Protien Structure Prediction
- 1. Protein Structure Prediction Submitted By :- Name : Md.Selim Reza Id : 183-15-12020 W E L - C O M E T o M y P r e s e n t a t i o n On Submitted To : Mohd. Saifuzzaman Lecturer, Daffodil International University
- 2. What is Protein structure prediction ? Protein structure prediction is the inference of the three- dimensional structure of a protein from its amino acid sequence—that is, the prediction of its secondary and tertiary structure from primary structure.
- 3. Different Levels of Protein Structure
- 4. METHODS FOR PROTEIN STRUCTURE PREDICTION 1.EXPERIMANTAL METHODS 2.COMPUTIONAL METHODS
- 5. Experimental Protein Structure Determination • • • X.ray crystallography – most accurate – in vitro – needs crystals – ~$100-200K per structure –time consuming and expansive. NMR – fairly accurate – in vivo – no need for crystals – limited to very small proteins –time consuming and hardly . Electron-microscopy – imaging technology – low resolution – not more observable.
- 6. Computational method • Major Techniques – Template Modeling • Homology Modeling • Threading • Both are use known protein structure – Template-Free Modeling • ab initio Methods – Physics-Based – Knowledge-Based – without use of known protein structure
- 7. Homology Modelling • also called comparitive modeling. • predict protein structures based on sequence homology with known structure. • Principle:- • if two proteins share a high enough sequence similarity,they are likely to have very similar three dimensional structure. • modeling server:-modbase,swiss-model etc. • Fail in absence of homology
- 8. Homology Modelling 6 steps:- 1.template selection (BLAST and FASTA) 2.sequence alignment (T-coffee and PRALINE) 3.model building (CODA) (a)backbone model building (b)loop modeling 4.side chain refinement (SCWRL) 5.model refinement using energy function (GROMOS) 6.model evalution (PROCHECK & WHAT IF) • Has been observed that even proteins with 30% sequence identity fold into similar structures • Does not work for remote homologs (< 30% pairwise identity)
- 9. Threading • Given: – sequence of protein 'P 'with unknown structure – Database of known folds • Find: – Most plausible fold for 'P' – Evaluate quality of such arrangement • Places the residues of unknown 'P' along the backbone of a known structure and determines stability of side chains in that arrangement
- 10. Threading and fold recognition • predicts the structural fold of unknown protein sequences by fitting the sequence into a structural database and selecting the best fitting fold. • we can identify structurally similar proteins even without detectablesequence similarity. • two algorithms:- 1.pairwise energy based method 2.profile based method
- 11. Protein Sequence Database Searching Multiple Sequence Alignment Homologue in PDB Homology Modelling Secondary Structure Prediction No Yes 3-D Protein Model Fold Recognition Predicted Fold Sequence-Structure Alignment Ab-initio Structure Prediction No Yes Overall Approach