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Protein structure prediction: the customer view

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Presentation on theme: "Protein structure prediction: the customer view"— Presentation transcript:

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2 Protein structure prediction: the customer view

3 Protein structure prediction: why

4 Predicting: Expected quality of a model (QMode 1) Expected error on residue C α (QMode 2) 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. Quoting the CASP web page: Protein structure Quality prediction: The casp initiative

5 Target xxPred Model serv1_1N1 Model serv1_2N2 ………….… Model serv1_5… … Model serv3_4… …. Target yyPred Model serv1_1N1 Model serv1_2N2 ………….… Model serv1_5… … Model serv3_4… …. Target xxGDT Model serv1_1G1 Model serv1_2G2 ………….… Model serv1_5… … Model serv3_4… …. Target yyGDT Model serv1_1G1 Model serv1_2G2 ………….… Model serv1_5… … Model serv3_4… …. Protein structure Quality prediction: The casp initiative

6 Target xxPred Model serv1_1N1 Model serv1_2N2 ………….… Model serv1_5… … Model serv3_4… …. Target yyPred Model serv1_1N1 Model serv1_2N2 ………….… Model serv1_5… … Model serv3_4… …. Target xxGDT Model serv1_1G1 Model serv1_2G2 ………….… Model serv1_5… … Model serv3_4… …. Target yyGDT Model serv1_1G1 Model serv1_2G2 ………….… Model serv1_5… … Model serv3_4… …. Pearson correlation By target Protein structure Quality prediction: The casp initiative

7 Target xxPred Model serv1_1N1 Model serv1_2N2 ………….… Model serv1_5… … Model serv3_4… …. Target yyPred Model serv1_1N1 Model serv1_2N2 ………….… Model serv1_5… … Model serv3_4… …. Target xxGDT Model serv1_1G1 Model serv1_2G2 ………….… Model serv1_5… … Model serv3_4… …. Target yyGDT Model serv1_1G1 Model serv1_2G2 ………….… Model serv1_5… … Model serv3_4… …. Pearson correlation Global Protein structure Quality prediction: The casp initiative

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

9 Protein structure modelling: A digression …

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

11 Maistas: taking splicing into account

12 Maistas: taking splicing into account

13 Maistas: taking splicing into account

14 ANTIBODIES: A different story

15 . ANTIBODIES: A different story

16 ANTIBODIES: A different story

17 * * Y Q S L P Y Q * * W T Y P L I Q ANTIBODIES: A different story Chothia et al., Nature 1989

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

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

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

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

22 Align Ab VL sequenceAb VH sequence BLAST VL template TL VH template TH TL=TH? Fit conserved interface Build template Build framework ANTIBODIES: A different story

23 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 ANTIBODIES: A different story

24 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 ANTIBODIES: A different story

25 Same antibody Same antibody and canonical structures Same canonical structures Best Vl and Vh ANTIBODIES: A different story

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29 ANTIBODIES: A different story ?

30 ANTIBODIES: A different story

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

32 ANTIBODIES: A different story

33 ANTIBODIES: A different story

34 ANTIBODIES: A different story

35 ANTIBODIES: A different story ANTIBODIES: A different story

36 ANTIBODIES: A different story PDB

37 ANTIBODIES: A different story

38 ANTIBODIES: A different story

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40 ANTIBODIES: A different story ?

41 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. DOnorio 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 EU Biosapiens Institut Pasteur-Cenci HFP Regione Sardegna

42 Advertisements:

43 Advertisements: 8 8 th Cagliari, Sardinia Italy Sometimes early December 2008


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