1/16 A linguistic model for the rational design of antimicrobial peptides Reporter: Yu Lun Kuo...
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Transcript of 1/16 A linguistic model for the rational design of antimicrobial peptides Reporter: Yu Lun Kuo...
1/16
A linguistic model for the rational design of antimicrobial peptides
Reporter: Yu Lun KuoE-mail: [email protected]: December 19, 2006
Christopher Loose1*, Kyle Jensen1,2,3*, Isidore Rigoutsos1,4 & Gregory Stephanopoulos1
Vol 443|19 October 2006|doi:10.1038/nature05233
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Outline
• Introduction
• Method
• Conclusion
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Introduction
• Antimicrobial peptides (AmPs) are small proteins
– Used by the innate immune system to combat bacterial infection in multicellular eukaryotes
• The rational design of new AmPs– Strong bacteriostatic activity against several species
of bacteria• Including Staphylococcus aureus and Bacillus anthracis
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Introduction
• These peptides were designed using a linguistic model of natural AmPs– Treated the amino-acid sequences of natural Am
Ps as a formal language
– Build a set of regular grammars to describe this language
• Create new, unnatural AmP sequences
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Introduction
• AmPs might have other interesting clinical applications– Act as adjuvants for the adaptive immune syste
m and might be useful certain cancers
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Introduction
• The preliminary studies of natural AmPs– Repeated usage of sequence modules
– Reminiscent of phrases in a natural language• Such as English
• The pattern QxEAGxLxKxxK is found in more than 90% of the insect AmPs known as cecropins
– We conjectured that the ‘language of AmPs’ could be described by a set of regular grammars
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Method
• Used the Teiresias pattern discovery tool– Find a set of regular grammars to describe AmPs
• Derived a set of 684 regular grammars
• Occur commonly in 526 well-characterized eukaryotic AmP sequences
– From the Antimicrobial Peptide Database (APD)
– http://aps.unmc.edu/AP/main.php
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• By design, each grammar in this set of ~700 grammars is ten amino-acids long
• To design unnatural AmPs, we combinatorially enumerated all grammatical sequences of length twenty – Each window of size ten in the 20-mers was matched by one
of the ~700 grammars
– This length because we could easily chemically synthesize 20-mers and this length is close to the median length of AmPs in the APD
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• We also designed a shuffled sequence– The order of the amino acids was rearranged randomly
– The sequence didn’t match any grammars
• We hypothesized that because the shuffled sequences were ‘ungrammatical’ – The would have no antimicrobial activity
• Despite having the same bulk physiochemical characteristics
– We selected eight peptides from the APD as positive controls and six 20-mers form non-antimicrobial proteins as negative controls
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• We characterized the activity of each synthetic AmP using a both microdilution assay
• This assay measures the minimum inhibitory concentration (MIC)– At the peptide inhibits growth of the target organis
m
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• To validate MIC determinations, we measured optical density at varying concentrations of a representative set of designed, shuffled, and natural peptides
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• Two designed peptides, D28 and D51, had MICs of 16 μgml–1 against Bacillus anthracis, which is equivalent to the activity of Cecropinmelittin hybrid
• We optimized our best candidate, peptide D28– D28 also had an MIC of 8 μgml–1 against S. aure
us
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Conclusion
• Our linguistic approach to designing synthetic AmPs might be successful because of the pronounced modular nature of natural AmP amino-acid sequences– This approach can be used to expand the AmP se
quence space rationally without using structure-activity information or complex simulations of the interactions of a peptide with a membrane
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Conclusion
• We hope that this approach will help to expand the diversity of known AmPs well beyond those found in nature, possibly leading to new candidates for AmP-based antibiotic therapeutics
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Thanks for your attention