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Systems biology of cell-signaling systems: It's all about protein-protein interactions

Systems biology of cell-signaling systems: It's all about protein-protein interactions. Jarek Meller Department s of Environmental Health and Biomedical Engineering , University of Cincinnati & Division of Biomedical Informatics, C incinnati Children’s Hospital Research Foundation

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Systems biology of cell-signaling systems: It's all about protein-protein interactions

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  1. Systems biology of cell-signaling systems:It's all about protein-protein interactions Jarek Meller Departments of Environmental Health and Biomedical Engineering, University of Cincinnati & Division of Biomedical Informatics, Cincinnati Children’s Hospital Research Foundation & Department of Informatics, Nicholas Copernicus University Joint work with Rafal Adamczak, Aleksey Porollo, Baoqiang Cao, Mukta Phatak, and Michael Wagner JM - http://folding.chmcc.org

  2. Can We Reliably Predict Interaction Sites from an Unbound Structure without Knowing Interaction Partners? Sequence only-based methods, structure-based approaches (e.g. hydrophobic patches, conserved hot spots), integrating structural and evolutionary info … JM - http://folding.chmcc.org

  3. From Sequence to Structure to Function: Which Residues Are Accessible to Solvent and Interaction Partners? Relative Solvent Accessibility of an amino acid residue in a proteinquantifies the degree of exposure (surface exposed area, SEA) to solvent molecules in relative terms:   RSA = SEA / MAX_SEA ; 0<= SEA <= MAX_SEA Thus, RSA is a real valued number in the interval [0,1], which for convenience may be scaled to take the values between 0% and 100%, where 0% corresponds to fully buried and 100% to fully exposed residues, respectively. Extended conformation / Folded conformation JM - http://folding.chmcc.org

  4. SABLE is a state-of-the-art RSA predictor 47 CASP6 proteins; Garg, Kaur and Raghava, Proteins 61 (2005) 16 FR/NF CASP6 proteins; Chen and Zhou, Nucl. Acids Res. 33 (2005) “The two-state accuracy bySABLEis 77.3% in the ProSup benchmark, 77.9% inthe SALIGN benchmark, 74.3% in the Lindahl benchmark and, 75.3% in the LiveBench 8 benchmark. This accuracy is consistent with the published performance of thisand other state-of-the-art predictors.” Liu, Zhang, Liang and Zhou, Proteins 68 (2007) JM - http://folding.chmcc.org

  5. Biases in RSA predictions for residues at the interaction interfaces: towards prediction of interaction sites Prediction “errors” at interaction interfaces: differences between predicted and actual (observed in an unbound structure) RSA values. Predictions obtained using SABLE; picture generated using the POLYVIEW server (A. Porollo) – also used to generate most animations and other pictures used in this presentation. JM - http://folding.chmcc.org

  6. Examples of SPPIDER predictions for proteins without homology to proteins used for training and validation … VHL CDK6 Red: known interaction sites predicted correctly; Blue: known interaction sites not predicted as such; Yellow: predicted sites without structural data supporting prediction Catalase JM - http://folding.chmcc.org

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