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Putting biology to work for you: In vitro (directed) evolution and other techniques

Putting biology to work for you: In vitro (directed) evolution and other techniques. Phage display. Make a combinatorial library of genes of interest Put genes into a vector so that each gene product is expressed on the surface of a bacteriophage

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Putting biology to work for you: In vitro (directed) evolution and other techniques

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  1. Putting biology to work for you:In vitro (directed) evolution and other techniques

  2. Phage display Make a combinatorial library of genes of interest Put genes into a vector so that each gene product is expressed on the surface of a bacteriophage Function encoded by each gene is on surface of phage Gene is inside phage Take collection of phage and select those with desired properties (e.g., binding to something) Similar methods: yeast display, bacterial display, ribosome display See animation of phage display here: http://www.dyax.com/discovery/phagedisplay.html

  3. Figure A-15 In vitro selection to produce human monoclonal antibodies or increase affinity of existing monoclonal antibody Clone into a phage so that each phage expresses one VH-VL surface fusion protein. Multiply phage display library in bacteria, bind phage to surface coated with antigen. Wash away unbound phage. Repeat procedure (multiply recovered phage, bind to antigen, wash away unbound phage) for several cycles. Recover specific high-affinity antigen binding VH-VL regions. Generate library of heavy and light chain variable regions using spleen DNA. Or introduce random mutations into variable regions genes of a specific antibody.

  4. Phage Display schematic 3 1 2 5 6 4 7 8

  5. Phage display to select for sequence-specific DNA binding proteins • Zinc finger proteins are modular. • Each finger contains two anti-parallel -strands, an -helix, and a Zn atom. • The -helix from each finger inserts into the major groove of DNA.

  6. A General Strategy for Selecting High Affinity Zinc Finger Proteins for Diverse DNA Target SitesGreisman et al., 1997, Science 275: 657 First use 3-finger/DNA crystal structure to determine important protein/DNA contacts

  7. A General Strategy for Selecting High Affinity Zinc Finger Proteins for Diverse DNA Target SitesGreisman et al., 1997, Science 275: 657 Originally bound to this sequence

  8. RNA aptamers -- antibody-like properties Aptamers have been made against small molecules, peptides, proteins, organelles, viruses, cells

  9. Vitamin b12-binding RNA aptamer

  10. Aptamer database: http://aptamer.icmb.utexas.edu/index.php

  11. Let the immune system make enzymes for you Catalyst must bind more tightly to transition state than to products or reactants.

  12. Catalytic Antibodies Wedemayer et al. (1997) Science 276, 1665-1669. • Raise antibodies against a transition state analog • Screen hybridomas for antibodies that catalyze desired reaction

  13. Catalytic antibody that hydrolyzes cocaineZhu et al., 2006, Structure 14: 205-216 (Nonpsychoactive products) Compound that was injected to raise antibodies Transition state analog that was crystallized with Fab

  14. / barrel enzymes evolved from a common ancestor 10% of enzymes are  barrels But this takes a long time…

  15. Directed evolution http://ocw.mit.edu/OcwWeb/Biology/7-344Spring-2008/CourseHome/index.htm

  16. In vitro evolution of enzymes Enzymes evolved for functions inside a living organism, not for biotechnology Might need long-term stability Might need activity in non-aqueous solutions Produce new enzymes using recombinant DNA technology, but don’t know how by rational design Use directed evolution

  17. Directed evolution experiment From Frances Arnold’s website: www.che.caltech.edu/groups/fha

  18. Some considerations… Don’t start with random sequences because there are too many (20N) Instead start with lightly mutagenized gene (e.g., error-prone PCR) or high level of random mutations to small part of gene

  19. Most mutations are destabilizing, so simply increasing protein stability can increase mutational robustness Marginally stable parent protein ∆Gf stable unstable Stabilized parent protein These previously unacceptable mutations are now acceptable. ∆Gf (critical threshold stability) “Protein stability promotes evolvability.” JD Bloom, ST Labthavikul, CR Otey, and FH Arnold. Proc Natl Acad Sci, 103:5869-5874 (2006).

  20. Two state unfolding transition N <--> DMonitor property of folded protein as function of increasing temperatureTransition midpoint (Tm) Evaluating stability Shows that class I MHC molecules require bound peptide for thermal stability

  21. “Family” shuffling experiment From Frances Arnold’s website: www.che.caltech.edu/groups/fha

  22. From Frances Arnold’s website: www.che.caltech.edu/groups/fha

  23. Protein Library Design multiple sequences 1 structure Sequence Space Structure Space Mayo lab, Caltech

  24. Protein Fold Prediction versus Protein Design 1 sequence 1 structure Sequence Space Structure Space Mayo lab, Caltech

  25. ResiduesSequencesMass 18 1023 Baseball 37 1048 Earth 42 1054 Sun 59 1077 Universe Computational Protein Design: Rationale by the Numbers Combinatorial Explosion 1 protein p residues 20 amino acid types 20p sequences Mayo lab, Caltech

  26. Methods Atom-Based Forcefields Combinatorial Optimization Algorithms Rotamer Libraries Protein Backbones Negative Design Computational Protein Design Optimization of Rotamers by Iterative Techniques (ORBIT)Apply to protein fold stabilization, enzyme design Applications Mayo lab, Caltech

  27. Designed protein Zif268 Zn finger De Novo Protein Design: Fully automated sequence selectionDahiyat & Mayo, 1997, Science 278: 82-87 Comparison of original and designedprotein structures Target fold: Zif268 (a zinc finger)

  28. Stability Based Design: Protein G • Bacterial protein involved in host immune system evasion • 56 amino acid domain • Objective was to stabilize protein while preserving structure and function • Design focused on 26 core and boundary positions • Combinatorial complexity, 106 amino acid sequences Mayo lab, Caltech

  29. active site template ab initio t.s. model catalytic antibody: kcat/kuncat = 106 Thorn et al., Nature 1995 Debler et al., PNAS 2005 Hu et al., JACS 2004 Kemp Elimination: a model system for enzyme design 5-nitrobenzsoxazole Mayo lab, Caltech

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