Strukturna biologija, bioinformatika, biologija sistema

1. Strukturna biologija, bioinformatika, biologija sistema biologija 21-og veka

2. Danasnja presentacija bice podeljena u tri dela: • Pozadina i opsti uvod • NMR • Rentgenska kristalografija • Strukturna biologija – primeri iz moje laboratorije 3. Poseban osvrt na bioinformatiku i biologiju sistema kao interdisciplinarne grane relvantne za kompiuterske nauke

3. Structural biology Human & other genome sequences Functionally cloned DNA molecules coding for proteins of interest. Bioinformatics Amino acid sequences Protein function Protein structure Protein chemistry / yeast 2-hybrid screens / proteomics / enzymology / genetics / transgenes / knock-outs / knock-ins / chemical genetics / etc.

4. 3D structures of molecules allow us to understand biological processes at the most basic level. We can ‘see’ which molecules interact, how they interact, how they function, how drugs act. They can help us understand disease at an atomic level. 3D structures can be exploited in development of new drugs. structure-based drug design

5. Strukturna Biologija • Struktura moze ponekad da odkrije funkciju proteina direktno • Struktura moza da racionalizuje eksperimentalnu obzervaciju o selktivitetu i specificnosti enzimaticne reakcije • Struktura moze da postane osnova za rational drug/inhibitor discovery. • Struktura moze da razotkrije dinamicki aspekt proteinskog ponasanja. • Trodimenzionalne topologije polipeptida obezbedjuju podatke za resavanje problema formiranja proteinske strukture -- ‘protein folding problem’. • [Sometimes a 3D structure can be rather uninformative - the ‘structural genomics’ debate.]

7. Experimental modes of molecular structural biology X-ray crystallography Protein crystals (3-50 mgs/ml; ca. 100 ml) [Se-methionine labelling] X-ray source/-Synchrotron Applicable to proteins of any size (in principle). NMR spectroscopy Protein solutions (> 0.5 mM; min. volume 0.3ml; 10-100 mg) 15N,13C-Isotope labelling NMR Spectrometer Applicable to small(ish) proteins (smaller than ca. 30,000 MW) Cryo-electron microscopy Macromolecular assemblies/particles frozen in vitreous ice Electron microscope Large particles, typically > 500,000 MW ‘Low’ resolution High resolution Medium resolution

8. 2 mm 200 mm 20 mm 200 nm 20 nm 2 nm 0.2 nm x 10 x 10 x 10 x 10 x 10 x 10 The sizes of cells and of their component parts Unaided eye Light microscope Electron microscope CELLS MOLECULES ORGANELLES ATOMS 1 m = 103 mm = 106mm = 109 nm

9. STA JE NMR? Nuclear Magnetic Resonance (NMR) je mocna spektroskopska tehnika koja pruza informaciju o strukturnim i hemijskim osobinama molekula. NMR je ne-destruktivna metoda za analizu strukture i dinamike molekula. NMR koristi osobine odredjenih atoma kada su izlozeni vrlo jakom magnetnom polju. For biochemists these are mainly 1H, 15N, 13C and 31P.1H and 31P are highly abundant isotopes whilst 15N and 13C are present at only low levels < 1%. Studies using these nuclei generally require isotopic enrichment by production of the molecule from media that has been enriched in these isotopes.

10. Prof. Kurt Wüthrich Nobel Prize for Chemistry 2002

11. Typically the magnets used in NMR spectroscopy are 10,000-15,000 times stronger than the earth’s magnetic field. The NMR experiment generally consists of applying short bursts or pulses of energy in the radio frequency (RF) range, typically 40-800 MHz, to the sample. These pulses of RF cause the nuclei to rotate away from their equilibrium position and they start to precess (rotate) around the axis of the magnetic field. The exact frequency at which the nuclei precess is related to both the chemical and physical environment of the atom in the molecule. By using different combinations of RF pulses and delays it is possible to determine how each atom in the molecule interacts with other atoms in the molecule.

12. 15N(ppm) 1H(ppm)

14. The NMR spectrum is exquisitely sensitive to the conformation of the polypeptide chain, and to the presence of interacting chemical ligands. These and other features of the rich ‘spin physics’ that underlies the NMR phenomenon mean that NMR spectroscopy is a highly versatile tool for the characterisation of: StructureDynamicsMolecular interactions

15. C C C a5 a2 a4 N N N a1 a6 a3 Harris et al. (2004) J. Mol. Biol.

16. C C E676 N E667 D709 N a3 a5 E664 a4 a2 a4 E700 a6 E699 a1 E652 Harris et al. (2004) J. Mol. Biol.

17. X-ray Crystallography • - An experimental technique involving diffraction of X-rays by crystalline material. • X-ray wavelength ~ Å • Based on the diffraction pattern, electron density of the molecule could be reconstructed. (Need intensities and phases) • Model is built in the reconstructed electron-density • Model – the molecular picture – molecular structure from global folds to atomic details • Limited information about the molecule’s dynamic • Depends on obtaining crystals

18. Why X-rays? • Why electron density? • Why crystals?

19. COMPUTED ELECTRON-DENSITY MAP EYEPIECE LENS magnification n CRYSTALLOGRAPHER Scattered radiation PHASES COMPUTER OBJECTIVE LENS magnification m DETECTOR Scattered radiation OBJECT OBJECT (crystal) VISIBLE LIGHT X-RAYS Enlarged image of object Magnification mn

20. Pregled procesa odredjivanja strukture proteina koriscenjem difrakcije X zraka • Proizvodnja izolovanog dovoljno velikog kristala kandidat proteina • Postavljanje kristala, prikupljanje i evaluacija preliminarnih difrakcionih podataka • Kompletno prikupljanje podataka i procena fazi • Izgradnja i rafiniranje proteinskih lanaca • Validacija strukture

22. European Synchrotron Radiation Facility (Grenoble, France)

23. Structural characterisation of drug-targets from M.tuberculosis Institute of Structural Molecular Biology Snezana Djordjevic

24. M. tuberculosis • 2-3 million deaths from tuberculosis annually • 1/3 of world population currently infected with the disease • Drug resistance -multidrug-resistant strains -12.6 % M. tuberculosis isolates resistant to at least one drug -2.2 % resistant to both isonazid and rifampin

25. New Drugs -agents that exhibit activity against drug resistant strains -completely sterilize infection -shorten the duration of drug therapy and thus promote drug compliance

26. METRO – 06/03/2007

27. Mechanism of resistance to Isoniazid -Isoniazid is a prodrug that is oxidized by KatG -KatG is catalase-peroxidase -Mutation of the KatG leads to resistance KatG Prodrug activation Resistance

28. AhpC AhpD KatG activity is important for virulence ! -Physiological function of the KatG includes protection of the mycobacterium against H2O2 and other ROS produced by the microbe and its host. ? KatG

29. AhpD Alkylhydroperoxidase From M. tuberculousis Paul Ortiz de Montellano Dept. of Pharmaceutical Chemistry, UCSF C2; a=186.38 Å, b=117.28 Å, c=88.99 Å, b=113.97° 177 residues/monomer

30. Structure solution: SeMet/MAD 4 wavelengths data collected in Grenoble 1.9 (1.7) Å resolution 2Fo-Fc map

31. a7 a6 a5 a3 a8 N a4 C C a2 a1 N AhpD Monomer Topology From structure to function and the catalytic mechanism CXXC Peroxiredoxins Thioredoxins -solvent exposed -pKa ~ 7.1

32. Cys130 Cys133 His137 Glu118

33. Putative substrate binding site Cys133

34. NADH NAD+ Lpd(ox) Lpd(red) DlaT-LpH2 DlaT-Lp AhpD(ox) AhpD(red) AhpC(red) AhpC(ox) ROOH ROH Novel redox pathway in M. tuberculosis E3 E2 Lpd: Dihydrolipoamide dehydrogenase SucB: Dihydrolipoamide acyltransferase Components of pyruvate dehydrogenase complexes Pyruvate Acetyl-CoA + CO2 NAD+ NADH

35. Molecular Surface

36. A Prototypical Two-Component Signal Transduction System Periplasmic Space P External Stimulus Response Histidine Kinase (HK) Sensory Protein Kinase Core Receptor / input / sensor domain Response Regulator (RR)

37. SAM B Chemotaxis P Tar -CH3 +CH3 R W W A A +ATP P P Y B

38. DosS • Induced by exposure to hypoxia, NO and ethanol. • Structural studies have been initiated with the aim of describing the signalling mechanism that leads to histidine kinase activation. • Histidine kinase domain (HK) undergoes autophosphorylation and can carry out a Mg2+ dependant phosphotransfer reaction onto DosR. • DosS : DosR are a cognate sensor-regulator pair.

39. Identification of domain boundaries

40. Further structural investigation of GAF domains a2 b1 b2 Secondary Structure: 1MC0 PDE2A_B 196 DVSVLLQEIITEARN-------LSNAEICSVFLLDQ------------NELVAKVFDGGVVDDe----sY DosSGAF_A 3 DLEATLRAIVHSATS-------LVDARYGAMEVHDRQH---------RVLHFVYEGIDEETVR------R cGMP PDE_1 154 DVTALCHKIFLHIHG-------LISADRYSLFLVCEdss-------ndKFLISRLFDVAEGSTleeasnN cGMP PDE_2 336 SLEVILKKIAATIIS-------FMQVQKCTIFIVDEdcsdsf-ssvfhMECEELEKSSDTLTR------E anfA 46 DLADALSIVLGVMQQ-------HLKMQRGIVTLYDMr----------aETIFIHDSFGLTEEEk-----K cGMP PDE_3 228 DATSLQLKVLRYLQQ-------ETQATHCCLLLVSEd----------nLQLSCKVIGEKVLG-------E ADEN_CYCL_1 79 GFENILQEMLQSITLkt---geLLGADRTTIFLLDEe----------kQELWSIVAAGEGDRS------L ADEN_CYCL_2 271 DLEDTLKRVMDEAKE-------LMNADRSTLWLIDRd----------rHELWTKITQDNGST-------K yebR 27 DLNRDFNALMAGETS-------FLATLANTSALLYErlt-------diNWAGFYLLEDDTLVLg----pF Hypoth. Pro. 54 LIKATLQKTMEASIH-------QTGAQLGSLFLLDGd----------gRVTESILARGATDQSqk---kN Nif-regul_1 68 RLEVTLANVVNVLSS-------MLQMRHGMICILDSe-----------GDPDMVATTGWTPEMa-----G Nif-regul_2 46 RLEVTLANVLGLLQS-------FVQMRHGLVSLFNDd-----------GVPELTVGAGWSEG-------T Nif-regul_3 35 NTARALAAILEVLHD-------HAFMQYGMVCLFDKe----------rNALFVESLHGIDGERkk--etR Nif-regul_4 21 DLSKTLREVLNVLSA-------HLETKRVLLSLMQDs-----------GELQLVSAIGLSYEEf-----Q consensus 1 DLEELLQTILEELRQ-------LLGADRVSIYLVDEDK---------RGELVLVASDGLTLPE------L a3 b3 b4 b5 a4 PDE2A_BEIRIPADQ-----GIAGHVATTGQILNIP-DAYAHPl--fYRGVDDSTGFR-----TRNILCFPIKNEn- DosSGAF_AIGHLPKGL-----GVIGLLIEDPKPLRLD-DVSAHP----AS-IGFPPYHPP----MRTFLGVPVRVR-- cGMP PDE_1 CIRLEWNK-----GIVGHVAAFGEPLNIK-DAYEDPr--fNAEVDQITGYK-----TQSILCMPIKNHr- cGMP PDE_2 RDANRINY-----MYAQYVKNTMEPLNIP-DVSKDKr---FPWTNENMGNInq-qcIRSLLCTPIKNGk- anfA RGIYAVGE-----GITGKVVETGKAIVAR-RLQEHP-----DFLGRTRVSRng-kaKAAFFCVPIMRA-- cGMP PDE_3 EVSFPLTM-----GRLGQVVEDKQCIQLK-DLTSDD----VQQLQNMLGCE-----LRAMLCVPVISRa- ADEN_CYCL_1 EIRIPADK-----GIAGEVATFKQVVNIPfDFYHDPrsifAQKQEKITGYR-----TYTMLALPLLSEq- ADEN_CYCL_2 ELRVPIGK-----GFAGIVAASGQKLNIPfDLYDHPdsatAKQIDQQNGYR-----TCSLLCMPVFNGd- yebR QGKIACVRipvgrGVCGTAVARNQVQRIE-DVHVFD-------GHIACDAA-----SNSEIVLPLVVK-- Hypoth. Pro. IVGQVLDK-----GLAGWVRENKRTGLIN-DTTKDY----RWLKLPDEPYQ-----ALSALGVPIVWG-- Nif-regul_1 QIRAHVPQ-----KAIDQIVATQMPLVVQ-DVTADP-----LFAGHEDLFGppeeaTVSFIGVPIKAD-- Nif-regul_2 DERYRTCVp---qKAIHEIVATGRSLMVE-NVAAEt---aFSAADREVLGAsd-siPVAFIGVPIRVD-- Nif-regul_3 HVRYRMGE-----GVIGAVMSQRQALVLP-RISDDQ-----RFLDRLNIYDy----SLPLIGVPIPGAd- Nif-regul_4 SGRYRVGE-----GITGKIFQTETPIVVR-DLAQEP-----LFLARTSPRQsqdgeVISFVGVPIKAA-- consensusGVRFPLDE-----GLVGRVAETGRPLVIP-DVEADP----FFFLDLLQRYQL----IRSFLAVPLVAG--

41. a5 b6 Secondary Structure|1MC0 PDE2A_B -QEVIGVAELVNK-------------------INGPWFSKFDEDLATAFSIYCGISIAHSLLYKKVN 345 DosSGAF_A-DESFGTLYLTDK-------------------TNGQPFSDDDEvlvqalaaaagiavanarlyqqak 150 cGMP PDE_1 -EEVVGVAQAINKk-----------------sGNGGTFTEKDEKDFAAYLAFCGIVLHNAQLYETSL 314 cGMP PDE_2 kNKVIGVCQLVNKmee--------------ttGKVKAFNRNDEQFLEAFVIFCGLGIQNTQMYEAVE 503 anfA -QKVLGTIAAERV-------------------YMNPRLLKQDVELLTMIATMIAPLVELYLIENIER 196 cGMP PDE_3 tDQVVALACAFNK-------------------LGGDFFTDEDERAIQHCFHYTGTVLTSTLAFQKEQ 375 ADEN_CYCL_1 -GRLVAVVQLLNKlkpyspp-----dallaerIDNQGFTSADEQLFQEFAPSIRLILESSRSFYIAT 249 ADEN_CYCL_2 -QELIGVTQLVNKkktgefppynpetwpiapeCFQASFDRNDEEFMEAFNIQAGVALQNAQLFATVK 441 yebR -NQIIGVLDIDST--------------------VFGRFTDEDEQGLRQLVAQLEKVLATTDYKKFFA 179 Hypoth. Pro. -DELLGILTLMHS--------------------QVNHFTPACATAMEKTAELIALVLNNARIQTKHK 202 Nif-regul_1 -HHVMGTLSIDRIw-----------------dGTARFRFDEDVRFLTMVANLVGQTVRLHKLVASDR 220 Nif-regul_2 -STVVGTLTIDRIp------------------EGSSSLLEYDARLLAMVANVIGQTIKLHRLFAGDR 198 Nif-regul_3 -NQPAGVLVAQPM-------------------ALHEDRLAASTRFLEMVANLISQPLRSATPPESLP 186 Nif-regul_4 -REMLGVLCVFRDg------------------QSPSRSVDHEVRLLTMVANLIGQTVRLYRSVAAER 180 consensus-GELLGVLALHRK-------------------DSPRPFTEEEEELLQALANQLAIALALAQLYEELR • SAMt99 : to detect remote structural homologues of this protein. • From the 11149 sequence homologies identified, 24 had a known structure but none of those identified produced significant global alignment. • Local alignments covered either the C or N terminal regions. No alignment was found that covered both putative GAF domains. • 1 structural homologue was identified for DosS GAF A domain : 1MC0

42. CO / NO / O2 Fe2+ His UV-Visible Characterisation of GAF A Haem Absorption spectra of DosS GAF A Absorption spectra of Haemoglobin

43. Visible/UV spectrum of the DosS GAF A (63-210) histidine to alanine mutants

44. Fe2+ P P The Model of Signalling O2 Fe2+ OFF A B DosR NO ON A B DosR

45. GAF B - NMR 1H, 15N labeled DosS GAF B HSQC NMR experiments: HNCO, HNCA, HN(CO)CA, HNCACB, CBCA(CO)NH, HA(CA)NH and HA(CACO)NH were obtained at 1H frequency of 500MHz on a 0.6mM [1H, 13C, 15N]-labelled DosS 231-379, pH6, 20mM phosphate, 100mM NaCl.

46. PROBLEMS: • 48 residues are still to be assigned • 21 expected cross-peaks are missing from the spectrum. • Sekharan MR, Rajagopal et al. 2005. Backbone 1H, 13C, and 15N resonance assignment of the 46 kDa dimeric GAF A domain of phosphodiesterase 5 J Biomol NMR. 33(1):75 • Some of the cross-peaks do not form one peak but multiple peaks. • High content of Val, Leu and Ala residues in the sequence. GAF B - NMR Predicted secondary structure for DosS GAF 2 using PSIPRED.

47. Signalling mechanism N C

48. STRUCTURAL GENOMICS CENTRES IN NORTH AMERICA, UK, FRANCE, JAPAN • OXFORD STRUCTURAL GENOMICS • Announced in 2003, with operations commencing in July 2004 for an initial three-year period, this initiative received funding from Canadian, Swedish and British sponsors from both the public and private sectors. For the second phase, July 2007, over £49 million is being made from public funding agencies in Canada, Sweden and Ontario, charitable foundations in the UK and Sweden, GlaxoSmithKline plc, Novartis and Merck. Laboratories at the University of Oxford , University of Toronto and Karolinska Institutet, Stockholm.

49. BIOINFORMATIKA U toku poslednjih nekoliko dekada, napredak u molekularnoj biologiji, zajedno sa progresom u genetskoj tehnologiji doveo je do eksplozije u kolicini informacija stvorenih u naucnoj zajednici. Pojava te mase informacija proizvela je potrebu i zahtev za kompiuterizovanim bankama podataka (databases) da bi se cuvali, organizovali i katalogovali podaci. Pritom neophodno je bilo razviti sredstva (tools) za pregled, vizualizaciju i analizu tih podataka.   

50. Computational biology(sam proces analize i interpretacije podataka) • Razvoj i primena alatki (tools) koji omogucavaju pristup, upotrebu i organizaciju raznih informacija • Razvoj novih algoritma i statistike sa kojima se mogu proceniti relazije medju komponentama u velikoj grupi podataka. Na primer metode za lociranje gene u okviru sekvence, predvidjanje strukture proteina/funkcije, i grupisanje proteinskih sekvenci u familije povezanih (related) slicnih sekvenci.