دورية أكاديمية
Enriching Peptide Libraries for Binding Affinity and Specificity Through Computationally Directed Library Design.
| العنوان: | Enriching Peptide Libraries for Binding Affinity and Specificity Through Computationally Directed Library Design. |
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| المؤلفون: | Foight GW; Department of Biology, Massachusetts Institute of Technology, 77 Massachusetts Ave., Bldg., 68-622, Cambridge, MA, 02139, USA.; Department of Chemistry, University of Washington, Seattle, WA, 98195, USA., Chen TS; Department of Biology, Massachusetts Institute of Technology, 77 Massachusetts Ave., Bldg., 68-622, Cambridge, MA, 02139, USA.; Google Inc., Mountain View, CA, 94043, USA., Richman D; Department of Biology, Massachusetts Institute of Technology, 77 Massachusetts Ave., Bldg., 68-622, Cambridge, MA, 02139, USA., Keating AE; Department of Biology, Massachusetts Institute of Technology, 77 Massachusetts Ave., Bldg., 68-622, Cambridge, MA, 02139, USA. keating@mit.edu.; Department of Biological Engineering, Massachusetts Institute of Technology, 77 Massachusetts Ave., Bldg., 68-622, Cambridge, MA, 02139, USA. keating@mit.edu. |
| المصدر: | Methods in molecular biology (Clifton, N.J.) [Methods Mol Biol] 2017; Vol. 1561, pp. 213-232. |
| نوع المنشور: | Journal Article; Research Support, N.I.H., Extramural |
| اللغة: | English |
| بيانات الدورية: | Publisher: Humana Press Country of Publication: United States NLM ID: 9214969 Publication Model: Print Cited Medium: Internet ISSN: 1940-6029 (Electronic) Linking ISSN: 10643745 NLM ISO Abbreviation: Methods Mol Biol Subsets: MEDLINE |
| أسماء مطبوعة: | Publication: Totowa, NJ : Humana Press Original Publication: Clifton, N.J. : Humana Press, |
| مواضيع طبية MeSH: | Algorithms* , Peptide Library*, Computational Biology/*methods , Peptide Fragments/*chemistry , Peptide Fragments/*metabolism , Proteins/*metabolism, Amino Acid Sequence ; Binding Sites ; Humans ; Protein Binding ; Proteins/chemistry ; Substrate Specificity |
| مستخلص: | Peptide reagents with high affinity or specificity for their target protein interaction partner are of utility for many important applications. Optimization of peptide binding by screening large libraries is a proven and powerful approach. Libraries designed to be enriched in peptide sequences that are predicted to have desired affinity or specificity characteristics are more likely to yield success than random mutagenesis. We present a library optimization method in which the choice of amino acids to encode at each peptide position can be guided by available experimental data or structure-based predictions. We discuss how to use analysis of predicted library performance to inform rounds of library design. Finally, we include protocols for more complex library design procedures that consider the chemical diversity of the amino acids at each peptide position and optimize a library score based on a user-specified input model. |
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| معلومات مُعتمدة: | R01 GM110048 United States GM NIGMS NIH HHS |
| فهرسة مساهمة: | Keywords: Integer linear programming; Library design; Peptide engineering |
| المشرفين على المادة: | 0 (Peptide Fragments) 0 (Peptide Library) 0 (Proteins) |
| تواريخ الأحداث: | Date Created: 20170226 Date Completed: 20180214 Latest Revision: 20181113 |
| رمز التحديث: | 20231215 |
| مُعرف محوري في PubMed: | PMC5553629 |
| DOI: | 10.1007/978-1-4939-6798-8_13 |
| PMID: | 28236241 |
| قاعدة البيانات: | MEDLINE |
| تدمد: | 1940-6029 |
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| DOI: | 10.1007/978-1-4939-6798-8_13 |