A linguistic model for the rational design of antimicrobial peptides.
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.
Loose
Christopher
C
Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA.
Jensen
Kyle
K
Rigoutsos
Isidore
I
Stephanopoulos
Gregory
G
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
D000900:Anti-Bacterial Agents; D023181:Antimicrobial Cationic Peptides