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Protein structure prediction: the customer view

Protein structure prediction: the customer view. Anna.Tramontano@uniroma1.it. Protein structure prediction: why. Protein structure Quality prediction: The casp initiative. Predicting:. Expected quality of a model (QMode 1) Expected error on residue C α (QMode 2).

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Protein structure prediction: the customer view

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  1. Protein structure prediction: the customer view Anna.Tramontano@uniroma1.it

  2. Protein structure prediction: why

  3. Protein structure Quality prediction: The casp initiative Predicting: • Expected quality of a model (QMode 1) • Expected error on residue Cα (QMode 2) Quoting the CASP web page: You may submit your quality assessment prediction in one of the two different modes:QMODE 1 :   global model quality score (MQS - one number for a model)QMODE 2 :   MQS and error estimate on per-residue basis.

  4. Protein structure Quality prediction: The casp initiative Target xx Pred Model serv1_1 N1 Model serv1_2 N2 …………. … Model serv1_5 … … Model serv3_4 … …. Target xx GDT Model serv1_1 G1 Model serv1_2 G2 …………. … Model serv1_5 … … Model serv3_4 … …. Target yy GDT Model serv1_1 G1 Model serv1_2 G2 …………. … Model serv1_5 … … Model serv3_4 … …. Target yy Pred Model serv1_1 N1 Model serv1_2 N2 …………. … Model serv1_5 … … Model serv3_4 … ….

  5. Protein structure Quality prediction: The casp initiative Target xx Pred Model serv1_1 N1 Model serv1_2 N2 …………. … Model serv1_5 … … Model serv3_4 … …. Target xx GDT Model serv1_1 G1 Model serv1_2 G2 …………. … Model serv1_5 … … Model serv3_4 … …. Pearson correlation Target yy GDT Model serv1_1 G1 Model serv1_2 G2 …………. … Model serv1_5 … … Model serv3_4 … …. Target yy Pred Model serv1_1 N1 Model serv1_2 N2 …………. … Model serv1_5 … … Model serv3_4 … …. By target

  6. Protein structure Quality prediction: The casp initiative Target xx Pred Model serv1_1 N1 Model serv1_2 N2 …………. … Model serv1_5 … … Model serv3_4 … …. Target xx GDT Model serv1_1 G1 Model serv1_2 G2 …………. … Model serv1_5 … … Model serv3_4 … …. Target yy GDT Model serv1_1 G1 Model serv1_2 G2 …………. … Model serv1_5 … … Model serv3_4 … …. Target yy Pred Model serv1_1 N1 Model serv1_2 N2 …………. … Model serv1_5 … … Model serv3_4 … …. Global Pearson correlation

  7. Protein structure Quality prediction: The casp initiative Cozzetto et al., Proteins 2007

  8. … Protein structure modelling: A digression

  9. Protein structure modelling: Expected accuracy Cozzetto and Tramontano, Proteins 2004

  10. Maistas: taking splicing into account

  11. Maistas: taking splicing into account http://www.bioinformatica.crs4.org

  12. Maistas: taking splicing into account

  13. ANTIBODIES: A different story

  14. . V V H H V V L L C C H1 H1 C C L L SS C C N H2 H2 C H3 C H1 C H3 H3 H2 L2 Antibody L3 L1 C N Antigen binding site ANTIBODIES: A different story

  15. ANTIBODIES: A different story

  16. 94 Pro 95 Pro 90 Gln ANTIBODIES: A different story 91 92 93 94 95 96 90 91 92 93 94 95 96 90 * * * * Y Q S L P Y Q W T Y P L I Q Chothia et al., Nature 1989

  17. ANTIBODIES: A different story Canonical structures for the ‘torso’ of H3: 94R – 101D 101 101 94 94 103 103 94 non R or 101 non D Morea et al., JMB., 1998

  18. ANTIBODIES: A different story target sequence BLAST VL template TL Align Build framework

  19. BLAST VL template TL Align Build framework ANTIBODIES: A different story target sequence

  20. Ab VL sequence Ab VH sequence “BLAST” VL template TL VH template TH “Align” TL=TH? Build framework Fit conserved interface Build template ANTIBODIES: A different story target sequence BLAST template Align Build framework

  21. Ab VL sequence Ab VH sequence “BLAST” VL template TL VH template TH TL=TH? Build framework Fit conserved interface Build template ANTIBODIES: A different story “Align”

  22. ANTIBODIES: A different story Taking the frameworks from different structures introduces errors One might be better off selecting the same template, at the cost of loosing in sequence identity

  23. ANTIBODIES: A different story Taking the loops from different structures introduces errors One might be better off selecting a template with the right CS, at the cost of loosing in sequence identity

  24. ANTIBODIES: A different story • Same antibody • Same antibody and canonical structures • Same canonical structures • Best Vl and Vh

  25. ANTIBODIES: A different story ?

  26. ANTIBODIES: A different story

  27. ANTIBODIES: A different story AVACFATG AFGTARAS DFEARTAS ADFAERAY HGTARYAP LSVNTERAT ….. ADFAERAY LDFNMRSY PDFHGRTY AEFKLLSY

  28. ANTIBODIES: A different story

  29. ANTIBODIES: A different story

  30. ANTIBODIES: A different story

  31. ANTIBODIES: A different story ANTIBODIES: A different story

  32. ANTIBODIES: A different story PDB

  33. ANTIBODIES: A different story

  34. ANTIBODIES: A different story

  35. ANTIBODIES: A different story ?

  36. acknowledgements Giuliana Brunetti Enrico Capobianco Simone Carcangiu Alberto de la Fuente Matteo Floris Elisabetta Marras Joël Masciocchi Elisabetta Muscas Massimiliano Orsini Enrico Pieroni Frédéric Reinier Patricia Rodriguez Tome’ Alphonse Thanaraj Thangavel Maria Valentini Tiziana Castrignanò P. D’Onorio De Meo Danilo Carrabino Domenico Cozzetto Enrico Ferraro Fabrizio Ferre’ Emanuela Giombini Alejandro Giorgetti Paolo Marcatili Domenico Raimondo Stefania Bosi Claudia Bertonati Alessandra Godi Michele Ceriani Romina Oliva Claudia Bonaccini Marialuisa Pellegrini Simonetta Soro EU Biosapiens Institut Pasteur-Cenci HFP Regione Sardegna

  37. Advertisements: http://www.eccb08.org

  38. Advertisements: http://predictioncenter.org 8th Cagliari, Sardinia Italy Sometimes early December 2008 8

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