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Protein Predictinon
The document discusses experimental and computational methods for protein structure prediction. Experimental methods like NMR, X-ray crystallography, and cryo-EM can accurately determine protein structure but require isolating and crystallizing the protein. Computational methods like homology modeling, ab initio modeling, and threading/folding predict structure from sequence alone and are less accurate but do not require crystallization. Computational methods work best when a template structure is available from experimental data. While experimental methods are very accurate, they are also costly and difficult for large numbers of proteins, making computational methods a useful complement despite being less accurate.
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Protein Predictinon
- 1. Protein Prediction Experimental Computational Predictingthe structure of protein using computational tools.
- 2. Why we arecalling it prediction? भविष्यिाणी पूिवकथन पूिव-सूचना Proteins are flexible. Structure depends on the environmental conditions. Binding of ligand changes the structure of the protein. Complete protein isolation is very difficult. It may be
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- 4. Prediction Experimental 1. NMR 2. X-RayCrystallograogy 3. Cryo EM Computational 1. Ab Initio 2. Threading/Folding 3. Homology Modelling Protein extraction and crystallization is required Algorithms and Statistical tools required Atomic Level Resolution Work good when template is available. Template is provided by experimental data Accurate Not so accurate Closer to native structure Cannot be said. Depends on accuracy Manually Tedious Computationally Tedious Costly Not so costly
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- 6. When experimental prediction isdoing well then what is the need of computational prediction?
- 7. 1. 2015 Study-Experimental data analysis Super-Computers2. Computers Theoretical Algorithm can be computed using Protein Evolutional stable Increased Cost3. Repetitive Experimental No new protein structure Large number of templates available Computational work great with template
- 8. Computational Prediction Homology Modelling Ab-Initio Threading (Folding) 1stStudent 2nd Student 3rd Student From the beginning Grab portions Template based Computationally very intensive Not intensive Large care of small parameters Not much care Toughest Easiest Sequence Alignment
- 10. Hydrophobicity Hydrophilicity Folding pH, pI, pKa Physiochemical Transmembrane Solubility Thermal Phylogenic Evolution Anfinsen’sTheory – All information in the sequence
- 11. Sequence Alignment Global AlignmentLocal Alignment
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