title: Exploration of sequence space for protein engineering.
abstract: The process of protein engineering is currently evolving towards a heuristic understanding of the sequence-function relationship. Improved DNA sequencing capacity, efficient protein function characterization and improved quality of data points in conjunction with well-established statistical tools from other industries are changing the protein engineering field. Algorithms capturing the heuristic sequence-function relationships will have a drastic impact on the field of protein engineering. In this review, several alternative approaches to quantitatively assess sequence space are discussed and the relatively few examples of wet-lab validation of statistical sequence-function characterization/correlation are described.
authors.affiliation: Maxygen Inc., Galveston Drive 515, Redwood City, CA 94063, USA. claes.gustafsson@maxygen.com
authors.forename: C
authors.initials: C
authors.lastname: Gustafsson
authors.forename: S
authors.initials: S
authors.lastname: Govindarajan
authors.forename: R
authors.initials: R
authors.lastname: Emig
mesh_terms: D000465:Algorithms; D005075:Biological Evolution; D004247:DNA / Q000032:analysis; D019992:Databases as Topic; D008962:Models, Theoretical; D016296:Mutagenesis; D015202:Protein Engineering / Q000379:methods*
chemical_list: D004247:DNA