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Hydrophobic Residue Patterning in β -Strands and Implications for β -Sheet Nucleation

Hydrophobic Residue Patterning in β -Strands and Implications for β -Sheet Nucleation. Brent Wathen Dept. of Biochemistry Queen’s University. Outline. Part I: Introduction Proteins Protein Folding Part II: Protein Structure Prediction Goals, Challenges Techniques State of the Art

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Hydrophobic Residue Patterning in β -Strands and Implications for β -Sheet Nucleation

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  1. Hydrophobic ResiduePatterning in β-Strands and Implications for β-SheetNucleation Brent Wathen Dept. of Biochemistry Queen’s University

  2. Outline • Part I: Introduction • Proteins • Protein Folding • Part II: Protein Structure Prediction • Goals, Challenges • Techniques • State of the Art • Part III: Residue Patterning on β-Strands • β-Sheet Nucleation • Hydrophobic/Hydrophilic Patterning

  3. Outline • Part I: Introduction • Proteins • Protein Folding • Part II: Protein Structure Prediction • Goals, Challenges • Techniques • State of the Art • Part III: Residue Patterning on β-Strands • β-Sheet Nucleation • Hydrophobic/Hydrophilic Patterning

  4. Part I: Introduction Proteins – Some Basics • What Is a Protein?

  5. Part I: Introduction Proteins – Some Basics • What Is a Protein? • Linear Sequence of Amino Acids...

  6. Part I: Introduction Proteins – Some Basics • What Is a Protein? • Linear Sequence of Amino Acids... • What is an Amino Acid?

  7. Part I: Introduction Proteins – Some Basics • What Is a Protein? • Linear Sequence of Amino Acids... • What is an Amino Acid?

  8. Part I: Introduction Proteins – Some Basics • How many types of Amino Acids?

  9. Part I: Introduction Proteins – Some Basics • How many types of Amino Acids? • 20 Naturally Occurring Amino Acids • Differ only in SIDE CHAINS IsoleucineArginineTyrosine

  10. Part I: Introduction Proteins – Some Basics • Amino Acids connect via PEPTIDE BOND

  11. Part I: Introduction Proteins – Some Basics • Backbone can swivel: DIHEDRAL ANGLES • 2 per Amino Acid • Proteins can be 100’s of Amino Acids in length! • Lots of freedom of movement

  12. Part I: Introduction Protein Functions • What do proteins do?

  13. Part I: Introduction Protein Functions • What do proteins do? • Enzymes • Cellular Signaling • Antibodies

  14. Part I: Introduction Protein Functions • What do proteins do? • Enzymes • Cellular Signaling • Antibodies • WHAT DON’T THEY DO!

  15. Part I: Introduction Protein Functions • What do proteins do? • Enzymes • Cellular Signaling • Antibodies • WHAT DON’T THEY DO! • Comes from Greek Work Proteios – PRIMARY • Fundamental to virtually all cellular processes

  16. Part I: Introduction Protein Functions • How do proteins do so much?

  17. Part I: Introduction Protein Functions • How do proteins do so much? • Proteins FOLD spontaneously • Assume a characteristic 3D SHAPE • Shape depends on particular Amino Acid Sequence • Shape gives SPECIFIC function

  18. Part I: Introduction Protein Structure • STRUCTURE  FUNCTION relationship • Determining structure is often critical in understanding what a protein does • 2 main techniques • X-ray crystallography • NMR • 0.5Å RMSD accuracy • Both are very challenging • Months to years of work • Many proteins don’t yield to these methods

  19. Part I: Introduction Protein Structure • Levels of organization • Primary Sequence • Secondary Structure (Modular building blocks) • α-helices • β-sheets • Tertiary Structure • Quartenary Structure • Hydrophobic/Hydrophilic Organization • Hydrophobics ON INSIDE • Hydrophobic Cores

  20. Part I: Introduction Protein Structure

  21. Part I: Introduction Protein Structure

  22. Part I: Introduction Protein Folding • What we DO know... • Protein folding is FAST!! • Typically a couple of seconds • Folding is CONSISTENT!! • Involves weak forces – Non-Covalent • Hydrogen Bonding, van der Waals, Salt Bridges • Mostly, 2-STATE systems • VERY FEW INTERMEDIATES • Makes it hard to study – BLACK BOX

  23. Part I: Introduction Protein Folding • What we DON’T know... • Mechanism...? • Forces...? • Relative contributions? • Hydrophobic Force thought to be critical

  24. Part I: Introduction Intro Summary • Proteins are central to all living things • Critical to all biological studies • Folding process is largely unknown • Sequence  Structure Mapping • Structure  Function relationship • Determining Protein Structure Experimentally is HARD WORK

  25. Outline • Part I: Introduction • Proteins • Protein Folding • Part II: Protein Structure Prediction • Goals, Challenges • Techniques • State of the Art • Part III: Residue Patterning on β-Strands • β-Sheet Nucleation • Hydrophobic/Hydrophilic Patterning

  26. Part II: Structure Prediction The Prediction Problem Can we predict the final 3D protein structure knowing only its amino acid sequence?

  27. Part II: Structure Prediction The Prediction Problem Can we predict the final 3D protein structure knowing only its amino acid sequence? • Studied for 4 Decades • “Holy Grail” in Biological Sciences • Primary Motivation for Bioinformatics • Based on this 1-to-1 Mapping of Sequence to Structure • Still very much an OPEN PROBLEM

  28. Part II: Structure Prediction PSP: Goals • Accurate 3D structures. But not there yet. • Good “guesses” • Working models for researchers • Understand the FOLDING PROCESS • Get into the Black Box • Only hope for some proteins • 25% won’t crystallize, too big for NMR • Best hope for novel protein engineering • Drug design, etc.

  29. Part II: Structure Prediction PSP: Major Hurdles • Energetics • We don’t know all the forces involved in detail • Too computationally expensive BY FAR! • Conformational search impossibly large • 100 a.a. protein, 2 moving dihedrals, 2 possible positions for each diheral: 2200 conformations! • Levinthal’s Paradox • Longer than time of universe to search • Proteins fold in a couple of seconds?? • Multiple-minima problem

  30. Part II: Structure Prediction Tertiary Structure Prediction • Major Techniques • Template Modeling • Homology Modeling • Threading • Template-Free Modeling • ab initio Methods • Physics-Based • Knowledge-Based

  31. Part II: Structure Prediction Template Modeling • Homology Modeling • Works with HOMOLOGS • ~ 50% of new sequences have HOMOLOGS • BLAST or PSI-BLAST search to find good models • Refine: • Molecular Dynamics • Energy Minimization

  32. Part II: Structure Prediction Template-Free Modeling • Modeling based primarily from sequence • May also use: Secondary Structure Prediction, analysis of residue contacts in PDB, etc. • Advantages: • Can give insights into FOLDING MECHANISMS • Adaptable: Prions, Membrane, Natively Unfolded • Doesn’t require homologs • Only way to model NEW FOLDS • Useful for de novo protein design • Disadvantages: HARD!

  33. Part II: Structure Prediction Template-Free Modeling • Physics-Based • Use ONLY the PRIMARY SEQUENCE • Try to model ALL FORCES • EXTREMELY EXPENSIVE computationally • Knowledge-Based • Include other knowledge: SSP, PDB Analysis • Statistical Energy Potentials • Not so interested in folding process • “Hot” area of research

  34. Part II: Structure Prediction Template-Free Modeling • All methods SIMPLIFY problem • Reduced Atomic Representations • C-α’s only; C-α + C-β; etc. • Simplify Force Fields • Only van der Waals; only 2-body interactions • Reduced Conformational Searches • Lattice Models • Dihedral Angle Restrictions

  35. Part II: Structure Prediction Template-Free Modeling • Basic Approach: 1. Begin with an unfolded conformation 2. Make small conformational change 3. Measure energy of new conformation Accept based on heuristic: SA, MC, etc. 4. Repeat until ending criteria reached • Underlying Assumption: Correct Conformation has LOWEST ENERGY

  36. Part II: Structure Prediction Diverse Efforts • Data Mining • Pattern Classification • Neural Networks, HMMs, Nearest Neighbour, etc. • Packing Algorithms • Search Optimization • Traveling Salesman Problem • Contact Maps, Contact Order • Constraint Logic, etc. • Combinations of the above!

  37. Part II: Structure Prediction ROSETTA • Pioneered by Baker Group (U. of Washington) • Fragment Based Method • Guiding Assumption: • Fragment Conformations in PDB approximate their structural preferences • Pre-build fragment library • Alleviates need to do local energy calculations • Lowest energy conformations should already be in library

  38. Part II: Structure Prediction ROSETTA • Pre-build fragment library • 3-mers and 9-mers • 200 structural possibilities for each • Build conformations from the library • Randomly assign 3-mers, 9-mers along chain • During conformational search, reassign a 3-mer or a 9-mer to a new conformation at random • Score using energy function • Adaptive: Coarse grain at first, detailed at end • Accept changes based on Monte Carlo method

  39. Part II: Structure Prediction Diverse Efforts • Data Mining • Pattern Classification • Neural Networks, HMMs, Nearest Neighbour, etc. • Packing Algorithms • Search Optimization • Traveling Salesman Problem • Contact Maps, Contact Order • Constraint Logic, etc. • Combinations of the above!

  40. Part II: Structure Prediction State of the Art • CASP Competition • Critical Assessment of Structure Prediction • Blind Competition Every 2 years • CASP6 in 2004 - CASP7 just completed • ~75 proteins whose structures have not been published as yet • Easy homologs examples • Distant homologs available • De novo structures: no homologs known

  41. Part II: Structure Prediction State of the Art • Template Modeling CASP6 Target 266 (green), and best model (blue) Moult, J. (2005) Cur. Opin. Struct. Bio.15:285-289

  42. Part II: Structure Prediction State of the Art • Template Modeling • Alignment still not easy, and often requires multiple templates • Accurate core models (within 2-3Å RMSD) • Still not good at modeling regions missing from template • Side-chain modeling not too good • Molecular dynamics not able to improve models as hoped

  43. Part II: Structure Prediction State of the Art • Template-Free Modeling CASP6 target 201, and best model. Vincent, J.J. et. al (2005) Proteins 7:67-83.

  44. Part II: Structure Prediction State of the Art • Template-Free Modeling CASP6 target 241, and 3 best models. Vincent, J.J. et. al (2005) Proteins 7:67-83.

  45. Part II: Structure Prediction State of the Art • How Good are Current Techniques? • CASP6 Summary: “The disappointing results for [hard new fold] targets suggest that the prediction community as a whole has learned to copy well but has not really learned how proteins fold.” Vincent, J.J. et. al (2005) Proteins 7:67-83.

  46. Part II: Structure Prediction PSP Summary • Many diverse, creative efforts • Progress IS being made in finding final 3D structures • Less so with regards to understanding folding mechanisms • NEEDED: • Marriage of Creative Ideas and Increased Resources

  47. Outline • Part I: Introduction • Proteins • Protein Folding • Part II: Protein Structure Prediction • Goals, Challenges • Techniques • State of the Art • Part III: Residue Patterning on β-Strands • β-Sheet Nucleation • Hydrophobic/Hydrophilic Patterning

  48. Part III: β-Strand Patterning β-Sheet Basics • Made up of β-Strands • Diverse: • Parallel/Antiparallel • Edge/Interior Strands • Typically Twisted • Many Forms • β-sandwiches, β-barrels, β-helices, β-propellers, etc. • 2D? 3D? • Less studied than helices

  49. Part III: β-Strand Patterning Beta Sheet Basics Internalin A Narbonin Polygalacturonase Galactose Oxidase

  50. Part III: β-Strand Patterning Beta Sheet Basics • What do we know? •  Residues: • V, I, F, Y, W, T, C L • Found largely in Protein Cores • Amphipathic Nature

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