Chapter title |
Computational Design of DNA-Binding Proteins.
|
---|---|
Chapter number | 16 |
Book title |
Computational Design of Ligand Binding Proteins
|
Published in |
Methods in molecular biology, January 2016
|
DOI | 10.1007/978-1-4939-3569-7_16 |
Pubmed ID | |
Book ISBNs |
978-1-4939-3567-3, 978-1-4939-3569-7
|
Authors |
Summer Thyme, Yifan Song, Thyme, Summer, Song, Yifan |
Editors |
Barry L. Stoddard |
Abstract |
Predicting the outcome of engineered and naturally occurring sequence perturbations to protein-DNA interfaces requires accurate computational modeling technologies. It has been well established that computational design to accommodate small numbers of DNA target site substitutions is possible. This chapter details the basic method of design used in the Rosetta macromolecular modeling program that has been successfully used to modulate the specificity of DNA-binding proteins. More recently, combining computational design and directed evolution has become a common approach for increasing the success rate of protein engineering projects. The power of such high-throughput screening depends on computational methods producing multiple potential solutions. Therefore, this chapter describes several protocols for increasing the diversity of designed output. Lastly, we describe an approach for building comparative models of protein-DNA complexes in order to utilize information from homologous sequences. These models can be used to explore how nature modulates specificity of protein-DNA interfaces and potentially can even be used as starting templates for further engineering. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Unknown | 13 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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Researcher | 4 | 31% |
Student > Postgraduate | 2 | 15% |
Student > Ph. D. Student | 2 | 15% |
Student > Master | 2 | 15% |
Other | 1 | 8% |
Other | 1 | 8% |
Unknown | 1 | 8% |
Readers by discipline | Count | As % |
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Agricultural and Biological Sciences | 2 | 15% |
Pharmacology, Toxicology and Pharmaceutical Science | 1 | 8% |
Neuroscience | 1 | 8% |
Chemistry | 1 | 8% |
Other | 1 | 8% |
Unknown | 2 | 15% |