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Patterned library analysis: A method for the quantitative assessment of hypotheses concerning the determinants of protein structure
- Source :
- Proceedings of the National Academy of Sciences. 96:14860-14865
- Publication Year :
- 1999
- Publisher :
- Proceedings of the National Academy of Sciences, 1999.
-
Abstract
- Site-directed mutagenesis and combinatorial libraries are powerful tools for providing information about the relationship between protein sequence and structure. Here we report two extensions that expand the utility of combinatorial mutagenesis for the quantitative assessment of hypotheses about the determinants of protein structure. First, we show that resin-splitting technology, which allows the construction of arbitrarily complex libraries of degenerate oligonucleotides, can be used to construct more complex protein libraries for hypothesis testing than can be constructed from oligonucleotides limited to degenerate codons. Second, using eglin c as a model protein, we show that regression analysis of activity scores from library data can be used to assess the relative contributions to the specific activity of the amino acids that were varied in the library. The regression parameters derived from the analysis of a 455-member sample from a library wherein four solvent-exposed sites in an α-helix can contain any of nine different amino acids are highly correlated (P< 0.0001,R2= 0.97) to the relative helix propensities for those amino acids, as estimated by a variety of biophysical and computational techniques.
- Subjects :
- chemistry.chemical_classification
Genetics
Multidisciplinary
Oligonucleotide
Oligonucleotides
Proteins
Mutagenesis (molecular biology technique)
Regression analysis
Computational biology
Biology
Protein Structure, Secondary
Protein Structure, Tertiary
Amino acid
Protein structure
Protein sequencing
Models, Chemical
chemistry
Mutagenesis
Protein methods
Commentary
Combinatorial Chemistry Techniques
Regression Analysis
Amino Acids
Serpins
Statistical hypothesis testing
Subjects
Details
- ISSN :
- 10916490 and 00278424
- Volume :
- 96
- Database :
- OpenAIRE
- Journal :
- Proceedings of the National Academy of Sciences
- Accession number :
- edsair.doi.dedup.....6259f4a04d81bd4846405d52b77a185e
- Full Text :
- https://doi.org/10.1073/pnas.96.26.14860