Difference between revisions of "Protein engineering"
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| − | + | <strong>Protein engineering</strong> is the application of science, mathematics, and bioinformatics to the process of developing valuable proteins. It has been an old discipline, with much research taking place into the understanding of protein folding and protein recognition for protein design principles. | |
<p>There are two general strategies for protein engineering. The first is known as <em>rational design</em>, in which the scientist uses detailed knowledge of the structure and function of the protein to make desired changes. This has the advantage of being generally inexpensive and easy, since site-directed mutagenesis techniques are well-developed. However, there is a major drawback in that detailed structural knowledge of a protein is often unavailable, and even when it is available, it can be extremely difficult to predict the effects of various mutations.</p> | <p>There are two general strategies for protein engineering. The first is known as <em>rational design</em>, in which the scientist uses detailed knowledge of the structure and function of the protein to make desired changes. This has the advantage of being generally inexpensive and easy, since site-directed mutagenesis techniques are well-developed. However, there is a major drawback in that detailed structural knowledge of a protein is often unavailable, and even when it is available, it can be extremely difficult to predict the effects of various mutations.</p> | ||
<p>Computational protein design algorithms seek to identify amino acid sequences that have low energies for target structures. While the sequence-conformation space that needs to be searched is large, the most challenging requirement for computational protein design is a fast, yet accurate, energy function that can distinguish optimal sequences from similar suboptimal ones. Using computational methods, a protein with a novel fold has been designed[1], as well as sensors for un-natural molecules[2].</p> | <p>Computational protein design algorithms seek to identify amino acid sequences that have low energies for target structures. While the sequence-conformation space that needs to be searched is large, the most challenging requirement for computational protein design is a fast, yet accurate, energy function that can distinguish optimal sequences from similar suboptimal ones. Using computational methods, a protein with a novel fold has been designed[1], as well as sensors for un-natural molecules[2].</p> | ||
<p>The second strategy is known as directed evolution. This is where random mutagenesis is applied to a protein, and a selection regime is used to pick out variants that have the desired qualities. Further rounds of mutation and selection are then applied. This method mimics natural evolution and generally produces superior results to rational design. An additional technique known as DNA shuffling mixes and matches pieces of successful variants in order to produce better results. This process mimics recombination that occurs naturally during sexual reproduction. The great advantage of directed evolution techniques is that they require no prior structural knowledge of a protein, nor it is 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 no one would have expected. The drawback is that they require high-throughput, which is not feasible for all proteins. Large amounts of recombinant DNA must be mutated and the products screened for desired qualities. The sheer number of variants often requires expensive robotic equipment to automate the process. Furthermore, not all desired activities can be easily screened for.</p> | <p>The second strategy is known as directed evolution. This is where random mutagenesis is applied to a protein, and a selection regime is used to pick out variants that have the desired qualities. Further rounds of mutation and selection are then applied. This method mimics natural evolution and generally produces superior results to rational design. An additional technique known as DNA shuffling mixes and matches pieces of successful variants in order to produce better results. This process mimics recombination that occurs naturally during sexual reproduction. The great advantage of directed evolution techniques is that they require no prior structural knowledge of a protein, nor it is 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 no one would have expected. The drawback is that they require high-throughput, which is not feasible for all proteins. Large amounts of recombinant DNA must be mutated and the products screened for desired qualities. The sheer number of variants often requires expensive robotic equipment to automate the process. Furthermore, not all desired activities can be easily screened for.</p> | ||
<p>Rational design and directed evolution techniques are not mutally exclusive; good researchers will often apply both. In the future, more detailed knowledge of protein structure and function, as well as advancements in high-throughput technology, will greatly expand the capabilities of protein engineering.</p> | <p>Rational design and directed evolution techniques are not mutally exclusive; good researchers will often apply both. In the future, more detailed knowledge of protein structure and function, as well as advancements in high-throughput technology, will greatly expand the capabilities of protein engineering.</p> | ||
| − | <p><a | + | <p><a name="See_also" id="See_also"></a></p> |
<h2><span class="editsection"></span><span class="mw-headline">See also</span></h2> | <h2><span class="editsection"></span><span class="mw-headline">See also</span></h2> | ||
<ul> | <ul> | ||
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<li>Structome</li> | <li>Structome</li> | ||
</ul> | </ul> | ||
| − | <p><a | + | <p><a name="External_links" id="External_links"></a></p> |
<h2><span class="editsection"></span><span class="mw-headline">External links</span></h2> | <h2><span class="editsection"></span><span class="mw-headline">External links</span></h2> | ||
<ul> | <ul> | ||
| − | <li><a | + | <li><a href="http://biologicalworld.com/sitedirectedmutagenesis.htm" rel="nofollow" title="http://biologicalworld.com/sitedirectedmutagenesis.htm" class="external text">Site-Directed Mutagenesis Protocol</a> </li> |
| − | <li><a | + | <li><a href="http://mrc-cpe.cam.ac.uk/" rel="nofollow" title="http://mrc-cpe.cam.ac.uk" class="external text">Centre for Protein Engineering</a> </li> |
| − | <li><a | + | <li><a href="http://peds.oupjournals.org/" rel="nofollow" title="http://peds.oupjournals.org/" class="external text">Protein Engineering Design and Selection</a> </li> |
| − | <li><a | + | <li><a href="http://www.structure.org/" rel="nofollow" title="http://www.structure.org/" class="external text">Structure with Folding & Design</a> </li> |
| − | <li><a | + | <li><a href="http://egad.ucsd.edu/EGAD_manual/index.html" rel="nofollow" title="http://egad.ucsd.edu/EGAD_manual/index.html" class="external text">EGAD; a free and open-source program for automated protein design</a> </li> |
</ul> | </ul> | ||
Latest revision as of 23:28, 27 September 2007
Protein engineering is the application of science, mathematics, and bioinformatics to the process of developing valuable proteins. It has been an old discipline, with much research taking place into the understanding of protein folding and protein recognition for protein design principles.
There are two general strategies for protein engineering. The first is known as rational design, in which the scientist uses detailed knowledge of the structure and function of the protein to make desired changes. This has the advantage of being generally inexpensive and easy, since site-directed mutagenesis techniques are well-developed. However, there is a major drawback in that detailed structural knowledge of a protein is often unavailable, and even when it is available, it can be extremely difficult to predict the effects of various mutations.
Computational protein design algorithms seek to identify amino acid sequences that have low energies for target structures. While the sequence-conformation space that needs to be searched is large, the most challenging requirement for computational protein design is a fast, yet accurate, energy function that can distinguish optimal sequences from similar suboptimal ones. Using computational methods, a protein with a novel fold has been designed[1], as well as sensors for un-natural molecules[2].
The second strategy is known as directed evolution. This is where random mutagenesis is applied to a protein, and a selection regime is used to pick out variants that have the desired qualities. Further rounds of mutation and selection are then applied. This method mimics natural evolution and generally produces superior results to rational design. An additional technique known as DNA shuffling mixes and matches pieces of successful variants in order to produce better results. This process mimics recombination that occurs naturally during sexual reproduction. The great advantage of directed evolution techniques is that they require no prior structural knowledge of a protein, nor it is 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 no one would have expected. The drawback is that they require high-throughput, which is not feasible for all proteins. Large amounts of recombinant DNA must be mutated and the products screened for desired qualities. The sheer number of variants often requires expensive robotic equipment to automate the process. Furthermore, not all desired activities can be easily screened for.
Rational design and directed evolution techniques are not mutally exclusive; good researchers will often apply both. In the future, more detailed knowledge of protein structure and function, as well as advancements in high-throughput technology, will greatly expand the capabilities of protein engineering.
See also
- Display:
- Bacterial display
- Phage display
- mRNA display
- Ribosome display
- Yeast display
- Enzymology
- Protein folding
- Protein design
- Proteinengineering.org
- Proteinomics
- Proteome
- Structural biology
- Structome
