosin

60 protein structure/function prediction grey: Hypertrophic cardiomyopathy Myosin yellow: Dilatative cardiomyopathy Dähmlow et al. 2002

61 Today 1. Does it support protein structure/function prediction? 2. Does it help to find relevant information? 3. Does it help to structure large data sets?? 4. Does it accelerate drug design cycles???

62 Alle über der Kurve haben den gleichen Fold und damit die gleiche Struktur und damit die gleiche Funktion? Schneider and Sander, 1991

63 Alignment Primärstrukturen Proteasomenuntereinheiten und Verwandte siehe auch prot.doc SHEET HELIX COIL a1_1ryp.dssp.gz 001..gadRHITIFSPEgR.LyQVEyAfkATNQTN... a2_1ryp.dssp.gz 002 tdrysfslttfspsgk.lgqidyaltavkqg... a3_1ryp.dssp.gz 002 srrydsrttifspegr.lyqveyalesisha... a4_1ryp.dssp.gz 001..gydRALSIFSPDgH.IfQVEyAleAVKRG... a5_1ryp.dssp.gz drgVSTFSPEgR.LfQVEySleAIKLG... a6_1ryp.dssp.gz 002 rnnydgdtvtfsptgr.lfqveyaleaikqg... a7_1ryp.dssp.gz 001 gtgydlsnsvfspdgr.nfqveyavkaveng... b1_1ryp.dssp.gz lkkG...EV b2_1ryp.dssp.gz b3_1ryp.dssp.gz sdpSS... b4_1ryp.dssp.gz b5_1ryp.dssp.gz b6_1ryp.dssp.gz qfnP...YG b7_1ryp.dssp.gz tqqPI hs_ecoli.dssp ap_mycobacteriumtuberculosis.embl msfPYFISPEqAMrERSELarKGIARA... a1_1ryp.dssp.gz INSLAVRG.kdCTVVISQKk...vPDKLLDPT.T...VS a2_1ryp.dssp.gz VTSLGIKA.tnGVVIATEKk...sSSPLAMSE.T...LS a3_1ryp.dssp.gz GTAIGIMA.sdGIVLAAERk...vTSTLLEQDT...STe a4_1ryp.dssp.gz TCAVGVKG.knCVVLGCERr...sTLKLQDTRIT...Ps a5_1ryp.dssp.gz STAIGIAT.keGVVLGVEKr...aTSPLLESD.S...IE a6_1ryp.dssp.gz SVTVGLRS.ntHAVLVALKr...nADELSS...Y...QK a7_1ryp.dssp.gz TTSIGIKC.ndGVVFAVEKl...iTSKLLVPQ.K...NV b1_1ryp.dssp.gz 007 SlgASIMAVTF.KDGVIlgADSRTTTGAYI.ANR...V...TD b2_1ryp.dssp.gz ttiVGVKF.NNGvvIAADTRSTQGPIV.ADK...N...Ca b3_1ryp.dssp.gz 006 INGgiVVAMTG.KDCVAiaCDLRLGSQSLG.VSN...K...FE b4_1ryp.dssp.gz 001..mdiILGIRV.QDSviLASSKAVTRGISV.LKD...S...Dd b5_1ryp.dssp.gz tttLAFRF.QGGiiVAVDSRATAGNWV.ASQ...T...Vk b6_1ryp.dssp.gz 007 DngGTILGIAG.EDFAVlaGDTRNITDYSI.NSR...Y...EP b7_1ryp.dssp.gz 006 VTGTSVISMKY.DNGviIAADNLGSYGSLL.RFN...G...Ve hs_ecoli.dssp ttiVSVRR.NGHvvIAGDGQATLGNTV.MKG...N...Vk ap_mycobacteriumtuberculosis.embl KSVVALAyaGGVLFVAEnP..SRSLQKI...SELyDR

64 Now we... 4-point pharmacophore z.b. ACE inhibitor Finn et al 1998

65 Bioinformatics is beginning: to provide both conceptual bases and practical methods for detecting systemic functional behaviours of the cell and the organism and methods to predict influence of anything on living systems.

66 What is missing??? Gene Genes?? mrna Gene(s) (mrnas)??(????????????????????????) protein(s) (fold function) proteins????????????????????????? cells Cells???????????????????????????? organs Organ??????????????????????????? organisms Genom?? (??????????????????????????????????) personalised health care

67 Steps forward: Experimental test systems Computational system biology Medical test systems Computational system medicine

68 bpi Credo 1 practise theory

69 Bioinformatics is going to the doctors Medical Faculty (Berlin, CUB)

70 The ultimate goal of all medical research is the reduction of morbidity and mortality through prevention and treatment!

71 e.g. Rheumatoide arthritis progression Ätiologie Pathogenese activity state therapy Berlinflame Supported by BMBF

72 DNA-Array Hybridisation synovectomy array-hybridisation RNA-extraction derivatisation AAAA AAAA TTTT cdna-synthesis UUUU

73 Goals of expressions analysis of genes Identification of important genes Pathogenesis and mechanisms of regulation Moleculare classifikation of arthritis identification of target genes Diagnostica, prognostica and therapeutica

74 Credo 2 phenotype genotype

75 Gene to physiology! Credo 2a physiology genotype

76 Neuroscience Berlin Neuroimaging centre (Villringer, Dirnagl)

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79 Computational system biology Kinetic modelling of complex cellular networks under special Consideration of the metabolism of hepatozytes Co-ordinator: Dr. HG Holzhütter

80 We are important for real doctors but not so much in the case of enviromental causes of death or illness tobacco use unhealthy diet physical inactivity excessive alcohol use trauma and exposure to environmental toxins. infections? But...

81 We are important for real doctors (and researcher) forever in the case of renewable (evolving) diseases cancer (evolution to immortal cells) immune diseases (autoimmunity, allergic diseases..) infectious diseases (evolution of viruses and bacteria) mendelian diseases ((new) diseases in human evolution) and in therapies tailored for individuals and as fighters against data massifs!

82 Be carefull with -OMICS because the alignment shows:...genomics..proteomics \ METABOLOMICS...COMICS

83 Schluss!