predikce trojrozměrných struktur proteinůspiwokv/modelovani/...predikce struktury biomolekul:...

Predikce trojrozměrných struktur proteinů

Vojtěch [email protected]Ústav biochemie a mikrobiologieVŠCHT, Praha

http://web.vscht.cz/spiwokv/http://www.metadynamics.cz

mailto:[email protected]://web.vscht.cz/spiwokv/http://www.metadynamics.cz/

Struktury biomolekul:

Studium toho jak proteiny fungují


www.rcsb.org cca 170 000 prostorových struktur biomolekul (hlavně proteinů)

PyMol

UCSFChimera

VMD

http://www.rcsb.org/


Návrh léčiv

4Q5M


Roentgenová strukturní krystalografie


Nukleární magnetická rezonance


CryoEM

Predikce struktury biomolekul:

Swiss model (https://swissmodel.expasy.org/)

https://swissmodel.expasy.org/

Abl (1IEP) Lck (2PL0)


Homologní modelování

>LckGSHMQTQKPQKPWWEDEWEVPRETLKLVERLGAGQFGEVWMGYYNGHTKVAVKSLKQGSMSPDAFLAEANLMKQLQHQRLVRLYAVVTQEPIYIITEYMENGSLVDFLKTPSGIKLTINKLLDMAAQIAEGMAFIEERNYIHRDLRAANILVSDTLSCKIADFGLARLIEDNEYTAREGAKFPIKWTAPEAINYGTFTIKSDVWSFGILLTEIVTHGRIPYPGMTNPEVIQNLERGYRMVRPDNCPEELYQLMRLCWKERPEDRPTFDYLRSVLEDFFTATEGQYQPQP

Identita 48 %Query 16 DEWEVPRETLKLVERLGAGQFGEVWMGYYNGHT-KVAVKSLKQGSMSPDAFLAEANLMKQ 74 D+WE+ R + + +LG GQ+GEV+ G + ++ VAVK+LK+ +M + FL EA +MK+Sbjct 6 DKWEMERTDITMKHKLGGGQYGEVYEGVWKKYSLTVAVKTLKEDTMEVEEFLKEAAVMKE 65

Query 75 LQHQRLVRLYAVVTQEP-IYIITEYMENGSLVDFLKTPSGIKLTINKLLDMAAQIAEGMA 133 ++H LV+L V T+EP YIITE+M G+L+D+L+ + ++ LL MA QI+ M Sbjct 66 IKHPNLVQLLGVCTREPPFYIITEFMTYGNLLDYLRECNRQEVNAVVLLYMATQISSAME 125

Query 134 FIEERNYIHRDLRAANILVSDTLSCKIADFGLARLIEDNEYTAREGAKFPIKWTAPEAIN 193 ++E++N+IHRDL A N LV + K+ADFGL+RL+ + YTA GAKFPIKWTAPE++ Sbjct 126 YLEKKNFIHRDLAARNCLVGENHLVKVADFGLSRLMTGDTYTAHAGAKFPIKWTAPESLA 185

Query 194 YGTFTIKSDVWSFGILLTEIVTHGRIPYPGMTNPEVIQNLERGYRMVRPDNCPEELYQLM 253 Y F+IKSDVW+FG+LL EI T+G PYPG+ +V + LE+ YRM RP+ CPE++Y+LMSbjct 186 YNKFSIKSDVWAFGVLLWEIATYGMSPYPGIDLSQVYELLEKDYRMERPEGCPEKVYELM 245

Query 254 RLCWKERPEDRPTFDYLRSVLEDFF 278 R CW+ P DRP+F + E FSbjct 246 RACWQWNPSDRPSFAEIHQAFETMF 270



Lck AVVTQEP-IYIITEY V T+EP YIITE+Abl GVCTREPPFYIITEF



C; A sample alignment in the PIR format; used in tutorial

>P1;1IEPstructureX:1IEP:233 :A:498 :A::::---------------DKWEMERTDITMKHKLGGGQYGEVYEGVWKKYSLTVAVKTLKEDTMEVEEFLKEAAVMKEIKHPNLVQLLGVCTREPPFYIITEFMTYGNLLDYLRECNRQEVSAVVLLYMATQISSAMEYLEKKNFIHRDLAARNCLVGENHLVKVADFGLSRLMTGDTYTAHAGAKFPIKWTAPESLAYNKFSIKSDVWAFGVLLWEIATYGMSPYPGIDLSQVYELLEKDYRMERPEGCPEKVYELMRACWQWNPSDRPSFAEIHQAFETMFQ*

>P1;lcksequence:lck:1 : :@ : ::::---------------DEWEVPRETLKLVERLGAGQFGEVWMGYYNGHT-KVAVKSLKQGSMSPDAFLAEANLMKQLQHQRLVRLYAVVTQEP-IYIITEYMENGSLVDFLKTPSGIKLTINKLLDMAAQIAEGMAFIEERNYIHRDLRAANILVSDTLSCKIADFGLARLIEDNEYTAREGAKFPIKWTAPEAINYGTFTIKSDVWSFGILLTEIVTHGRIPYPGMTNPEVIQNLERGYRMVRPDNCPEELYQLMRLCWKERPEDRPTFDYLRSVLEDFFT*



Abl (1IEP) Lck (model) Lck (2PL0)




Homologní modelování – modeller

alignment.aliC; A sample alignment in the PIR format; used in tutorial

>P1;1IEPstructureX:1IEP:233 :A:498 :A::::---------------DKWEMERTDITMKHKLGGGQYGEVYEGVWKKYSLTVAVKTLKEDTMEVEEFLKEAAVMKEIKHPNLVQLLGVCTREPPFYIITEFMTYGNLLDYLRECNRQEVSAVVLLYMATQISSAMEYLEKKNFIHRDLAARNCLVGENHLVKVADFGLSRLMTGDTYTAHAGAKFPIKWTAPESLAYNKFSIKSDVWAFGVLLWEIATYGMSPYPGIDLSQVYELLEKDYRMERPEGCPEKVYELMRACWQWNPSDRPSFAEIHQAFETMFQ*

>P1;lcksequence:lck:1 : :@ : ::::---------------DEWEVPRETLKLVERLGAGQFGEVWMGYYNGHT-KVAVKSLKQGSMSPDAFLAEANLMKQLQHQRLVRLYAVVTQEP-IYIITEYMENGSLVDFLKTPSGIKLTINKLLDMAAQIAEGMAFIEERNYIHRDLRAANILVSDTLSCKIADFGLARLIEDNEYTAREGAKFPIKWTAPEAINYGTFTIKSDVWSFGILLTEIVTHGRIPYPGMTNPEVIQNLERGYRMVRPDNCPEELYQLMRLCWKERPEDRPTFDYLRSVLEDFFT*


Homologní modelování – modeller

model-default.py# Comparative modeling by the automodel classfrom modeller import * # Load standard Modeller classesfrom modeller.automodel import * # Load the automodel class

log.verbose() # request verbose outputenv = environ() # create a new MODELLER environment to build this model in

# directories for input atom filesenv.io.atom_files_directory = ['.', '../atom_files']

a = automodel(env, alnfile = 'alignment.ali', # alignment filename knowns = '1IEP', # codes of the templates sequence = 'lck') # code of the targeta.starting_model= 1 # index of the first modela.ending_model = 1 # index of the last model # (determines how many models to calculate)a.make() # do the actual comparative modeling


Fold recognition – Phyre2 (http://www.sbg.bio.ic.ac.uk/~phyre2/)

http://www.sbg.bio.ic.ac.uk/~phyre2/


Ab initioRosetta (https://www.rosettacommons.org)Foldit (https://fold.it/)


Koevoluce


Strojové učení – Google Alphafold

https://deepmind.com/


Simulace sbalování proteinů

Lindorff-Larsen et al. Science 2011, 334(6055) 517-520.


Shrnutí metod:

Metoda Použití Přesnost

Homologní modelování >30 % identity o něco horší než experiment

Fold recognition existuje protein jakš takšs podobnoustrukturon

Ab initio cokoliv nic moc

Koevoluce cokoliv nic moc (jen kontakty)prosekvenované

Strojové učení uvidíme uvidíme


CASP - https://predictioncenter.org/

https://predictioncenter.org/

Predikce struktury biomolekulárních komplexů

Protein-ligand docking

Glide (Schrodinger LLC),PLANTS, Autodock, Autodock VINA,Gold, Dock, ...

De Graaf et al. J. Med. Chem. 2011, 54(23) 8195-8206.

Protein-protein docking

Haddock

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predikce trojrozměrných struktur proteinůspiwokv/modelovani/...predikce struktury biomolekul:...

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