Molecular modelling José R. Valverde CNB/CSIC © José R. Valverde, 2014 CC-BY-NC-SA.

Slides:



Advertisements
Similar presentations
Applications of Homology Modeling
Advertisements

PROTEOMICS 3D Structure Prediction. Contents Protein 3D structure. –Basics –PDB –Prediction approaches Protein classification.
Protein Threading Zhanggroup Overview Background protein structure protein folding and designability Protein threading Current limitations.
Applications of Homology Modeling Hanka Venselaar.
Prediction to Protein Structure Fall 2005 CSC 487/687 Computing for Bioinformatics.
Structure Prediction. Tertiary protein structure: protein folding Three main approaches: [1] experimental determination (X-ray crystallography, NMR) [2]
CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU Homology Modeling Anne Mølgaard, CBS, BioCentrum, DTU.
Tertiary protein structure viewing and prediction July 1, 2009 Learning objectives- Learn how to manipulate protein structures with Deep View software.
CISC667, F05, Lec21, Liao1 CISC 467/667 Intro to Bioinformatics (Fall 2005) Protein Structure Prediction 3-Dimensional Structure.
Protein structure (Part 2 of 2).
Structure Prediction. Tertiary protein structure: protein folding Three main approaches: [1] experimental determination (X-ray crystallography, NMR) [2]
Tertiary protein structure viewing and prediction July 5, 2006 Learning objectives- Learn how to manipulate protein structures with Deep View software.
Thomas Blicher Center for Biological Sequence Analysis
The Protein Data Bank (PDB)
. Protein Structure Prediction [Based on Structural Bioinformatics, section VII]
1 Protein Structure Prediction Reporter: Chia-Chang Wang Date: April 1, 2005.
Protein Tertiary Structure. Primary: amino acid linear sequence. Secondary:  -helices, β-sheets and loops. Tertiary: the 3D shape of the fully folded.
Molecular modelling / structure prediction (A computational approach to protein structure) Today: Why bother about proteins/prediction Concepts of molecular.
1 Protein Structure Prediction Charles Yan. 2 Different Levels of Protein Structures The primary structure is the sequence of residues in the polypeptide.
CENTER FOR BIOLOGICAL SEQUENCE ANALYSISTECHNICAL UNIVERSITY OF DENMARK DTU Homology Modelling Thomas Blicher Center for Biological Sequence Analysis.
Homology Modeling Seminar produced by Hanka Venselaar.
Protein Tertiary Structure Prediction Structural Bioinformatics.
Protein Structures.
An introduction and homology modeling
Bioinformatics Ayesha M. Khan Spring 2013.
Protein Structure Prediction and Analysis
Homology Modeling David Shiuan Department of Life Science and Institute of Biotechnology National Dong Hwa University.
Protein Tertiary Structure Prediction
Construyendo modelos 3D de proteinas ‘fold recognition / threading’
Macromolecular structure
Practical session 2b Introduction to 3D Modelling and threading 9:30am-10:00am 3D modeling and threading 10:00am-10:30am Analysis of mutations in MYH6.
COMPARATIVE or HOMOLOGY MODELING
Representations of Molecular Structure: Bonds Only.
RNA Secondary Structure Prediction Spring Objectives  Can we predict the structure of an RNA?  Can we predict the structure of a protein?
Lecture 12 CS5661 Structural Bioinformatics Motivation Concepts Structure Prediction Summary.
Protein Folding Programs By Asım OKUR CSE 549 November 14, 2002.
Protein Structure & Modeling Biology 224 Instructor: Tom Peavy Nov 18 & 23, 2009
Protein secondary structure Prediction Why 2 nd Structure prediction? The problem Seq: RPLQGLVLDTQLYGFPGAFDDWERFMRE Pred:CCCCCHHHHHCCCCEEEECCHHHHHHCC.
Applied Bioinformatics Week 12. Bioinformatics & Functional Proteomics How to classify proteins into functional classes? How to compare one proteome with.
Protein Folding and Modeling Carol K. Hall Chemical and Biomolecular Engineering North Carolina State University.
1 Protein Structure Prediction (Lecture for CS397-CXZ Algorithms in Bioinformatics) April 23, 2004 ChengXiang Zhai Department of Computer Science University.
Structure prediction: Homology modeling
Protein Modeling Protein Structure Prediction. 3D Protein Structure ALA CαCα LEU CαCαCαCαCαCαCαCα PRO VALVAL ARG …… ??? backbone sidechain.
Predicting Protein Structure: Comparative Modeling (homology modeling)
Protein Structure Prediction: Homology Modeling & Threading/Fold Recognition D. Mohanty NII, New Delhi.
Introduction to Protein Structure Prediction BMI/CS 576 Colin Dewey Fall 2008.
Protein Folding & Biospectroscopy Lecture 6 F14PFB David Robinson.
Structural classification of Proteins SCOP Classification: consists of a database Family Evolutionarily related with a significant sequence identity Superfamily.
CS-ROSETTA Yang Shen et al. Presented by Jonathan Jou.
Ab-initio protein structure prediction ? Chen Keasar BGU Any educational usage of these slides is welcomed. Please acknowledge.
Protein Tertiary Structure Prediction Structural Bioinformatics.
Protein Structure Prediction: Threading and Rosetta BMI/CS 576 Colin Dewey Fall 2008.
Protein Structure Prediction. Protein Sequence Analysis Molecular properties (pH, mol. wt. isoelectric point, hydrophobicity) Secondary Structure Super-secondary.
Lab Lab 10.2: Homology Modeling Lab Boris Steipe Departments of Biochemistry and.
Automated Structure Prediction using Robetta in CASP11 Baker Group David Kim, Sergey Ovchinnikov, Frank DiMaio.
Homology 3D modeling Miguel Andrade Mainz, Germany Faculty of Biology,
PROTEIN MODELLING Presented by Sadhana S.
Protein Structure Visualisation
Molecular modelling Practical session
Challenges in Creating an Automated Protein Structure Metaserver
Computational Chemistry
Protein Structure Prediction and Protein Homology modeling
Protein dynamics Folding/unfolding dynamics
Protein Structures.
Molecular Modeling By Rashmi Shrivastava Lecturer
3-Dimensional Structure
Rosetta: De Novo determination of protein structure
Homology Modeling.
Protein structure prediction.
Homology modeling in short…
Presentation transcript:

Molecular modelling José R. Valverde CNB/CSIC © José R. Valverde, 2014 CC-BY-NC-SA

Contents Ab initio modelling Ab initio Quantum Mechanics Ab initio Molecular Mechanics Homology modelling Homology Threading Structure prediction

Ab initio modelling Predict 3D structure from chemical formula Out of purely theoretical models Maximum quality (given state of the art) Maximum cost (nothing is assumed)

Ab initio QM The best possible approximation Tremendous computational cost N 3 – N 8 (on the number of elementary particles) Unfeasible for all but smallest systems Modern approaches on the order of N (medium sized systems) Linearly scaling DFT Multipoles and cutoffs MOZYME

Ab initio MM/MD Classical mechanics treatment E = E bonded + E non-bonded E non-bonded scales to N 2 Soft charged spheres joined by springs Ignore bond-breaking and formation From scratch approaches Tractable only for small-medium size systems Large systems Workable if we can start close to the solution

Ab initio modeling Hard problem solvable for small proteins/fragments (~ < 200 a.a.) Energy-based / fragment-based Model from scratch using physical principles Evolutionary covariation to predict contacts Working for hundreds of residues Servers Quark:zhanglab.ccmb.med.umich.edu/QUARK/ Robetta: Evfold:

Homology modelling Conformational search is a combinatorial problem: N! In the best case we know all factors involved But we don't We may assume that similar functions share similar structures and sequences Start from similar structure Assume it is close to the solution Apply an energy minimization step.

Know your problem The first step in any simulation is knowing your problem What do you want to know What is already known? Is the solution already known? Is there an approximate solution? What are the characteristics, properties and constrains of your system? Bibliography Database searches

Search for the structure Is the structure already known? Do we know the sequence? Blast/FastA against PDB Look for exact matches A mutation or polymorphism means we need to build a model If we ignore the sequence Direct PDB searches If we succeed, we can ignore the rest: we do have the structure

Search for a template Start from a sequence New sequence Old sequence mutated Use FASTA format on a text editor Select a modeling method General good similarity (>40%): Homology Twilight zone (30-40%): Threading Local similarities: partial models

Steps Template recognition and alignment Alignment correction Backbone generation Loop modeling Side-Chain modeling Model optimization Model validation

Finding templates Run blast/FastA against PDB Do we have matches with enough similarity? > 40% : homology model 30-40% : threading What is the sequence coverage Complete or nearly complete: homology Domain of interest: homology Partial domains : threading

Align sequence to template We will use the known structure(s) as template We must pair residues in the sequence with unknown structure with residues in the sequence(s) with known structure Start with an automatic alignment program Review and correct the alignment e. g. check domain/secondary structure limits

Generate backbone Using as template the backbone coordinates of the known structure(s) assign coordinates to the backbone of the problem sequence N, C , C, O If they are the same, the side chain can also be assigned Note that there may be discordances between templates

Loop/turn modeling Most discordances will affect loops Different lengths, greater flexibility Cut out loops Model loops separately Knowledge based: refer to known PDB structures Loop databases Energy based (ab initio): minimize an energy function

Side chain modeling When side chains are not the same, we cannot use the reference coordinates Use available knowledge (gathered from PDB) to select the most appropriate rotamer Dunbrack rotamer library Look for a rotamer that favours packing and lower energy ~90% accuracy on hydrophobic core (tightly packed), ~50% for surface residues

Refine initial model What next? It may be sensible to stop here If similarity is very high (point mutation) After ensuring no steric clashes (try rotamers) It we know there are no major changes If validation shows no major conflicts If it agrees with prior knowledge Perform additional refinement cycles Minimization (to avoid strong conflicts) MD (to allow for conformational changes) Simulated annealing

Model optimization In general, more stable structures will have lower internal energy Compute energy Use energy to optimize the structure Molecular Mechanics Force field Various minimization algorithms: Quick and dirty Slow and accurate

Further optimization Validate your structure Check against prior knowledge Optimization might have found a local minimum Look for alternate configurations Simulated Annealing Molecular Dynamics Simulation times are too short (ps-ns) Validate and repeat

Model Validation All models tend to contain errors Errors may accumulate after “refinement”! There may be “errors” in the template(s) Check for energetic conflicts Check for “normality” Requires caution Compare with template(s) Decide if they are significant (affect relevant portions of the structure)

Homology modelling Check CASP results Some studies report that automated modeling may be safer than human-curated Less subjective decisions Start with public servers Automatic: Upload a sequence and wait 3D-Jigsaw, CPHmodels, Robetta, EasyPred3D... Semiautomatic: Upload a sequence and participate WHATIF, HOMER, SwissModel with DeepView

MetaServers GeneSilico Wide variety of predictions LOMETS: zhanglab.ccmb.med.umich.edu/LOMETS Local MetaThreading server Protein Model Portal: Interactive Modeling Access existing models

Servers CPHmodels HHpred ModBase LOOPP Zhang Lab

Servers (continued) Phyre 2 (ps) 2 PsiPred M4T SwissModel

Threading Generalization of homology modeling Homology: align sequence to sequence Threading: align sequence to structures Limited number of basic folds in nature Amino acids have environmental preferences for specific folds Used when sequence identity < 25%

Threading components Library of core fold templates (e.g. from SCOP, CATH, FSSP, PDB...) Function to evaluate quality of assignment Consider a. a. preferences for location, structure, neighbors... Method for aligning sequences to fold templates Method for choosing best template among alignments

Threading software HHpred RaptorX Phyre 2 SPARKS X sparks-lab.org/yueyang/server/SPARKS-X/ 3D-JigSaw

Questions? Image by DasWortgewand. CC0