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 Generate library of heavy and light chain variable regions using spleen DNA. Or introduce random mutations into variable regions genes of a specific antibody. Clone into a phage so that each phage expresses one V H -V L 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 V H -V L regions.

4. Phage Display schematic 1 2 3 4 56 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 Sites Greisman 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 Sites Greisman 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 Raise antibodies against a transition state analog Screen hybridomas for antibodies that catalyze desired reaction Wedemayer et al. (1997) Science 276, 1665-1669.

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

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

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 (20 N ) 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 ∆G f Marginally stable parent protein ∆G f stableunstable Stabilized parent protein These previously unacceptable mutations are now acceptable. (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. Evaluating stability Two state unfolding transition N D Monitor property of folded protein as function of increasing temperature Transition midpoint (T m ) 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

23. Sequence SpaceStructure Space multiple sequences1 structure Protein Library Design Mayo lab, Caltech

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

25. Computational Protein Design: Rationale by the Numbers Residues Sequences Mass 18 10 23 Baseball 37 10 48 Earth 42 10 54 Sun 59 10 77 Universe Combinatorial Explosion 1 protein p residues 20 amino acid types 20 p sequences Mayo lab, Caltech

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

27. De Novo Protein Design: Fully automated sequence selection Dahiyat & Mayo, 1997, Science 278: 82-87 Comparison of original and designed protein structures Target fold: Zif268 (a zinc finger) Designed protein Zif268 Zn 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, 10 6 amino acid sequences Mayo lab, Caltech

29. catalytic antibody: k cat /k uncat = 10 6 Thorn et al., Nature 1995 Debler et al., PNAS 2005 5-nitrobenzsoxazole active site templateab initio t.s. model Hu et al., JACS 2004 Kemp Elimination: a model system for enzyme design Mayo lab, Caltech