Editing Protein engineering (section)

=== Directed evolution ===
{{main|Directed evolution}}
In directed evolution, random [[mutagenesis]], e.g. by [[error-prone PCR]] or [[sequence saturation mutagenesis]], is applied to a protein, and a selection regime is used to select variants having desired traits.  Further rounds of mutation and selection are then applied.  This method mimics natural [[evolution]] and, in general, produces superior results to rational design. An added process, termed [[DNA shuffling]], mixes and matches pieces of successful variants to produce better results.  Such processes mimic the [[homologous recombination|recombination]] that occurs naturally during [[sexual reproduction]].  Advantages of directed evolution are that it requires no prior structural knowledge of a protein, nor is it necessary to be able to predict what effect a given mutation will have.  Indeed, the results of directed evolution experiments are often surprising in that desired changes are often caused by mutations that were not expected to have some effect.  The drawback is that they require [[high-throughput screening]], which is not feasible for all proteins.  Large amounts of [[recombinant DNA]] must be mutated and the products screened for desired traits.  The large number of variants often requires expensive robotic equipment to automate the process.  Further, not all desired activities can be screened for easily.

Natural Darwinian evolution can be effectively imitated in the lab toward tailoring protein properties for diverse applications, including catalysis. Many experimental technologies exist to produce large and diverse protein libraries and for screening or selecting folded, functional variants. Folded proteins arise surprisingly frequently in random sequence space, an occurrence exploitable in evolving selective binders and catalysts. While more conservative than direct selection from deep sequence space, redesign of existing proteins by random mutagenesis and selection/screening is a particularly robust method for optimizing or altering extant properties. It also represents an excellent starting point for achieving more ambitious engineering goals. Allying experimental evolution with modern computational methods is likely the broadest, most fruitful strategy for generating functional macromolecules unknown to nature.<ref>{{cite journal |last1=Jäckel |first1=Christian |last2=Kast |first2=Peter |last3=Hilvert |first3=Donald |title=Protein Design by Directed Evolution |journal=Annual Review of Biophysics |date=June 2008 |volume=37 |issue=1 |pages=153–173 |doi=10.1146/annurev.biophys.37.032807.125832 |pmid=18573077 }}</ref>

The main challenges of designing high quality mutant libraries have shown significant progress in the recent past. This progress has been in the form of better descriptions of the effects  of mutational loads on protein traits. Also computational approaches have shown large advances in the innumerably large sequence space to more manageable screenable sizes, thus creating smart libraries of mutants. Library size has also been reduced to more screenable sizes by the identification of key beneficial residues using algorithms for systematic recombination. Finally a significant step forward toward efficient reengineering of enzymes has been made with the development of more accurate statistical models and algorithms quantifying and predicting coupled mutational effects on protein functions.<ref>{{Cite journal|last1=Shivange|first1=Amol V|last2=Marienhagen|first2=Jan|last3=Mundhada|first3=Hemanshu|last4=Schenk|first4=Alexander|last5=Schwaneberg|first5=Ulrich|title=Advances in generating functional diversity for directed protein evolution|journal=Current Opinion in Chemical Biology|language=en|volume=13|issue=1|pages=19–25|doi=10.1016/j.cbpa.2009.01.019|pmid=19261539|year=2009}}</ref>

Generally, directed evolution may be summarized as an iterative two step process which involves generation of protein mutant libraries, and high throughput screening processes to select for variants with improved traits. This technique does not require prior knowledge of the protein structure and function relationship. Directed evolution utilizes random or focused mutagenesis to generate libraries of mutant proteins. Random mutations can be introduced using either error prone PCR, or site saturation mutagenesis. Mutants may also be generated using recombination of multiple homologous genes. Nature has evolved a limited number of beneficial sequences. Directed evolution makes it possible to identify undiscovered protein sequences which have novel functions. This ability is contingent on the proteins ability to tolerant amino acid residue substitutions without compromising folding or stability.<ref name=PoluriBook/>{{page needed|date=May 2017}}

Directed evolution methods can be broadly categorized into two strategies, asexual and sexual methods.