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Applications of Homology Modeling

Applications of Homology Modeling. Hanka Venselaar. This seminar…. Homology Modeling… What? Why? When? How? And a few real world examples…. EEC syndrome. No structure:. ?. Sequence:.

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Applications of Homology Modeling

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  1. Applications of Homology Modeling Hanka Venselaar

  2. This seminar…. Homology Modeling… • What? • Why? • When? • How? • And a few real world examples….

  3. EEC syndrome No structure: ? Sequence: MSQSTQTNEFLSPEVFQHIWDFLEQPICSVQPIDLNFVDEPSEDGATNKIEISMDCIRMQDSDLSDMWPQYTNLGLLNSMDQQIQNGSSSTSPYNTDHAQNSVTAPSPYAQPSSTFDALSPSPAIPSNTDYPGPHSFDVSFQQSSTAKSATWTYSTELKKLYCQIAKTCPIQIKVMTPPPQGAVIRAMPVYKKAEHVTEVVKRCPNHELSREFNEGQIAPPSHLIRVEGNSHAQYVEDPITGRQSVLVPYEPPQVGTEFTTVLYNFMCNSSCVGGMNRRPILIIVTLETRDGQVLGRRCFEARICACPGRDRKADEDSIRKQQVSDSTKNGDGTKRPFRQNTHGIQMTSIKKRRSPDDELLYLPVRGRETYEMLLKIKESLELMQYLPQHTIETYRQQQQQQHQHLLQKQTSIQSPSSYGNSSPPLNKMNSMNKLPSVSQLINPQQRNALTPTTIPDGMGANIPMMGTHMPMAGDMNGLSPTQALPPPLSMPSTSHCTPPPPYPTDCSIVSFLARLGCSSCLDYFTTQGLTTIYQIEHYSMDDLASLKIPEQFRHAIWKGILDHRQLHEFSSPSHLLRTPSSASTVSVGSSETRGERVIDAVRFTLRQTISFPPRDEWNDFNFDMDARRNKQQRIKEEGE EEC syndrome

  4. Homology modeling in short… Prediction of structure based upon a highly similar structure • 2 basic assumptions: • Structure defines function • During evolution structures are more conserved than sequence Use one structure to predict another

  5. Homology modeling % identity * O # residues * Actually, modelling is possible, but we cannot get an alignment… Example: by 80 residues  30% identity sufficient

  6. NSDSECPLSHDG || || | || NSYPGCPSSYDG NSDSECPLSHDG ? Model sequence Unknown structure Known structure Back bone copied Homology modeling in short… Prediction of structure based upon a highly similar structure Model! Copy backbone and conserved residues Add sidechains, Molecular Dynamics simulation on model Known structure

  7. The 8 steps of Homology modeling

  8. 1: Template recognition and initial alignment

  9. NSDSECPLSHDGYCLHDGVC || || | ||||| ||| NSYPGCPSSYDGYCLNGGVC 1: Template recognition and initial alignment • BLAST your sequence against PDB • Best hit  normally template • Initial alignment 

  10. 2: Alignment correction 1: Template recognition and initial alignment

  11. CPISRTAAS-FRCW CPISRTG-SMFRCW CPISRTA--TFRCW CPISRTAASHFRCW CPISRTGASIFRCW CPISRTA---FRCW CPISRTGASIFRCW CPISRTGASIFRCW CPISRTA---FRCW CPISRT---AFRCW Correct alignment 2: Alignment correction • Functional residues  conserved • Use multiple sequence alignments • Deletions  shift gaps Multipe sequence alignment  Sequence with known structure Your sequence Both are possible

  12. E I E E V V A P C C C S R R M R G L M P P 2: Alignment correction -A-V F-D- • Core residues  conserved • Use multiple sequence alignments • Deletions in your sequence  shift gaps Known structure FDICRLPGSAEAV Model FNVCRMP---EAI Model FNVCR---MPEAI  Correct alignment

  13. 3: Backbone generation 2: Alignment correction 1: Template recognition and initial alignment

  14. 3: Backbone generation • Making the model…. • Copy backbone of template to model • Make deletions as discussed • (Keep conserved residues)

  15. 4: Loop modeling 2: Alignment correction 1: Template recognition and initial alignment 3: Backbone generation

  16. 4: Loop modeling Known structure GVCMYIEA---LDKYACNC Your sequence GECFMVKDLSNPSRYLCKC Loop library, try different options

  17. 5: Sidechain modeling 2: Alignment correction 1: Template recognition and initial alignment 3: Backbone generation 4: Loop modeling

  18. 5: Side-chain modeling • Several options • Libraries of preferred rotamers based upon backbone conformation

  19. 6: Model optimization 2: Alignment correction 1: Template recognition and initial alignment 3: Backbone generation 4: Loop modeling 5: Sidechain modeling

  20. 6: Model optimization • Molecular dynamics simulation • Remove big errors • Structure moves to lowest energy conformation

  21. 2: Alignment correction 1: Template recognition and initial alignment 3: Backbone generation 4: Loop modeling 5: Sidechain modeling 7: Model validation 6: Model optimization

  22. 7: Model Validation • Second opinion by PDBreport /WHATIF • Errors in active site?  new alignment/ template • No errors?  Model!

  23. 2: Alignment correction 1: Template recognition and initial alignment 3: Backbone generation 4: Loop modeling 8: Iteration 8: Iteration 5: Sidechain modeling 8: Iteration 8: Iteration 7: Model validation 6: Model optimization

  24. 2: Alignment correction 1: Template recognition and initial alignment 3: Backbone generation 4: Loop modeling 8: Iteration 8: Iteration 5: Sidechain modeling Model! 8: Iteration 8: Iteration 7: Model validation 6: Model optimization

  25. Alignment Modeling Correction 8 steps of homology modeling 1: Template recognition and initial alignment 2: Alignment correction 3: Backbone generation 4: Loop modeling 5: Side-chain modeling 6: Model optimization 7: Model validation 8: Iteration

  26. EEC syndrome Structure! P63 MSQSTQTNEFLSPEVFQHIWDFLEQPICSVQPIDLNFVDEPSEDGATNKIEISMDCIRMQDSDLSDMWPQYTNLGLLNSMDQQIQNGSSSTSPYNTDHAQNSVTAPSPYAQPSSTFDALSPSPAIPSNTDYPGPHSFDVSFQQSSTAKSATWTYSTELKKLYCQIAKTCPIQIKVMTPPPQGAVIRAMPVYKKAEHVTEVVKRCPNHELSREFNEGQIAPPSHLIRVEGNSHAQYVEDPITGRQSVLVPYEPPQVGTEFTTVLYNFMCNSSCVGGMNRRPILIIVTLETRDGQVLGRRCFEARICACPGRDRKADEDSIRKQQVSDSTKNGDGTKRPFRQNTHGIQMTSIKKRRSPDDELLYLPVRGRETYEMLLKIKESLELMQYLPQHTIETYRQQQQQQHQHLLQKQTSIQSPSSYGNSSPPLNKMNSMNKLPSVSQLINPQQRNALTPTTIPDGMGANIPMMGTHMPMAGDMNGLSPTQALPPPLSMPSTSHCTPPPPYPTDCSIVSFLARLGCSSCLDYFTTQGLTTIYQIEHYSMDDLASLKIPEQFRHAIWKGILDHRQLHEFSSPSHLLRTPSSASTVSVGSSETRGERVIDAVRFTLRQTISFPPRDEWNDFNFDMDARRNKQQRIKEEGE EEC syndrome

  27. Arginine • Loss of negative charge • Loss of interaction with the DNA Mutation RS Serine

  28. Another real world example: Mutation analysis HFE

  29. Transferrin receptor (dimer) binds iron/transferrin complex HFE – complex: -Signaling and regulation of iron in bloodstream. -Expressed in liver and colon. -Mutations cause iron deposition disease “Hereditary Hemachromatosis“ HFE β2-microglobulin  Facilitates trafficking of HFE to the cellmembrane

  30. Hereditary Hemachromatosis 3 occuring mutations • C280Y • D41H • L161P L161P D41H C280Y

  31. Loss of cystein bridge • Disturbing of β2-microglobulin binding domain • No trafficking to membrane Mutation C260Y

  32. Introduction of additional negative charge • Disturbing of hydrogen bridges • Loss of stability in this area Mutation H41D

  33. Loss hydrophobic interactions • Major disturbance of the helix • Less interaction of the helix with the transferrin receptor Mutation L161P

  34. Seriousness of mutation Seriousness of the disease D41H L161P C260Y D41H L161P C260Y Conclusion: the seriousness of the mutation is related to the seriousness of the disease and can be explained by analyzing the mutations with the 3D structure.

  35. To conclude…. Homology Modeling… • What? Prediction of an unknown structure based on an homologous and known structure • Why? To answer biological and medical questions when the “real” structure is unknown • When? A template with enough identity must be available • How? 8 Steps • Real world examples: mutations in EEC syndrome and HFE can be explained

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