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Protein structure prediction in 2002

Protein structure prediction in 2002. Jack Schonbrun, William J Wedemeyer and David Baker. CASP: Critical Assessment of Protein Structure Prediction. A competition of protein structure prediction Predict the structure of target sequences whose structures will be released soon.

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Protein structure prediction in 2002

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  1. Protein structure prediction in 2002 Jack Schonbrun, William J Wedemeyer and David Baker

  2. CASP: Critical Assessment of Protein Structure Prediction • A competition of protein structure prediction • Predict the structure of target sequences whose structures will be released soon

  3. Protein structure prediction in three areas • Comparative modeling:Where there is a clear sequence relationship between the target structure and one or more known structures. • Fold recognition ('threading'):No sequence homology with known structures. Find consistent folds (remote homology detection). • Ab initio structure prediction(‘de novo’):Deriving structures, approximate or otherwise, from sequence.

  4. Comparative Modeling • Find homology proteins with known structure as templates • Align target with template sequences in terms of sequence/PSSM (most important) • Evolution makes sequence similarity weaker • No one-one corresponding due to Insertion/deletion • full-atom refinement and loop modeling

  5. Fold recognition • There is no known structure for the homologies of target sequence • Find remote homologies with consistent (similar) structures. • Does structural information help? • Do comparative modeling

  6. De novo • No template available for use, predict the structure by folding simulation • Rosetta: • based on short segments independently sample distinct distributions of local conformations from known structure • Folding happens when orientations and conformations allow low free energy interactions. Optimized by a Monte Carlo search procedure

  7. Coalescence of structure prediction problems • Comparative modeling uses more sensitive way to find templates • Fold recognition have improved alignment by more detailed sequence information • Fold recognition may be able to find very related structures as template • Loop modeling in comparative modeling is a small ‘de nova’ prediction problem

  8. Conclusions • Refinement doesn’t help comparative modeling • Structural information helps fold recognition • De novo prediction obtained a reasonable results • Obstacle is high-resolution modeling

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