Introduction to Directed Evolution

• Directed Evolution: A technique to enhance the 'fitness' of naturally occurring or rationally designed enzymes by mimicking natural evolution.

  • Requires no prior knowledge of protein structure or catalytic mechanisms.

• Goals of Directed Evolution:

  • Improve:

  1. Stability

  2. Specificity

  3. Catalytic efficiency

Random Mutagenesis and Screening

• Random Mutagenesis by Error-Prone PCR:

  • Involves amplification of the gene for the protein of interest, leading to a library of mutant genes (ranging from $10^2$ to $10^9$ mutants).

  • DNA is inserted into a vector for protein expression, resulting in a library of mutant proteins either in cells or on the surface of viruses.

  • Screening or Selection:

  • Identify and choose the most ‘improved’ proteins.

  • The process is typically repeated multiple times, using the improved variant as a new starting sequence.

  • Procedure:

  • Utilize Taq polymerase with an increased concentration of MgCl2 and the addition of MnCl2 for PCR.

  • Extract plasmid DNA for further manipulation.

Success Factors in Screening and Selection

• The success in directed evolution largely depends on the quality of the screening or selection process:

  • Screen: Characterizes mutants individually.

  • Selection: Tests all mutants simultaneously, allowing only desirable mutants to thrive.

• Both needs to provide:

  • Accuracy

  • High throughput (typically $10^2$ to $10^9$ mutants).

• Challenges:

  • Screening for substrate binding is easier than for catalysis, which often yields better results.

  • Requires a method to physically link enzyme activity to its DNA for large-scale screening.

• Two types of screening developed:

  • In Vivo Screening: Measures altered phenotype of transformed microorganisms due to modified protein expression.

  • In Vitro Screening: Uses phage display for selection.

In Vivo Screening Example: dsRed

• dsRed:

  • A red fluorescent protein ideal for microscopy, characterized by slow maturation (half-time of 11 hours).

  • The objective is to find mutants with the same fluorescence characteristics but with a faster maturation rate.

• Procedure:

  • Generate 100,000 mutants per round.

  • Measure fluorescence of colonies after 24 hours of growth, selecting the reddest colony, indicative of faster maturation rates.

  • Extract DNA and repeat the mutagenesis cycle 6 times.

Mutant Analysis of dsRed

• Changes in dsRed.T4 Compared to Wild Type (WT):

  • Notable mutations: R2A, K5E, N6D, T21S, H41T, N42Q, V44A, A145P, and T217A.

  • Maturation parameters comparison:
    | Variant | ε (M^-1cm^-1) | Maturation half-time (h) | Excitation max. (nm) | Emission max. (nm) | Relative brightness | Quantum yield |
    |-------------|-----------------|--------------------------|----------------------|-------------------|---------------------|--------------|
    | WT | 52000 | 11 | 558 | 583 | 1.00 | 0.68 |
    | dsRed.T3 | 49500 | 1.3 | 560 | 587 | 0.83 | 0.59 |
    | dsRed.T4 | 30300 | 0.71 | 555 | 586 | 0.38 | 0.44 |

In Vitro Screening: Phage Display

• Phage Display:

  • The protein of interest is fused to g3p, displaying it at the tip of M13 bacteriophage, linking it to its DNA.

• Procedure:

  1. Cloning of DNA fragments in frame with g3p and transforming E.coli.

  2. Infection with helper phage to generate phage particles.

  3. Panning process (3-5 times with increasing washing stringency).

  4. Results in a library of DNA variants with tight binding affinities, which can be retransformed into E.coli for sequencing and further selection.

Enhancements in Directed Evolution

• Directed evolution effectively increases the ‘fitness’ of specific properties in enzymes, with libraries screening up to $10^9$ mutants.

• Dramatic increases in enzyme stability reported, while modifying substrate specificity is more challenging, although there are successes, such as changing cytochrome P450's substrate specificity.

  • Reference: Angew. Chem. Int. Ed. 2007, 46, 8414-8418.

• Factors impacting substrate specificity include residue changes near the catalytic site, while stability and activity also involve distant residue changes affecting overall protein dynamics.

Smart Libraries for Screening

• High-Throughput Screening Constraints:

  • Smaller libraries with higher hit frequencies required in certain circumstances.

• Smart Libraries:

  • Target specific sites for change, focusing on residues involved in substrate binding.

  • Requires information on 3D structures, previous site-directed mutagenesis, and in-silico modeling data.

  • Saturation Mutagenesis at hotspots can be combined with random whole-gene mutagenesis cycles.

Example of Directed Evolution Impact

• Kemp Elimination Catalyst:

  • De-novo design improved through 7 rounds of directed evolution, leading to a >200 fold increase in catalytic efficiency:

  • Mutant KE07*: $k_{cat} ext{ (s}^{-1} ext{)} = 0.018$

  • R7 mutant: $k_{cat} = 1.37$

  • Best rational design (KE59): $k_{cat} = 0.29$

  • Rate Relationships:

  • $k<em>{cat}/K</em>m$ values given as:

    • KE07*: $12.2 ext{ M}^{-1} ext{s}^{-1}$

    • R7 mutant: $2590 ext{ M}^{-1} ext{s}^{-1}$

    • KE59: $163 ext{ M}^{-1} ext{s}^{-1}$

  • Rate enhancement observed as $1.6 imes 10^4$ for KE07*, $1.2 imes 10^6$ for R7 mutant, $2.5 imes 10^5$ for KE59.

Analysis of the R7 Mutant

1. Key residues (catalytic E101 and H-donor K222) were preserved during in vitro evolution.

2. Changes occurred in residues adjacent to designed positions, resulting in subtle fine-tuning of catalytic ability.

   • Directed evolution refines rationally designed structures further.

Catalytic Antibodies (Abzymes)

• Background:

  • Requires prior knowledge of the reaction mechanism.

  • Linus Pauling's recognition of the role of enzymes in stabilizing transition states (TS) in 1946:

  • "…in order to catalyse a reaction an enzyme must recognize the transition state in a selective way, i.e., it must stabilize it better than the substrate."

  • Enzymes catalyze reactions by lowering the free energy of the transition state, showing a greater affinity for the TS compared to substrates or products.

Development of Catalytic Antibodies

• William Jencks (1969) proposed the use of antibodies for catalyzing reactions:

  • "If complementarity between the active site and the transition state contributes significantly to enzymatic catalysis, it should be possible to synthesize an enzyme by constructing such an active site."

• General Protocol for Catalytic Antibody Production:

  1. Synthesize Transition State Analogue (TSA).

  2. Covalently link to a carrier protein.

  3. Immunize a mouse.

  4. Isolate B-cells from the spleen and fuse with myeloma cells to create immortal antibody-expressing hybridoma cells.

  5. Screen monoclonal antibodies for catalytic activity.

Transition State Analogues (TSA)

• Characteristics:

  • Transition states are unstable and cannot be isolated, hence the use of TSAs, which are stable approximations of the TS.

  • Success is contingent on how effectively the TSA approximates the actual transition state.

Examples of Transition State Analogues

1. Ester Hydrolysis:

   • The TSA approximates the transition state involving an incoming hydroxyl group, displaying different bond lengths than in the TS.

2. Metal Insertion into Porphyrin Ring:

   • The introduction of a methyl group distorts the mesoporphin ring, mimicking transition state structure for metal ion insertion.

   • Efficiency in catalyzing Zn2+ insertion compared to its natural enzyme counterpart.

   • Reference: Yin et al (2003) PNAS 100, 856-861.

Applications of Catalytic Antibodies

1. Novel Catalysis:

   • Available for aldol reactions, crucial in synthetic chemistry for carbon-carbon bond formation.

2. Drug Clearance:

   • Catalytic antibodies designed to metabolize cocaine effectively and treat overdoses:

     • Breakdown pathway: Cocaine → Ecgonine methyl ester → Benzoic acid.

     • Catalytic antibodies remain stable in plasma, enhancing their utility as therapeutic agents.

3. Pro-drug Activation:

   • Utilization in antibody-directed enzyme pro-drug therapy (ADEPT).

   • Clinical trials conducted with humanized catalytic antibodies to minimize immune responses.

Evaluation of Catalytic Antibodies

• Over 100 catalytic antibodies documented, demonstrating notable catalytic efficiency:

• Performance metrics include:

  • $k<em>{cat}/K</em>m$ ranging between $10^6 - 10^8 ext{ M}^{-1} ext{s}^{-1}$,

  • Rate enhancement as high as $10^6 - 10^{12}$,

  • Affinities for transition states varying across orders of magnitude.

Limitations of Catalytic Antibodies

• Challenges:

  • Imperfect TSA design may impact effectiveness.

  • Lack of intrinsic catalytic machinery (e.g., nucleophiles, bases, acids) restricts antibodies to maximizing binding interactions rather than facilitating catalysis.

  • Structural dynamics differ; antibodies have a more rigid binding site compared to diverse enzyme folds.

  • Naturally occurring enzymes may exploit alternate catalytic mechanisms not mimicked by TSAs.

• Improvement Strategies:

  • Site-Directed Mutagenesis: Introduce catalytic residues into antibody binding sites, necessitating high-resolution structural insights.

  • Directed Evolution: Enhance the catalytic efficiency of antibodies through iterative development.