title: De novo identification of binding sequences for antibody replacement molecules.
abstract: A new in silico method has been developed that automatically identifies peptide sequences that can bind to targets of known three-dimensional structure. The method is potentially faster and more economical than traditional methods of raising antibodies by means of hybridomas or biopanning technology. The current algorithm creates an initial peptide library that is either completely random or that is constrained by the user. This library represents only a small fraction of possible sequence space and the peptides are created with a specified torsional geometry. The library is used as input to any number of available molecular docking programs and the library is docked and scored. The final rank ordering is then used to create a new library by constraining that library to the sequence conservation pattern deduced from the top N-scoring peptides in the first round. Successive rounds of screening, scoring, and new library creation ultimately results in the system converging to a final solution set of peptides. To test the method, a family of novel peptides that can bind to, and inhibit the enzyme Deoxyribonuclease I has been discovered. The peptides inhibit the enzyme either alone or when placed into a protein backbone structure as has been confirmed experimentally.
authors.affiliation: Kimberly-Clark Corporation, Roswell, Georgia 30076, USA.
authors.forename: Stephen
authors.initials: S
authors.lastname: Quirk
authors.forename: Shi
authors.initials: S
authors.lastname: Zhong
authors.forename: Rigoberto
authors.initials: R
authors.lastname: Hernandez
mesh_terms: D000465:Algorithms; D000911:Antibodies, Monoclonal / Q000737:chemistry*; D001665:Binding Sites; D010455:Peptides / Q000737:chemistry*; D011485:Protein Binding
chemical_list: D000911:Antibodies, Monoclonal; D010455:Peptides