Protein structure prediction: the customer view [email protected]

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Transcript of Protein structure prediction: the customer view [email protected]

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Slide 2 Protein structure prediction: the customer view [email protected] Slide 3 Protein structure prediction: why Slide 4 Predicting: Expected quality of a model (QMode 1) Expected error on residue C (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 Slide 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 Slide 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 Slide 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 Slide 8 Cozzetto et al., Proteins 2007 Protein structure Quality prediction: The casp initiative Slide 9 Protein structure modelling: A digression Slide 10 Protein structure modelling: Expected accuracy Cozzetto and Tramontano, Proteins 2004 Slide 11 Maistas: taking splicing into account Slide 12 Maistas: taking splicing into account http://www.bioinformatica.crs4.org Slide 13 Maistas: taking splicing into account Slide 14 ANTIBODIES: A different story Slide 15 . ANTIBODIES: A different story Slide 16 ANTIBODIES: A different story Slide 17 91 92 93 94 95 96 90 * * Y Q S L P Y Q 91 92 93 94 95 96 90 * * W T Y P L I Q ANTIBODIES: A different story Chothia et al., Nature 1989 Slide 18 Canonical structures for the torso of H3: 94R 101D 94 non R or 101 non D 103 94 101 103 94 101 Morea et al., JMB., 1998 ANTIBODIES: A different story Slide 19 target sequence BLAST Align VL template TL Build framework ANTIBODIES: A different story Slide 20 ANTIBODIES: A different story target sequence Build framework Align BLAST VL template TL Slide 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 Slide 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 Slide 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 Slide 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 Slide 25 Same antibody Same antibody and canonical structures Same canonical structures Best Vl and Vh ANTIBODIES: A different story Slide 26 Slide 27 Slide 28 Slide 29 ANTIBODIES: A different story ? Slide 30 ANTIBODIES: A different story Slide 31 ANTIBODIES: A different story AVACFATG AFGTARAS DFEARTAS ADFAERAY HGTARYAP LSVNTERAT .. ADFAERAY LDFNMRSY PDFHGRTY AEFKLLSY Slide 32 ANTIBODIES: A different story Slide 33 ANTIBODIES: A different story Slide 34 ANTIBODIES: A different story Slide 35 ANTIBODIES: A different story ANTIBODIES: A different story Slide 36 ANTIBODIES: A different story PDB Slide 37 ANTIBODIES: A different story Slide 38 ANTIBODIES: A different story Slide 39 Slide 40 ANTIBODIES: A different story ? Slide 41 acknowledgements Giuliana Brunetti Enrico Capobianco Simone Carcangiu Alberto de la Fuente Matteo Floris Elisabetta Marras Jol Masciocchi Elisabetta Muscas Massimiliano Orsini Enrico Pieroni Frdric Reinier Patricia Rodriguez Tome Alphonse Thanaraj Thangavel Maria Valentini Tiziana Castrignan 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 Slide 42 Advertisements: http://www.eccb08.org Slide 43 Advertisements: http://predictioncenter.org 8 8 th Cagliari, Sardinia Italy Sometimes early December 2008