title: Enriching Peptide Libraries for Binding Affinity and Specificity Through Computationally Directed Library Design.
abstract: 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.
authors.affiliation: 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.
authors.forename: Glenna Wink
authors.initials: GW
authors.lastname: Foight
authors.affiliation: Department of Biology, Massachusetts Institute of Technology, 77 Massachusetts Ave., Bldg., 68-622, Cambridge, MA, 02139, USA.|Google Inc., Mountain View, CA, 94043, USA.
authors.forename: T Scott
authors.initials: TS
authors.lastname: Chen
authors.affiliation: Department of Biology, Massachusetts Institute of Technology, 77 Massachusetts Ave., Bldg., 68-622, Cambridge, MA, 02139, USA.
authors.forename: Daniel
authors.initials: D
authors.lastname: Richman
authors.affiliation: 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.
authors.forename: Amy E
authors.initials: AE
authors.lastname: Keating
mesh_terms: D000465:Algorithms; D000595:Amino Acid Sequence; D001665:Binding Sites; D019295:Computational Biology / Q000379:methods*; D006801:Humans; D010446:Peptide Fragments / Q000737:chemistry* / Q000378:metabolism*; D019151:Peptide Library; D011485:Protein Binding; D011506:Proteins / Q000737:chemistry / Q000378:metabolism*; D013379:Substrate Specificity
chemical_list: D010446:Peptide Fragments; D019151:Peptide Library; D011506:Proteins
keywords: Integer linear programming; Library design; Peptide engineering