title: A linguistic model for the rational design of antimicrobial peptides.
abstract: Antimicrobial peptides (AmPs) are small proteins that are used by the innate immune system to combat bacterial infection in multicellular eukaryotes. There is mounting evidence that these peptides are less susceptible to bacterial resistance than traditional antibiotics and could form the basis for a new class of therapeutic agents. Here we report the rational design of new AmPs that show limited homology to naturally occurring proteins but have strong bacteriostatic activity against several species of bacteria, including Staphylococcus aureus and Bacillus anthracis. These peptides were designed using a linguistic model of natural AmPs: we treated the amino-acid sequences of natural AmPs as a formal language and built a set of regular grammars to describe this language. We used this set of grammars to create new, unnatural AmP sequences. Our peptides conform to the formal syntax of natural antimicrobial peptides but populate a previously unexplored region of protein sequence space.
authors.affiliation: Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA.
authors.forename: Christopher
authors.initials: C
authors.lastname: Loose
authors.forename: Kyle
authors.initials: K
authors.lastname: Jensen
authors.forename: Isidore
authors.initials: I
authors.lastname: Rigoutsos
authors.forename: Gregory
authors.initials: G
authors.lastname: Stephanopoulos
mesh_terms: D000595:Amino Acid Sequence; D000900:Anti-Bacterial Agents / Q000737:chemistry* / Q000494:pharmacology*; D023181:Antimicrobial Cationic Peptides / Q000737:chemistry* / Q000494:pharmacology*; D019295:Computational Biology / Q000379:methods*; D015195:Drug Design; D008037:Linguistics / Q000379:methods*; D008826:Microbial Sensitivity Tests; D008962:Models, Theoretical; D008969:Molecular Sequence Data
chemical_list: D000900:Anti-Bacterial Agents; D023181:Antimicrobial Cationic Peptides