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Alejandro Giorgetti 3rd Permanent School in Bioinformatics Madrid 2005 Protein Structure Modeling Alejandro Giorgetti.

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Presentation on theme: "Alejandro Giorgetti 3rd Permanent School in Bioinformatics Madrid 2005 Protein Structure Modeling Alejandro Giorgetti."— Presentation transcript:

1 Alejandro Giorgetti 3rd Permanent School in Bioinformatics Madrid 2005 Protein Structure Modeling Alejandro Giorgetti

2 The number of different protein folds is limited: [ last update: Oct 2001 ] New Folds Known Folds Public Database Holdings:

3 Alejandro Giorgetti Fold recognition Principle: Find a compatible fold >Target Sequence XY MSTLYEKLGGTTAVDLAVAAVA GAPAHKRDVLNQ Build model of target protein based on each template structure Rank models according to SCORE or ENERGY Profile methods Threading M A T E A F T S G Q  Fold =f(environment)  Local Secondary Structure  Solvent Accessibility  Degree of burial of polar / apolar Fragment based methods: New fold prediction

4 Alejandro Giorgetti Some remarks concerning fold recognition:  Capable of detecting quite remote sequence-structure matches.  Sensitivity depends on the size of the protein and its secondary structure content.  The two most versatile enzymatic functions (hydrolases and o- glycosyl-glucosidases) are associated with seven folds each.  Better for detecting: all-α > αβ > all-β

5 Alejandro Giorgetti Homology modeling  Comparative protein modeling Idea: Proteins evolving from a common ancestor maintained similar core 3D structures.  Known structure/s is/are used as a template to model an unknown structure with known sequence.  Both of them should be related by evolution.  First applied in late 1970’s by Tom Blundell

6 Alejandro Giorgetti 10 % 30 % 50 % 70 % 90 % Drug design? Biochemistry? Molecular Biology? [ Chothia & Lesk (1986) ] Evolution of protein structure families X-ray cristallography: MR

7 Alejandro Giorgetti Template(s) selection Sequence Alignment Structure Modeling Structure Evaluation Final Structural Models Comparative Modeling Known Structures (templates) Target sequence >hTEII MSSPQAPEDGQGCGDRGDPPGDLRSVLVTTV LNLEPLDEDLFRGRHYWVPAKRLFGGQIVGQ ALVAAAKSVSEDVHVHSLHCYFVRAGDPKLP

8 Alejandro Giorgetti Template(s) selection Sequence Alignment Structure Modeling Structure Evaluation Final Structural Models Target sequence Protein Data Bank PDB Database of templates Separate into single chains Remove bad structures (models) Create BLAST database Comparative Modeling Known Structures (templates)

9 Alejandro Giorgetti Known Structures (templates) Sequence Alignment Structure Modeling Structure Evaluation Final Structural Models Target sequence  Sequence Similarity / Fold recognition  Structure quality (resolution, experimental method)  Experimental conditions (ligands and cofactors) Comparative Modeling Template(s) selection

10 Alejandro Giorgetti Known Structures (templates) Template(s) selection Structure Modeling Structure Evaluation Final Structural Models Target sequence  Key step in homology modeling  Global alignment is required  Small error in alignment can lead to big error in model  Multiple alignments are better than pairwise alignments  Do we know something else? Experiments? Comparative Modeling Sequence Alignment

11 Alejandro Giorgetti Known Structures (templates) Template(s) selection Structure Evaluation Final Structural Models Target sequence  Template based fragment Assembly (SwissMod).  Satisfaction of Spatial Restraints: MODELLER Comparative Modeling Sequence Alignment Structure Modeling

12 Alejandro Giorgetti Known Structures (templates) Template(s) selection Sequence Alignment Structure Modeling Final Structural Models Target sequence  Errors in template selection or alignment result in bad models  Iterative cycles of alignment, modeling and evaluation Comparative Modeling Structure Evaluation

13 Alejandro Giorgetti [ ] I. Template based fragment assembly (SwissModel)

14 Alejandro Giorgetti SwissPdb downloading: a)Read and Accept licence b)Download: SwissPdb viewer v3.7sp5(linux) Installation: a)gunzip spdbv37sp5-Linux.tar.gz b)tar –xvf spdbv37sp5-Linux.tar c)cd SPDBV_Distribution and do:./install.sh d)Local installation :..../guestxx/ e)Run: /guestxx/SPDBV/bin/spdbv SwissModel submission: a)Search template: MODEL.html Interactive tools: Search the template...(paste sequence)http://www.expasy.org/swissmod/SWISS- MODEL.html b)Model request submission: Save project (SwissPdb Viewer); c)Swiss- Model web page: Modelling Requests – Optimise mode. d)Fill the form and Upload your project asking for Short mode output. Day activities. Morning

15 Alejandro Giorgetti  Corresponds to the most stable regions.  Highest sequence conservation and fewer gaps.  In general: secondary structures elements. a) Build conserved core framework (Structurally conserved regions -SCRs) I. Template based fragment assembly [ ]

16 Alejandro Giorgetti  Least stable or more flexible regions.  Highest level of gapping  Lowest sequence conservation  Loops and turns  Loop-Database  “ab-initio” rebuilding of loops (Monte Carlo, molecular dynamics, genetic algorithms, etc.) b) Loop modeling (Structural variable regions - SVRs) and backbone completion I. Template based fragment assembly [ ]

17 Alejandro Giorgetti c) Side Chain placement  Find the most probable side chain conformation, using homologues structures back-bone dependent rotamer libraries energetic and packing criteria I. Template based fragment assembly [ ]

18 Alejandro Giorgetti  modeling will produce unfavorable contacts and bonds  idealization of local bond and angle geometry  extensive energy minimization will move coordinates away  keep it to a minimum  SwissModel is using GROMOS 96 force field d) Energy minimization I. Template based fragment assembly

19 Alejandro Giorgetti  Find the most probable structure given its alignment  Satisfy spatial restraints derived from the alignment.  Uses probability density functions.  Minimizes violations on restraints. Comparative protein modeling by satisfaction of spatial restraints. A. Šali and T.L. Blundell. J. Mol. Biol. 234, II. Modeling by Satisfaction of Spatial restraints

20 Alejandro Giorgetti Model Evaluation ? Topics:  correct fold  model coverage (%)  C  - deviation (rmsd)  alignment accuracy (%)  side chain placement  Structure Analysis and Verification Server :

21 Alejandro Giorgetti EVA Evaluation of Automatic protein structure prediction [ Burkhard Rost, Andrej Sali, ]http://maple.bioc.columbia.edu/eva CASP Community Wide Experiment on the Critical Assessment of Techniques for Protein Structure Prediction 3D - Crunch Very Large Scale Protein Modelling Project Model Accuracy Evaluation

22 Alejandro Giorgetti Protein Structure Resources PDBhttp://www.pdb.org PDB – Protein Data Bank of experimentally solved structures (RCSB)http://www.pdb.org CATHhttp://www.biochem.ucl.ac.uk/bsm/cathhttp://www.biochem.ucl.ac.uk/bsm/cath Hierarchical classification of protein domain structures SCOPhttp://scop.mrc-lmb.cam.ac.uk/scop Alexey Murzin’s Structural Classification of proteinshttp://scop.mrc-lmb.cam.ac.uk/scop DALIhttp://www2.ebi.ac.uk/dali Lisa Holm and Chris Sander’s protein structure comparison serverhttp://www2.ebi.ac.uk/dali SS-Prediction and Fold Recognition PHDhttp://cubic.bioc.columbia.edu/predictproteinhttp://cubic.bioc.columbia.edu/predictprotein Burkhard Rost’s Secondary Structure and Solvent Accessibility Prediction Server PSIPRED L.J McGuffin, K Bryson & David T. Jones Secndary struture prediction Server 3DPSSMhttp://www.sbg.bio.ic.ac.uk/~3dpss Fold Recognition Server using 1D and 3D Sequence Profiles coupled.http://www.sbg.bio.ic.ac.uk/~3dpss THREADER: David T. Jones threading program

23 Alejandro Giorgetti UCL, Janet Thornton & Christine Orengo Class (C), Architecture(A), Topology(T), Homologous superfamily (H) Protein Structure Classification CATH - Protein Structure Classification [ ] SCOP - Structural Classification of Proteins MRC Cambridge (UK), Alexey Murzin, Brenner S. E., Hubbard T., Chothia C. created by manual inspection comprehensive description of the structural and evolutionary relationships [ ]

24 Alejandro Giorgetti Class(C) derived from secondary structure content is assigned automatically Architecture(A) describes the gross orientation of secondary structures, independent of connectivity. Topology(T) clusters structures according to their topological connections and numbers of secondary structures Homologous superfamily (H)

25 Alejandro Giorgetti Protein Homology Modeling Resources SWISS MODEL: Deep View - SPDBV: homepage: Tutorials WhatIf Gert Vriend’s protein structure modeling analysis program WhatIf Modeller: Andrej Sali's homology protein structure modelling by satisfaction of spatial restraints ROBETTA: Full-chain Protein Structure Prediction Server Programs and www servers very useful in Comparative modeling:

26 Alejandro Giorgetti


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